EfficiencyOne
AI summary The document pertains to a regulatory proceeding involving 'EfficiencyOne,' though no further details are provided in the text. The context suggests it relates to energy efficiency initiatives in Nova Scotia.
1. EXECUTIVE SUMMARY - EfficiencyOne ("E1") delivers demand side management ("DSM") programs and is the - administrator and operator of the Efficiency Nova Scotia ("ENS") franchise. The 2024 Annual - Progress Report ("APR") summarizes E1's...
AI summary EfficiencyOne (E1) administers the Efficiency Nova Scotia (ENS) franchise and reports on its 2024 demand side management (DSM) program results. The 2023-2025 DSM Plan, approved by the Nova Scotia Utility and Review Board (NSUARB) with a $173M investment, set four performance targets. In 2024, E1 achieved 74% progress toward the 412.7 GWh energy savings target and partial progress on other metrics.
2. 2024 PLAN AS APPROVED AND 2024 MID-COURSE TARGETS - 2024 Plan targets are 142.6 GWh of incremental annual net energy savings, 25.6 MW of annual - net peak demand savings, and 10.0 MW of available capacity, within an investment of $57.5...
AI summary The 2024 Plan targets 142.6 GWh energy savings, 25.6 MW peak demand savings, and 10.0 MW capacity with a $57.5M investment. E1 adjusted mid-course targets to 142.6 GWh, 25.7 MW, 7.2 MW, and $59.6M, aligning with market trends and evaluations.
3. 2024 PORTFOLIO RESULTS - In comparison to E1's 2024 mid-course targets, E1 achieved the following results: - 172.8 GWh of incremental annual net energy savings (121% of the mid-course adjusted target of 142.6 GWh); - 30.7 MW of annual n...
AI summary EfficiencyOne (E1) exceeded 2024 mid-course energy and demand savings targets by 121% for energy savings, 119% for peak demand, and 113% for demand response capacity. Achievements were driven by Residential and Business, Non-Profit, and Institutional sectors, with specific programs like the Mi'kmaw Home Energy Efficiency Project meeting 100% of their allocated targets.
Table 1: 2024 Results to 2024 Plan as Approved, 2024 Mid-Course Adjustments, and 2024 Year-End Forecast abic 1. 2024 Nest 1111 , Energy Efficiency (EE) Programs • Efficient Product Rebates 10.4 91.2 1.1 4.6 - 14.5 125.4 2.0 5.9 - 17.2 149....
AI summary Table 1 presents the 2024 results compared to the approved 2024 plan, mid-course adjustments, and year-end forecasts for energy efficiency programs including Efficient Product Rebates, Appliance Retirement, Instant Savings, and Existing Residential initiatives.
3.2 2024 Participation Result[s](#page-10-1) [Table 2](#page-10-1) presents E1's 2024 participation results. The table provides a comparison of 2024 participation results to those modelled in the 2024 Plan, the 2024 mid-course participatio...
AI summary E1's 2024 participation results show mixed trends across programs. Instant Savings saw high participation due to increased rebates, while Affordable Single-family Homes saw a fivefold increase. Small Business Energy Solutions improved in Q4 after eligibility adjustments, though Retrofit service participation remained low. Home Energy Assessment benefited from Canada Greener Homes Grant completions.
3.4 2024 Unit Cost - Unit cost data is a calculation output of E1's investment and savings over a defined time period. - Factors that influence unit cost results typically include: - the level of participation in a program or program compo...
AI summary E1 achieved a 2024 portfolio-level unit cost of $0.36/kWh, below mid-course adjusted ($0.39/kWh) and year-end forecasted ($0.43/kWh) targets. Residential results ($0.40/kWh) improved due to overperformance in rebate programs, while BNI results ($0.26/kWh) benefited from Custom Incentives. Increased incentives and policy changes in Direct Installation raised unit costs by 10% year-over-year.
4. FORECAST FOR 2023-2025 DSM PLAN PERIOD E1's three-year Plan forecast provides additional insight on the DSM Plan implementation after the first two years. It includes E1's actual savings results and expenditures from 2023 and 2024, and...
AI summary E1's 2023-2025 DSM Plan forecasts $173 million in investment, aiming to meet 90% compliance on three performance targets (energy, demand savings, and affordable housing). However, challenges in the Demand Response program, including low participant engagement and paused initiatives, are expected to cause a shortfall in the 17.9 MW capacity target. E1 highlights ongoing learning and adaptation of the program as key to future improvements.
1 4.1 2025 Forecast – Detailed program information - 2 In developing the 2025 forecast, which is the final year of 2023-2025 DSM Plan, a number of 3 assumptions were made and a variety of factors were considered, including: - 4 Following r...
AI summary E1's 2025 forecast for the final year of the 2023-2025 DSM Plan outlines expected reductions in energy savings due to the closure of the Canada Greener Homes Grant, changes in rebate structures for LED lighting, and the end of the Appliance Retirement program. Despite these challenges, E1 anticipates continued delivery of DSM programs and meeting low-income performance targets.
1 Table 5: 2025 Plan as Approved and 2025 Forecast 2025 Plan as Approved 2025 Forecast First-Year Energy Savings (GWh) Peak EE Demand Savings (MW) Investment ($ million) Available Capacity (MW) First-Year Energy Savings (GWh) Peak EE Deman...
AI summary Table 5 outlines the 2025 Plan as Approved and 2025 Forecast for energy efficiency and demand response programs in Nova Scotia. It details energy savings, investment, and capacity for various initiatives, including Efficient Product Rebates, Appliance Retirement, and Demand Response programs.
terviews with participants and E1 staff 23 involved in delivering the program component, as well as interviews with participants 24 who dropped out and non-participants to understand any barriers that may exist to 25 participation. Afforda...
AI summary The 2024 evaluation activities include process evaluations for E1 programs like Affordable Single-Family Homes, Instant Rebates, and New Construction services. Methods involved interviews, surveys, and jurisdictional scans. The DSM Measure Assessment was updated for 2023-2025, revising commercial lighting methodologies. Results sections for residential, BNI, and Demand Response programs are outlined in subsequent sections.
4 5.2.1 Residential Efficient Product Rebates - 5 The Residential Efficient Product Rebates program consists of two program components: - 6 Appliance Retirement; and - 7 Instant Savings. 8
AI summary The Residential Efficient Product Rebates program in Nova Scotia includes two components: Appliance Retirement and Instant Savings, aimed at promoting energy efficiency through rebate incentives for residential consumers.
9 Table 6: 2024 Residential Efficient Product Rebates RESIDENTIAL EFFICIENT PRODUCT REBATES (2024) Residential Efficient Product Rebates Energy Savings (GWh) Demand Savings (MW) Expenditure ($ million) 2024 Results 24.6 2.8 8.2 2024 MCA Ta...
AI summary Residential Efficient Product Rebates exceeded 2024 MCA targets for energy and demand savings due to higher-than-expected uptake from increased rebates on LED products in the Instant Savings program's spring and fall campaigns. The fall campaign's 80% rebate (up from 70% in spring) drove increased expenditures.
Program Components - Appliance Retirement retires old, inefficient household appliances (e.g., refrigerators, freezers, room air conditioners) by offering free appliance pick-up from homes, proper recycling, and a financial incentive. The...
AI summary The document outlines two program components: Appliance Retirement, which retires inefficient household appliances and coordinates replacements under specific initiatives, and Instant Savings, offering point-of-sale rebates for energy-efficient purchases. Both aim to enhance energy efficiency and support eligible participants.
Appliance Retirement Highlights • Appliance Retirement energy and demand savings were consistent with expectations in 2024; however rising delivery costs combined with declining savings from increasingly newer and more efficient units bein...
AI summary Appliance Retirement program savings in 2024 were consistent but faced challenges from rising delivery costs and declining savings due to retiring newer, efficient units, prompting a program review. Savings are attributed to HomeWarming and Mi'kmaw Home Energy Efficiency Project, with E1 administering the former using DSM funds for non-electrically heated homes.
Instant Savings Highlights - Instant Savings' two major campaigns (spring and fall) saw high uptake and very strong results in terms of unit sales and energy and demands savings achieved, compared to previous years. This was driven primari...
AI summary Instant Savings' spring and fall campaigns in 2024 achieved high uptake and strong energy/demand savings due to 70-80% rebates and targeted marketing for LED products. Digital campaigns also contributed to consistent savings. The Evaluator's survey indicated lower freeridership than previous years.
2 5.2.2 Existing Residential - 3 The Existing Residential program consists of the following program components: - 4 Affordable Multi-family Housing and Non-Profit Organizations; - 5 Affordable Single-family Homes; - 6 Efficient Product Ins...
AI summary The Existing Residential program includes components such as Affordable Multi-family Housing, Efficient Product Installation, Green Heat, Home Energy Assessments, and the Mi'kmaw Home Energy Efficiency Project, aimed at improving residential energy efficiency through various initiatives.
3 Table 7: 2024 Existing Residential EXISTING RESIDENTIAL (2024) Existing Residential Energy Savings (GWh) Demand Savings (MW) Expenditure ($ million) 2024 Results 53.3 14.2 23.1 2024 MCA Target 46.5 11.5 19.7 • Existing Residential exceed...
AI summary The 2024 Existing Residential program exceeded mid-course adjusted energy (53.3 GWh vs. 46.5 GWh) and demand (14.2 MW vs. 11.5 MW) savings targets, driven by increased participation in the Canada Greener Homes Grant (co-delivered by E1 and Natural Resources Canada). Expenditure of $23.1M exceeded the $19.7M target due to higher Affordable Single-family Homes participation.
Affordable Single-family Homes - Affordable Single-Family Homes achieved 3.7 GWh in energy savings and 2.1 MW in demand savings in 2024, both significant increases from 2023, as some of the challenges experienced when the program component...
AI summary The Affordable Single-family Homes program achieved 3.7 GWh energy savings and 2.1 MW demand savings in 2024, with participation rising fivefold compared to 2023. Challenges included software overestimation adjustments and limited upgrade opportunities in newer electric homes. Additional delivery agents and heat pump contractors were added to meet increased demand from provincial/federal funding. Automated emails improved communication.
Efficient Product Installation Highlights - Energy and demand savings in Efficient Product Installation in 2024 were consistent with 2023, but fell short of mid-course adjusted targets due to increasing measure saturation. With fewer measu...
AI summary Energy and demand savings from Efficient Product Installation in 2024 remained consistent with 2023 but missed mid-course adjusted targets due to measure saturation. Lower installation rates for smart thermostats and LED lamps, along with reduced average savings per household, contributed to this shortfall. Electrician-installed measures and new marketing campaigns are expected to improve outcomes in 2025.
Home Energy Assessment Highlights - Energy and demand savings remained very strong in 2024, as Canada Greener Homes Grant (which E1 co-delivers with Natural Resources Canada and provides a top up to DSM incentives, through the Home Energy...
AI summary Energy and demand savings remained strong in 2024 despite the Canada Greener Homes Grant closing in February. Savings were impacted by a billing analysis adjusting HOT2000 modelling software overestimation ratios. Post-grant closure, demand for Home Energy Assessments declined, though a marketing campaign was launched in H2 2024.
Mi'kmaw Home Energy Efficiency Project Highlights • Participation in the Mi'kmaw Home Energy Efficiency Project was higher in 2024 than any previous year in the project's history, but the program component did not meet its mid-course adjus...
AI summary Participation in the Mi'kmaw Home Energy Efficiency Project increased in 2024, but energy and demand savings targets were unmet due to a billing analysis updating the HOT2000 software overestimation ratio. Outreach included distributing a bilingual 2023 Impact Report and program materials to 13 First Nations communities.
1 5.3 Business, Non-Profit and Institutional (BNI) Sector Results - 2 The BNI sector is comprised of the following programs: - 3 Efficient Product Rebates; - 4 Custom Incentives; and - 5 Direct Installation. 6 10 7 In 2024, the BNI sector...
AI summary The BNI sector achieved 94.8 GWh energy savings and 13.7 MW peak demand savings in 2024, exceeding mid-course adjusted targets. E1's Energy Manager initiative supported large organizations, with 33 energy manager positions, six partially funded by DSM. Variance explanations were provided for Custom Incentives programs deviating by +/-25% from targets.
9 5.3.1 Efficient Product Rebates 10 The 2024 Efficient Product Rebates program is marketed as Business Energy Rebates. 11
AI summary The 2024 Efficient Product Rebates program is marketed as Business Energy Rebates in Nova Scotia's regulatory proceeding. The program falls under Efficiency Nova Scotia's initiatives, overseen by the NSUARB.
12 Table 8: 2024 BNI Efficient Product Rebates BNI EFFICIENT PRODUCT REBATES (2024) BNI Efficient Product Rebates Energy Savings (GWh) Demand Savings (MW) Expenditure ($ million) 2024 Results 39.5 5.7 8.6 2024 MCA Target 39.7 5.1 9.7 • BNI...
AI summary Table 8 compares 2024 BNI Efficient Product Rebates results against MCA targets, showing the program met its demand savings target (5.7 MW vs. 5.1 MW target) but fell slightly short on energy savings (39.5 GWh vs. 39.7 GWh target). Expenditure was $8.6 million, under the $9.7 million target.
Business Energy Rebates Highlights - Business Energy Rebates, including both the Instant Rebates and Application Rebates services, fell slightly short of its 2024 mid-course adjusted energy savings target and achieved its mid-course adjust...
AI summary Business Energy Rebates under Efficiency Nova Scotia (ENS) missed 2024 mid-course adjusted energy savings targets but met demand targets. Instant Rebates saw lower 2024 participation due to reduced LED lamp sales, though rebate increases in Q2 and promotional campaigns were implemented. 2024 savings aligned with 2023 results.
6 Table 9: 2024 Custom Incentives CUSTOM INCENTIVES (2024) Custom Incentives Energy Savings (GWh) Demand Savings (MW) Expenditure ($ million) 2024 Results 44.4 5.8 9.2 2024 MCA Target 31.3 4.6 8.6 • Custom Incentives exceeded its mid-cours...
AI summary Custom Incentives exceeded 2024 mid-course adjusted energy and demand savings targets, driven by Retrofit and New Construction services. Compressed air leak audits in Retrofit contributed significantly to savings.
Program Components / Offerings - The Custom program component provides large business, non-profit and institutional participants with technical assistance and financial incentives to help reduce electricity consumption and demand and inclu...
AI summary The Custom program component offers technical assistance and financial incentives to large BNI participants through services like Retrofit and Pay-for-Performance. Strategic Energy Management focuses on operational changes to reduce energy use, with E1 merging Energy Management Information Systems into this program as per the 2023-2025 DSM Plan. The goal is to enhance long-term energy performance through business practice changes.
Custom Highlights - Custom exceeded its 2024 mid-course adjusted energy and demand savings targets, as the Retrofit, New Construction, and Building Optimization services all achieved higher savings in 2024 than 2023. Several partial saving...
AI summary Custom exceeded its 2024 energy and demand savings targets through higher savings from Retrofit, New Construction, and Building Optimization services, and partial savings claims. Despite lower Retrofit participation, average savings per project increased. E1 focused on compressed air opportunities in Retrofit.
5 Table 10: 2024 Direct Installation DIRECT INSTALLATION (2024) Direct Installation Energy Savings (GWh) Demand Savings (MW) Expenditure ($ million) 2024 Results 10.9 2.2 7.3 2024 MCA Target 10.6 2.6 6.5 • Direct Installation met its mid-c...
AI summary Table 10 shows Direct Installation met its 2024 mid-course adjusted energy savings target (10.9 GWh vs. 10.6 GWh) but fell short of demand savings (2.2 MW vs. 2.6 MW). Increased unitary incentives in Q2 drove higher-than-target expenditure ($7.3M vs. $6.5M).
Program Component • The Direct Installation program is comprised of the Small Business Energy Solutions program component. Small Business Energy Solutions offers small businesses incentives and resources to encourage them to make energy ef...
AI summary The Direct Installation program includes the Small Business Energy Solutions initiative, offering incentives and resources for small businesses to implement energy-efficient upgrades. Participants can opt for a no-charge audit or a DIY approach, with contractors from the Efficiency Preferred Partner Network or self-selected contractors completing installations.
Small Business Energy Solution Highlights • Changes made to Small Business Energy Solutions in Q2 – increasing the eligibility cap for businesses from 350,00 kWh of electrical energy consumption annually to 600,000 kWh, extending the preap...
AI summary Small Business Energy Solutions in Nova Scotia saw increased applications and energy savings after Q2 2023 changes, including higher eligibility caps and extended preapproval windows. However, demand savings targets were slightly missed. E1's Large Industrial initiative offers incentives for full-time Industrial Energy Managers at large industrial sites, launched in 2021 under the Custom Incentives program.
1 Table 11: 2024 Demand Response DEMAND RESPONSE (2024) Demand Response Available Demand Response Capacity (MW) Expenditure ($ million) 2024 Results 8.1 3.3 2024 MCA Target 7.2 3.8 • Results reflect available capacity achieved during the p...
AI summary Table 11 shows 2024 Demand Response results, with E1 achieving 8.1 MW available capacity (exceeding its 7.2 MW mid-course target) and spending $3.3 million (below the $3.8 million target). The operational period was December 1, 2023, to February 29, 2024.
5.5.2 Performance Indicator The NSUARB also established a Performance Indicator of incidental cumulative annual energy savings of 23.6 GWh applicable to low-income and underserved communities from non-targeted programs. [24](#page-42-1) In...
AI summary The NSUARB set a performance indicator for 23.6 GWh annual energy savings from non-targeted programs targeting low-income and underserved communities. E1 updated its methodology in 2023 and met its 2024 mid-course target, achieving 26.4 GWh (112% of the three-year goal). Results reflect revised low-income estimation assumptions, with 2024 non-targeted program savings at 16.1 GWh.
1 Table 13: 2023 Results Applicable to Low-Income and Underserved Communities, Non-Targeted Programs 2024 Plan Performance Indicators 2024 Mid-Course Adjustments 2024 Forecast (Year-End) 2024 Results First-Year Energy Savings (GWh) Lifetim...
AI summary Table 13 presents 2023 results for low-income and underserved communities under non-targeted programs, including energy savings, participation numbers, and investment figures. It outlines performance indicators for 2024, mid-course adjustments, forecasts, and actual results, with data on efficient product rebates and appliance retirement initiatives.
10 Table 14: 2024 Enabling Strategies
AI summary Table 14 outlines 2024 Enabling Strategies, referencing acronyms like DSM, ENS, and NSUARB. It likely details initiatives for energy efficiency and regulatory compliance in Nova Scotia, involving organizations such as Efficiency Nova Scotia and EfficiencyOne.
ENABLING STRATEGIES 2024 ACTIVITY HIGHLIGHTS
AI summary This section from a Nova Scotia regulatory proceeding highlights Enabling Strategies 2024 activities, focusing on energy efficiency programs and collaborations involving Efficiency Nova Scotia, EfficiencyOne, and the Mi'kmaw Home Energy Efficiency Project, under the oversight of the Nova Scotia Utility and Review Board.
Education and Outreach Education and Outreach activities in 2024 included the following activities: - E1 participated in five home shows; as well as the Build Green Atlantic conference, which had record attendance and featured several E1 s...
AI summary E1 conducted outreach through home shows, conferences, and summer events across all 18 Nova Scotia counties. Green Schools engaged 30,375 students, with focused efforts in communities with high African Nova Scotian and Mi'kmaw populations. Ecology Action Centre developed training and educational videos on energy efficiency featuring Mi'kmaw and African Nova Scotian voices.
Innovation - The deep retrofit navigator pilot continued with five of the six participants completing their upgrades in 2024. - The heat pump water heater market transformation pilot launched in 2024. Activities included updating the Effic...
AI summary The deep retrofit navigator pilot saw five of six participants complete upgrades in 2024. The heat pump water heater market transformation pilot launched in 2024, involving updates to the Efficiency Preferred Partner network, plumber recruitment, marketing material development, and installer training in Sydney, Kentville, and Dartmouth.
2 5.7 Additional 2024 Performance Indicators - 3 The NSUARB approved additional Performance Indicators as identified in the Supply - Agreement.26 4 In 2024, results of E1's additional Performance Indicators are as follows: - 5 Total lifeti...
AI summary The NSUARB approved additional performance indicators in the Supply Agreement. In 2024, E1 achieved a Customer Satisfaction Index of 89.9 and total lifetime ratepayer benefits of $243 million from energy and demand savings. Awareness of Efficiency Nova Scotia was approximately 85 percent, consistent with 2023 results.
14 Residential Sector Programs
AI summary The section outlines residential sector programs under Nova Scotia's regulatory proceeding, referencing key acronyms like DSM, E1, ENS, and NSUARB. It highlights initiatives such as the Mi'kmaw Home Energy Efficiency Project (MHEEP) and mentions regulatory oversight by the NSUARB.
15 Efficient Product Rebates - 16 Instant Savings - 17 To increase participation in the fall campaign resulting in additional savings from the lighting - 18 category, E1 increased rebates for several measures in Q3 2024, which had an impac...
AI summary EfficiencyOne (E1) increased rebates in Q3 2024 to boost participation in a fall campaign, impacting Q4 2024 average incentives. Post-campaign, incentive levels reverted to pre-campaign thresholds, including specific per-unit amounts for LED fixtures and recessed downlights. A NSUARB decision (M10473) is referenced in footnotes.
6. CONCLUSION - In 2024, E1 achieved 172.8 GWh of incremental annual net energy savings (121% of the mid- - course adjusted target of 142.6 GWh), 30.7 MW of annual net peak demand savings (119% of the - mid-course adjusted target of 25.7 M...
AI summary E1 exceeded 2024 DSM targets for energy and demand savings but expects to miss the available capacity target. They plan to spend $173 million under their 2023-2025 plan and will file a quarterly report in May 2025.
ATTACHMENT 1: 2024 RATE CLASS RESULTS
AI summary Attachment 1 presents the 2024 rate class results from a Nova Scotia regulatory proceeding, involving entities such as Efficiency Nova Scotia (ENS), EfficiencyOne (E1), and the Nova Scotia Utility and Review Board (NSUARB). Key programs include the Mi'kmaw Home Energy Efficiency Project (MHEEP) and Demand Side Management (DSM).
12 2024 Rate Class Results by Program - 13 [Table](#page-55-0)s 3 7 provide a breakdown of 2024 net incremental energy and net peak demand savings, - 14 expenditures, and participation achieved by rate class within the energy efficiency pr...
AI summary The document presents tables (3 and 7) detailing 2024 net incremental energy and peak demand savings, expenditures, and participation rates by rate class under energy efficiency programs. The data reflects outcomes across different customer segments within Nova Scotia's regulatory framework.
1 Table 3: 2024 Residential Efficient Product Rebates Rate Class Results Residential Efficient Product Rebates (2024) First-Year Energy Savings (GWh) Lifetime Energy Savings (GWh) Peak Demand Savings (MW) Expenditures ($ million) Units Reb...
AI summary Table 3 presents the 2024 Residential Efficient Product Rebates rate class results, including energy and demand savings, expenditures, and the number of rebated units across various residential and industrial categories. The data highlights the impact of the rebate program on energy efficiency and cost.
9 Table 4: 2024 Existing Residential Rate Class Results Existing Residential (2024) First-Year Energy Savings (GWh) Lifetime Energy Savings (GWh) Peak Demand Savings (MW) Expenditures ($ million) Housing Units / Products (#) Residential/Ch...
AI summary Table 4 presents 2024 residential rate class results, showing energy and demand savings across various categories, along with expenditures and the number of housing units or products. Savings are calculated net of free-ridership and spillover, and expenditures are unaudited.
13 Existing Residential includes the following program components: Affordable Multi-family Housing and Non-Profit Organizations, Efficient Product 14 Installation, Green Heat, Home Energy Assessment, Affordable Single-family Homes, Mi'kmaw...
AI summary The Existing Residential program includes several components such as Affordable Multi-family Housing, Efficient Product Installation, Green Heat, and the Mi'kmaw Home Energy Efficiency Project. The Home Energy Assessment component primarily targets homes heated by electricity, with some non-electric homes also participating. The Appliance Retirement program collects eligible appliances from BNI customers and residential participants.
1 Table 7: 2024 Direct Installation Rate Class Results Direct Installation (2024) First-Year Energy Savings (GWh) Lifetime Energy Savings (GWh) Peak Demand Savings (MW) Expenditures ($ million) Products (#) Residential/Charitable (2,3,4) 1...
AI summary Table 7 outlines the 2024 Direct Installation Rate Class Results, showing energy and demand savings across various rate classes, along with expenditures and the number of products installed. Notably, some rate classes show no savings or expenditures, and the data includes footnotes about rounding and unaudited figures.
onducting a billing analysis when a large enough participant sample becomes available. 2018 HEA - R1 Complete E1 agrees with this recommendation. The Evaluator and E1 explored the factors potentially responsible for the inconclusive result...
AI summary EfficiencyOne (E1) agrees with the 2018 HEA - R1 recommendation to conduct a billing analysis with a large enough participant sample. E1 and the Evaluator developed an evaluation approach completed in 2024, with results to be presented in the Existing Residential Evaluation Report filed with the Nova Scotia Utility and Review Board on March 31, 2025.
EfficiencyOne
AI summary The document text consists solely of the heading 'EfficiencyOne' from a Nova Scotia regulatory proceeding, with no further content or context provided in the chunk.
DEFINITIONS Accuracy Reflects the proximity of measurements to the true value. The number of years by which the first-year savings estimate is multiplied to obtain lifetime energy savings. This value takes into account variations in annual...
AI summary The document defines key terms related to energy efficiency evaluations, including accuracy, effective useful life, evaluated savings, and the evaluation plan. These definitions are essential for understanding how energy savings are measured and reported in programs.
EfficiencyOne (E1), an independent, non-profit organization, is responsible for helping Nova Scotians improve the energy efficiency of their homes and workplaces by designing, marketing, and delivering demand-side management (DSM) for Nova...
AI summary EfficiencyOne (E1) is an independent non-profit that delivers energy efficiency and demand response programs in Nova Scotia through the Efficiency Nova Scotia franchise. An evaluation of E1's 2024 DSM program portfolio confirmed significant energy and GHG savings, with 172.760 GWh in net electrical energy savings and 81,577 tonnes of CO2 eq in avoided GHG emissions.
Demand-side Management Measure Assessment Document The impact evaluation scope for 2024 also included an update of the Demand-side Management Measure Assessment (DSM MA) document. This update covered all prescriptive measures and their par...
AI summary The 2024 update of the Demand-side Management Measure Assessment (DSM MA) includes prescriptive and semi-prescriptive measures, reviews of parameters like unitary energy savings and peak demand-to-energy ratios, and annual updates for LED lighting and appliance retirements, using new data sources and methodologies.
2.1.2 Data-collection Tool Development and Sampling Strategy Data-collection tool development and sampling were carried out for Instant Savings, Affordable Multifamily Housing (AMH), Affordable Single-family Homes (ASFH)[,](#page-15-4) 9 E...
AI summary The section outlines the development of data-collection tools for programs like Instant Savings, AMH, ASFH, EPI, and BER. Instruments included surveys, interviews, and protocols informed by documentation reviews and staff interviews, with an integrated approach to process and market evaluation.
Table 3: 2024 Interviews Completed Program Component Program Manager/1 E1 Staff/Business Development Manager Service Providers/ Distributors/ Contractors Participants Non participants Dropped-out or Overdue Participants Residential Applian...
AI summary Table 3 presents the number of interviews conducted in 2024 across various program components, including residential and business energy programs. It includes data on participants, non-participants, and dropped-out or overdue participants, with the exception of Appliance Retirement, which had only one round of interviews.
Site Visits and Project Reviews with Follow-up Site Visits or Interviews The Evaluator performed a total of 146 project reviews during the summer and fall of 2024, 70 of which were complemented through site visits and 14 were complemented...
AI summary The Evaluator conducted 146 project reviews in 2024, including site visits and phone interviews, to validate installations and gather information on free-ridership and spillover effects for various programs such as Efficient Product Installation, Affordable Multifamily Housing, and Strategic Energy Management.
Table 4: 2024 Site Visits and Project Reviews with Follow-up Site Visits or Interviews Program Component Project Reviews Followed by Site Visits Project Reviews Followed by Phone Interviews Project Reviews Without Site Visits or Phone Inte...
AI summary Table 4 outlines the 2024 project reviews and site visits conducted under various programs, including Affordable Multifamily Housing, Efficient Product Installation, and BNI. It details the distribution of project reviews followed by site visits, phone interviews, or neither, with a note on the exclusion of a large-scale compressed air leak audit from adjustment ratio calculations.
Unitary Savings Review As part of the update to the 2024-2025 DSM MA that was reviewed in its entirety in 2024, for program components with unitary savings values - namely Appliance Retirement, Instant Savings, Home Energy Assessment, Gree...
AI summary The 2024-2025 DSM MA update reviewed unitary savings values for programs like Appliance Retirement, Home Energy Assessments, and Business Energy Rebates. Parameters were validated and updated, with new measures added, including advanced thermostats and solar PV systems. Review methods included literature reviews, metering studies, and energy models.
Billing Analyses In 2024, three billing analyses were performed for Green Heat, Home Energy Assessment, and Residential Behaviour. The Green Heat billing analysis was conducted to obtain measured electrical energy savings generated through...
AI summary In 2024, three billing analyses were conducted for Green Heat, Home Energy Assessment, and Residential Behaviour. The analyses aimed to measure energy savings from MSHP installations, establish adjustment ratios for HOT2000 estimates, and calculate net savings using a difference-in-difference approach. Participants who modified their homes during participation were excluded to ensure accurate savings calculations.
2.1.4 Effective Useful Life Review As part of the DSM MA update in 2024, the Evaluator reviewed the EUL values for existing and new measures to ensure they were valid and revised them where appropriate. The EUL update was based on a litera...
AI summary The 2024 DSM MA update reviewed and revised EUL values for energy measures using technical references from other jurisdictions. Adjusted EUL calculations considered baseline evolution and lifetime savings, applied to programs like Affordable Single-family Homes and Mi'kmaw Home Energy Efficiency Project, with updated metrics for multifamily housing heat pumps.
2.2 Process and Market Evaluations Process and market evaluations were conducted using a range of activities such as program component documentation as well as secondary data reviews, jurisdictional scans, logic model reviews, as well as p...
AI summary Process and market evaluations were conducted through documentation, data reviews, surveys, and interviews, focusing on Efficient Product Installation, Business Energy Rebates – Instant Rebates, Affordable Multifamily Housing, Affordable Single-family Homes, and Custom New Construction programs.
3 Impact Evaluation Results This section presents an analysis of the impact evaluation results for all program components by comparing 2024 tracked electrical energy and peak demand savings with evaluated electrical energy and peak demand...
AI summary This section compares 2024 tracked electrical energy and peak demand savings with evaluated savings, presenting NTGRs, lifetime energy savings, and GHG emission reductions as key evaluation outcomes.
3.1 Individual Impact Evaluation Results [Table](#page-24-0) 5 and [Table](#page-25-0) 6 below respectively list the evaluated electrical energy and peak demand savings as well as the corresponding savings tracked by E1 for each program co...
AI summary The text discusses the evaluation of electrical energy and peak demand savings for various programs offered in 2024. Net savings are calculated using the net-to-gross ratio (NTGR), and lifetime energy savings are based on the effective useful life (EUL) of efficiency measures. Line loss factors were submitted to the Nova Scotia Utility and Review Board (NSUARB) as part of the 2014 Cost of Service Study Progress Update.
Table 5: Comparison of 2024 Evaluated and Tracked Energy Savings at the Generator a Tracked Results Evaluated Results Program Component Annual Gross Savings (GWh) Annual Net Savings (GWh) Annual Gross Savings (GWh) NTGR b Annual Net Saving...
AI summary Table 5 compares the 2024 evaluated and tracked energy savings for various programs in Nova Scotia. It highlights discrepancies between gross and net savings, as well as differences in net savings and net realization rates for each program component, including Appliance Retirement, Instant Savings, Affordable Multifamily Housing, and others.
Table 6: Comparison of 2024 Evaluated and Tracked Peak Demand Savings at the Generator a Program Component Tracked Results Evaluated Results Difference DSM Program Annual Gross Savings (MW) Annual Net Savings (MW) Available Capacity (MW) A...
AI summary Table 6 compares the evaluated and tracked peak demand savings at the generator for various programs in 2024. It shows results for residential, BNI, and demand response programs, highlighting differences in net savings and available capacity, along with net realization rates for each component.
3.1.1 Residential DSM Programs
AI summary The section outlines residential demand-side management (DSM) programs aimed at enhancing energy efficiency in residential sectors through initiatives like appliance retirement, home energy assessments, and incentives for efficient technologies such as heat pumps and LED lighting.
Instant Savings - › Participation levels in 2024 increased by 82% compared to 2023 levels, likely driven by E1's Lights Out campaign, with ENERGY STAR® certified LED fixtures and ENERGY STAR certified non-A-type LED lamps being the largest...
AI summary Participation in Instant Savings programs rose 82% in 2024, driven by E1's Lights Out campaign and LED product adoption. Savings from non-lighting products increased, with LED lighting remaining the primary contributor. Free-ridership for LED products decreased, and evaluated savings exceeded E1's tracked results.
Existing Residential In 2024, the net electrical energy savings for Existing Residential reached 53.331 GWh at the generator, while the net peak demand savings amounted to 14.229 MW at the generator. Existing Residential is comprised of Af...
AI summary In 2024, Existing Residential programs achieved 53.331 GWh of net electrical energy savings and 14.229 MW of peak demand savings. The category includes Affordable Multifamily Housing, Affordable Single-family Homes, Efficient Product Installation, Green Heat, Home Energy Assessment, the Mi'kmaw Home Energy Efficiency Project, and Residential Behaviour. Program component results are detailed below.
Affordable Multifamily Housing - › Despite a slight increase (5%) in participation compared to 2023 levels, AMH achieved lower gross electrical energy and peak demand savings than in 2023. - › In 2024, prescriptive projects generated the m...
AI summary AMH participation rose 5% in 2024 but achieved lower energy and peak demand savings than 2023. Prescriptive projects dominated savings (80% energy, 88% peak demand). Evaluator adjusted savings upward for electrical energy (1.016 ratio) but downward for peak demand (0.003-0.006 MW reductions). Net savings aligned closely with E1 tracking despite adjustments.
Efficient Product Installation - › Compared to 2023 levels, participation in 2024 increased by 2% while average electrical energy savings per participant decreased by 6.3%. This reduction in savings per participant was mainly due to the up...
AI summary Efficient Product Installation (EPI) participation rose 2% in 2024 compared to 2023, but average electrical energy savings per participant fell 6.3% due to 2024-2025 DSM MA updates, particularly reduced smart thermostat and LED lamp savings. Evaluated net electrical energy savings were 6% lower than tracked, while peak demand savings increased 1% due to DSM MA updates and NTGR adjustments.
Home Energy Assessment - › With 5,367 projects, the 2024 participation level was the highest observed since the program component was launched. The average gross electrical energy savings per home slightly decreased compared to 2023 levels...
AI summary The 2024 Home Energy Assessment program achieved record participation with 5,367 projects, driven by the Canada Greener Homes Grant. Energy savings slightly decreased from 2023 but remained high. Updated adjustment ratios from a 2024 billing analysis revealed higher savings than E1's tracked results due to DSM MA updates.
Mi'kmaw Home Energy Efficiency Project - › While MHEEP achieved the highest participation since its inception with an increase of 19%, the average energy savings per participant decreased by 41%, generating 31% lower gross energy savings a...
AI summary The Mi'kmaw Home Energy Efficiency Project (MHEEP) saw a 19% increase in participation but a 41% drop in average energy savings per participant in 2024. Evaluated net electrical energy savings were lower than initial estimates, while peak demand savings were higher, impacting gross energy and peak demand outcomes.
Efficient Product Rebates Efficient Product Rebates is comprised of one program component, Business Energy Rebates, which is further comprised of two services, namely Application Rebates and Instant Rebates. In 2024, Business Energy Rebate...
AI summary Efficient Product Rebates includes Business Energy Rebates, which achieved 39.529 GWh in net electrical energy savings and 5.746 MW in net peak demand savings in 2024 through Application and Instant Rebates services.
Table 8: 2024 Evaluated Net Lifetime Electrical Energy Savings at the Generator DSM Program Program Component Annual Net Energy Savings (GWh) Lifetime Net Energy Savings (GWh) Weighted Average EUL (years) Share of Annual Net Energy Savings...
AI summary Table 8 outlines the 2024 evaluated net lifetime electrical energy savings by DSM program and component, highlighting the significant contributions from residential and BNI programs. The Home Energy Assessment program contributes the highest share of both annual and lifetime savings, while the Demand Response program is excluded due to no electrical energy savings.
Table 9: 2024 Evaluated GHG Emission Reductions DSM Program Program Component Gross Annual Avoided GHG Emissions in CO2 eq Tonnes Net Annual Avoided GHG Emissions in CO2 eq Tonnes Residential Efficient Appliance Retirement 1,981 1,117 Prod...
AI summary Table 9 presents evaluated greenhouse gas (GHG) emission reductions for 2024 under various demand-side management (DSM) programs in Nova Scotia. The table includes both gross and net annual avoided emissions in CO2 equivalent tonnes for different program components, such as appliance retirement, product rebates, and energy assessments.
4.1 Participant and Partner Satisfaction The 2024 evaluation revealed high participant satisfaction with E1 and its programs. Affordable Multifamily Housing, Affordable Single-family Homes, Efficient Product Installation, Custom (New Const...
AI summary The 2024 evaluation showed high participant satisfaction with E1 and its programs, with scores of 7.9 or higher for several initiatives. Program partners were generally satisfied but less so than participants. A table presents the average satisfaction scores for program components on a 0-to-10 scale.
Table 13: Evaluated Net Peak Demand Savings at the Generator, 2020-2024 Peak Demand Savings (MW) Peak Demand Savings (%) DSM Program a Program Component 2020 2021 2022 2023 2024 2020 2021 2022 2023 2024 Residential Residential Efficient Ap...
AI summary Table 13 presents evaluated net peak demand savings from various Demand Side Management (DSM) programs in Nova Scotia from 2020 to 2024. It details savings by program type, including residential and BNI programs, and provides both megawatt (MW) and percentage savings for each year.
Table 14: Evaluated Net Available DR Capacity, 2023-2024 DSM Program Program Component Available DR Capacity (MW) Available DR Capacity (%) 2023 2024 2023 2024 Demand Response (DR) Demand Response Residential Demand Response 0.058 0.057 2%...
AI summary Table 14 shows the evaluated net available demand response (DR) capacity for 2023 and 2024, with significant contributions from BNI Demand Response. In 2024, E1 achieved notable increases in net electrical energy and peak demand savings compared to 2023, driven by both residential and BNI programs.
› Some participants would benefit from project management support. Based on comments from E1, Energy Auditors (EAs) and participants, project management assistance, technical/maintenance support, and help finding contractors would be usefu...
AI summary Participants require project management support, technical assistance, and contractor access to avoid delays and program withdrawal. Additional information on upgrades like heat pumps and insulation, along with case studies, is requested to improve program engagement and understanding.
› More product information would be helpful for participants. Some participants say they did not receive information about the products installed and some still have doubts about how to operate and maintain their new equipment (especially...
AI summary Participants report insufficient information about installed products, particularly heat pumps, leading to operational and maintenance doubts. Contractors and DAs address many questions, but the lack of clarity may hinder proper use and energy savings.
National Energy Code of Canada for Buildings [NECB] 2020 Part 9 buildings); such an approach could be considered by E1 if the program wishes to capture a higher proportion of projects outside the HRM. › Participants are satisfied with the...
AI summary Participants report high satisfaction with E1's responsiveness but moderate satisfaction with program value due to costs and ROI uncertainty. Decarbonization motivates participation, yet financial barriers (higher costs, modelling expenses) and low modeller engagement hinder adoption. Insufficient modelling cost coverage is a key concern.
Business Energy Rebates – Instant Rebates: BNI Lighting To analyze the evolution of the BNI lighting market, the Evaluator completed a market characterization study to assess the state of the lighting market and review whether updates to a...
AI summary The market for BNI lighting under BER-IR has shifted almost entirely to LED technology, with distributors reporting 100% LED stock for most fixtures. This validates the use of a 'replace-on-burnout' baseline and suggests imminent updates to program baselines. Non-LED options remain limited, and retrofit opportunities persist in sectors with capital constraints.
Table 15: 2024 Recommendations on Residential Program Components No. Recommendation ASFH – R5 Ensure that DAs/contractors provide a leave-behind so that participants know who to contact in case of questions or difficulties or to better und...
AI summary The table outlines 2024 recommendations for residential program components, focusing on improving communication, administrative efficiency, and product satisfaction. Key recommendations include providing leave-behind materials, streamlining record-keeping, updating training guides, improving smart thermostat retention, and removing low-impact products from offers.
h-energy-systems/6833)[pump/ground-source-heat-pumps-earth-energy-systems/6833](https://www.nrcan.gc.ca/energy-efficiency/energy-star-canada/about-energy-star-canada/energy-star-announcements/publications/heating-cooling-heat-pump/ground-s...
AI summary The text lists bibliographic references and citations to studies, technical manuals, and research papers related to energy efficiency programs, effective useful life of appliances, and lighting technologies, including contributions from organizations like Nova Scotia Power, Hydro-Québec, NREL, and DNV.
Program Components Bibliographic References http://interchange.puc.state.tx.us/WebApp/Interchange/Documents/40891_20_8 71637.PDF. Accessed: Feb 18, 2016. Minnesota Commerce Department, State of Minnesota Technical Reference Manual for Ener...
AI summary The text lists bibliographic references for energy efficiency programs, technical manuals, and evaluations from various states and organizations, including Minnesota, Iowa, Massachusetts, and Pennsylvania, as well as studies on refrigeration equipment and rebate programs.
Program Components Bibliographic References Roberts J. and Tso B. (SBW Consulting), Do Savings from Retrocommissioning Last? Results from an Effective Useful Life Study, ACEEE Summer Study on Energy Efficiency in Buildings, 2010 Illinois C...
AI summary The document lists bibliographic references and cross-references related to various energy efficiency programs and studies, including retrocommissioning, technical reference manuals, and appliance retirement initiatives. It also cites regulatory matters and reports from Nova Scotia Power and Emera Inc.
Survey Margins of Error The 2024 Green Heat past participant survey margins of error were established by using the following formula that correspond to the margin of error calculation for a proportion (i.e. a value between 0% and 100%). Ma...
AI summary This section explains the calculation of the margin of error for the 2024 Green Heat past participant survey. The formula uses a proportion-based approach, with parameters including the confidence level, sample size, and population size. A sample size of 204 participants was used, and a 90% confidence level corresponds to a Zα coefficient of 1.645.
Calculation of the Weighted Average of Adjustment Ratios In 2024, different types of projects were reviewed for Custom Retrofit; the example herein is for regular retrofit projects. For these projects, the Evaluator used a stratified sampl...
AI summary The document details the calculation of a weighted average adjustment ratio (AR) for retrofit projects in 2024. Using a stratified sample of 18 projects, the Evaluator applied a formula involving stratum weights and energy savings, resulting in a weighted average AR of 1.021. This ratio reflects adjustments to energy savings estimates across different project strata.
Calculation of the Margin of Error The margin of error on the adjustment ratio of the EPI LED lighting free-ridership level was established by using the following formula that is the general equation linking the standard error to the margi...
AI summary The margin of error for EPI LED lighting free-ridership was calculated using a formula involving standard error (0.0193), a t-value (1.667 for 90% confidence), and a sample size (n=70 from N=5,342 participants). The result was 3.2%, applied to EPI, Instant Savings, BER Instant Rebates, Custom programs, EPI installation rates, and AMH adjustment ratios in 2024.
NTGR Calculations Free-ridership algorithm High Free-ridership Participant Medium Free-ridership Participant purchase and install LED bulbs in your home? 2) No 0% Yes 100% Yes 100% Yes 100%
AI summary The text presents a table related to the NTGR (Net-to-Gross Ratio) calculations, focusing on free-ridership levels for participants in a program that involves purchasing and installing LED bulbs. It categorizes participants into high, medium, and no free-ridership levels with corresponding percentages.
EfficiencyOne
AI summary The document introduces EfficiencyOne (E1), a program under Nova Scotia's energy efficiency initiatives, and lists related acronyms and terms. It outlines programs like Demand-Side Management (DSM), Affordable Multifamily Housing (AMH), and Business Energy Rebates (BER), highlighting their roles in energy conservation and affordability.
Evaluation Approach The 2024 evaluation was aimed at calculating program component gross and net results, namely electrical first-year and lifetime energy savings, peak demand savings, as well as avoided greenhouse gas (GHG) emissions. [Ta...
AI summary The 2024 evaluation aimed to calculate program component gross and net results, including electrical first-year and lifetime energy savings, peak demand savings, and avoided greenhouse gas emissions. Table 1 summarizes the types of evaluation conducted for each program component and the corresponding methodology.
Table 1: Summary of 2024 Residential Efficient Product Rebates Program Evaluation Program Evaluation Type Component Impact Process Market Methodology Appliance Retirement Condensed › Tracking sheet audit › Unitary savings review › Calculat...
AI summary The 2024 Residential Efficient Product Rebates Program Evaluation includes assessments of the Appliance Retirement and Instant Savings components. The evaluation uses methods such as tracking sheet audits, unitary savings reviews, and GHG emission reduction calculations. The Instant Savings component also includes participant surveys and market effects analysis.
[Table](#page-84-0) 2 below presents the participation levels, NTGRs, evaluated gross and net savings at the generator, annual GHG emission reductions, as well as EUL values for each program component and for Residential Efficient Product...
AI summary Table 2 outlines participation levels, NTGRs, evaluated gross and net savings at the generator, annual GHG emission reductions, and EUL values for each program component and for Residential Efficient Product Rebates as a whole in 2024.
Participa ation Level Gross Savings NTGR Net S avings Value Unit Value Unit Value Value Unit ARet Energy Savings 5,941 Appliances 4.195 GWh 0.56 2.365 GWh Lifetime Energy Savings 16.729 GWh 0.56 9.433 GWh Peak Demand Savings 0.598 MW 0.56...
AI summary The Residential Efficient Product Rebates program exceeded its 2024 energy savings and peak demand savings targets by 70% and 41%, respectively, with Instant Savings being the primary contributor. The program achieved significant reductions in GHG emissions and energy consumption.
ARet Findings and Recommendations This subsection presents the key findings from the 2024 ARet evaluation. The Evaluator has no specific recommendation for ARet. 2024 ARet-Finding: ARet achieved both its net electrical energy savings and p...
AI summary The 2024 ARet program met its energy and peak demand savings targets by 22% and 18%, respectively, with a 39% increase in participation driven mainly by refrigerator and freezer retirements. Savings tracked by the Evaluator were slightly lower than those by E1.
Instant Savings Findings and Recommendations This subsection presents the key findings from 2024 Instant Savings evaluation. The Evaluator has no specific recommendation for Instant Savings. 2024 Instant Savings-Finding: Instant Savings su...
AI summary 2024 Instant Savings exceeded energy savings (77%) and peak demand savings (45%) targets. Participation rose 82% due to E1's campaign, with LED lighting driving most savings. Non-lighting savings increased, free-ridership dropped, and evaluator-estimated savings outpaced E1's tracked results.
Table 3: Comparison of 2024 Tracked and Evaluated Savings at the Generator Gross Savings Net Savings Realization Unit NTGR Value Unit Rate Energy Savings Tracked Savings by E1 4.212 GWh 0.56 2.374 GWh 100% Evaluation Results 4.195 GWh 0.56...
AI summary Table 3 compares tracked and evaluated energy and peak demand savings for 2024, showing data from EfficiencyOne (E1) and evaluation results. Gross and net savings are presented in gigawatt-hours (GWh) and megawatts (MW), with realization rates and NTGR values provided for each category.
INTRODUCTION EfficiencyOne (E1), an independent, non-profit organization, is responsible for helping Nova Scotians improve the energy efficiency of their homes and workplaces by designing, marketing, and delivering demand-side management (...
AI summary EfficiencyOne (E1), a non-profit organization, manages demand-side management (DSM) programs in Nova Scotia through the Efficiency Nova Scotia (ENS) franchise. E1's 2024 DSM program portfolio includes the Residential Efficient Product Rebates program with components like Appliance Retirement and Instant Savings. Econoler was commissioned to evaluate these programs, focusing on baseline definitions, savings calculations, and net-to-gross ratios.
Table 4: Types of Evaluation Conducted for Each Program Component, 2024 2024 Program Program Component Process Market Impact Residential Efficient Product Rebates ARet Condensed Instant Savings Comprehensive For each program, the Evaluator...
AI summary Table 4 outlines the types of evaluation conducted for each program component in 2024, specifically for the Residential Efficient Product Rebates program. The Evaluator prepared a DSM evaluation report detailing findings, energy savings, peak demand savings, and GHG emissions avoidance.
1.3 Participation History Since 2012, ARet has retired or replaced a total of 77,696 old and inefficient appliances from homes and schools. These were recycled so that they could not be refurbished, sold second hand, or left plugged in. In...
AI summary Since 2012, ARet has retired over 77,696 appliances, with 5,941 retired in 2024, a 39% increase from 2023. Energy and peak demand savings rose by 39% in 2024. Incentives for refrigerators and freezers were increased in 2021 to boost participation.
Table 5: 2024 ARet Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate gross results › Are the data in the tracking sheet complete, accurate, and consistent? › What are the evaluated first-year and lifetime g...
AI summary Table 5 outlines the 2024 ARet Evaluation Approach, focusing on calculating gross and net results through methods like tracking sheet audits and unitary savings reviews. It addresses research questions on data accuracy, energy savings, and greenhouse gas emission reductions.
Unitary Savings Review As part of a major update to the 2024-2025 Demand-side Management Measure Assessment (DSM MA)[,](#page-90-2) 4 a unitary savings review was conducted for all measures. The unitary savings review entailed a literature...
AI summary A unitary savings review was conducted for the 2024-2025 Demand-side Management Measure Assessment (DSM MA), involving a literature review of technical manuals, metering studies, and program evaluations to refine methodologies for calculating energy and peak demand savings. The review specifically examined refrigerators and freezers, considering changes in manufacturing year-classes and unit sizes.
3.2 Gross Savings For ARet, gross savings correspond to the change in energy consumption resulting from the retirement of energy inefficient appliances in participants' homes regardless of both why they participated and what they would hav...
AI summary Gross savings for ARet are calculated based on energy consumption changes from retiring inefficient appliances, regardless of participation motives. The 2024-2025 DSM MA update revised unitary savings values for freezers, refrigerators, and air conditioners using updated data, while dehumidifier values retained 2022 figures. Detailed calculations are outlined in the DSM MA document.
3.2.1 Unitary Energy Savings [Table](#page-92-4) 6 below presents the tracked and evaluated energy savings for each type of appliance retired through ARet for which a change in unitary savings was made in 2024 compared to 2023. For full-si...
AI summary The text discusses changes in unitary energy savings for retired appliances in 2024 compared to 2023, specifically for full-sized and small refrigerators and freezers, attributing the variations to differences in appliance age and size.
Table 6: 2024 ARet Tracked and Evaluated Unitary Energy Savings Appliance Tracked Unitary Energy Savings [kWh/year] Evaluated Unitary Energy Savings [kWh/year] Difference (%) ARet Refrigerators 654 660 1% Freezers 752 726 -3% Air Condition...
AI summary Table 6 presents 2024 ARet Tracked and Evaluated Unitary Energy Savings for various appliances, including refrigerators, freezers, air conditioners, and small refrigerators and freezers. The table compares tracked and evaluated energy savings and highlights the percentage difference between them.
3.2.2 Peak Demand Savings Peak demand savings correspond to the demand savings that coincide in time with the peak demand period of the electricity system. The projected electricity peak demand period in Nova Scotia is between 5 p.m. and 7...
AI summary Peak demand savings in Nova Scotia occur during 5-7 p.m. on non-holiday weekdays from December to February. Table 7 shows 2024 unitary peak demand savings for retired appliances via ARet, with variations due to updated energy savings values in the 2024-2025 DSM MA. Refrigerators and freezers show 1% and -4% changes respectively, while small appliances remained stable.
3.2.3 Interactive Effects Interactive effects occur when an implemented energy efficiency measure has an impact on the energy consumption of other elements such as heating and cooling equipment. For ARet, retiring old appliances causes an...
AI summary Interactive effects from retiring inefficient appliances (ARet) in Nova Scotia may increase winter heating loads and reduce summer cooling loads. However, factors like electricity use for heating, appliance placement, and air conditioning adoption mitigate these effects. The Evaluator concluded interactive effects are negligible, setting the factor at 0%.
3.2.4 Effective Useful Life Effective useful life (EUL) values are used in the calculations of electrical energy savings that are expected to persist over time. For ARet, the lifetime energy savings and equivalent EUL values are highly inf...
AI summary The document discusses the use of Effective Useful Life (EUL) values in calculating electrical energy savings for appliance retirement programs. It references the 2024-2025 DSM Measure Assessment and notes that the weighted average EUL value is 4.0 years.
Table 8: 2024 ARet Equivalent EUL and Gross Lifetime Unitary Savings Values Appliance Tracked Equivalent EUL [years] Evaluated Equivalent EUL [years] Evaluated Gross Lifetime Unitary Savings [kWh] ARet Refrigerators 4 No change 2,640 Freez...
AI summary Table 8 presents the 2024 ARet Equivalent EUL and Gross Lifetime Unitary Savings Values for various appliances, including refrigerators, freezers, air conditioners, and small refrigerators and freezers. The Equivalent EUL remains unchanged for most appliances, while the Gross Lifetime Unitary Savings are provided in kWh.
The gross energy and peak demand savings resulting from the retirement of appliances through ARet are listed in [Table](#page-95-0) 9 below. Line loss factors correspond to the values submitted to the Nova Scotia Utility and Review Board (...
AI summary The document discusses energy and peak demand savings from appliance retirements through ARet, using line loss factors submitted to the NSUARB in the 2014 Cost of Service Study Progress Update. It also references technical reference manuals from various U.S. states and mentions the application of interactive effect factors for freezers and refrigerators in some regions.
Table 13: Evaluated 2024 ARet Net Energy and Peak Demand Savings Appliance Retirement Measure Category Refrigerators Freezers Room Air Conditioners Small Refrigerators Small Freezers Total Energy Savings Gross Energy Savings – at the Meter...
AI summary Table 13 evaluates the 2024 Appliance Retirement (ARet) program's energy and peak demand savings. The program exceeded its energy and peak demand savings targets by 22% and 18% respectively, as outlined in Figure 6.
Table 14: Comparison of 2024 ARet Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Unit Value Energy Savings Tracked Savings by E1 4.212 GWh 0.56 2.374 GWh 100% Evaluatio...
AI summary Table 14 compares energy and peak demand savings tracked by E1 and evaluation results for 2024 ARet. It shows gross savings, net savings, and realization rates for both energy and peak demand, highlighting a slight difference between tracked and evaluated savings.
Table 15: List of 2024 Rebates by Product Products Offered During Campaigns Rebate During Spring Campaign Rebate During Fall Campaign ENERGY STAR® Certified LED Lights Non-A-series (single & multipacks) Up to 70% off package price Up to 80...
AI summary Table 15 outlines the 2024 rebate amounts for various energy-efficient products offered during spring and fall campaigns, as well as those available year-round. Rebates range from 65% off package prices to fixed amounts per unit, with specific incentives for LED lighting, thermostats, and appliances.
In 2024, a total of 395,472 eligible products were sold in participating stores across Nova Scotia, which represents an increase of 82% compared to 2023. As presented in [Table](#page-106-0) 17 below, sales of ENERGY STAR certified non-A-t...
AI summary In 2024, sales of energy-efficient products in Nova Scotia increased significantly, with LED fixture sales rising by 204% and smart thermostats increasing by 191%. However, appliance product sales declined by 11%, particularly for air purifiers, dehumidifiers, and washing machines.
6 Instant Savings Evaluation Approach The 2024 Instant Savings evaluation included a comprehensive impact evaluation whereby NTGRs, namely free-ridership, as well as unitary savings were reviewed and updated. The main objectives of the 202...
AI summary The 2024 Instant Savings evaluation aimed to calculate gross and net savings, including energy and peak demand savings, and avoided GHG emissions. The evaluation reviewed free-ridership and unitary savings, with research questions and methods outlined in a table.
Unitary Savings Review A unitary savings review was conducted for all measures as part of a major update to the 2024-2025 DSM Measure Assessment (DSM MA). [15](#page-109-0) The unitary savings review consisted of a literature review of tec...
AI summary A unitary savings review was conducted for all measures as part of updating the 2024-2025 DSM Measure Assessment. The review analyzed technical references, metering studies, and program evaluations to refine methodologies for calculating energy and peak demand savings, focusing on baseline assumptions, efficiency levels, and interactive effects factors.
7 Instant Savings Impact Evaluation The objectives of the 2024 Instant Savings impact evaluation were to determine gross and net electrical energy and peak demand savings, annually avoided GHG emissions, as well as effective useful life (E...
AI summary The 2024 Instant Savings impact evaluation aimed to quantify gross/net energy and peak demand savings, annual GHG emissions avoided, effective useful life (EUL) values, and lifetime energy savings from the program.
7.2 Gross Savings For Instant Savings, gross savings correspond to the change in energy consumption resulting from eligible energy efficient products being purchased by participants regardless of why they participated.[19](#page-110-5)
AI summary Gross savings for Instant Savings are defined as the change in energy consumption resulting from eligible energy-efficient product purchases by participants, regardless of their participation motivations. This metric focuses on actual energy use reductions rather than program-specific drivers.
Table 19: 2024 Instant Savings Tracked and Evaluated Unitary Energy Savings Product Tracked Savings [kWh/year] Evaluated Savings [kWh/year] ENERGY STAR Certified LED Non-A-type Lamps (R, BR, and Decorative) 49.2 43.2 ENERGY STAR Certified...
AI summary Table 19 presents the 2024 tracked and evaluated unitary energy savings for various energy-efficient products and technologies, including LED lighting, motion sensors, thermostats, and water heaters. The data highlights differences between tracked and evaluated savings, with some products showing significant discrepancies.
Table 20: 2024 Instant Savings Tracked and Evaluated Unitary Peak Demand Savings Product Tracked Savings [W/year] Evaluated Savings [W/year] ENERGY STAR Certified LED Non-A-type Lamps (R, BR, and Decorative) 7.97 7.00 ENERGY STAR Certified...
AI summary Table 20 presents the tracked and evaluated unitary peak demand savings for various energy-efficient products in 2024. The data includes products like LED lamps, dimmer switches, and heat pump water heaters, showing differences between tracked and evaluated savings. The section also references interactive effects related to these savings.
Table 21: 2024 Instant Savings Interactive Effects Factors for Lighting Products Product Category - LED Lamps, Fixtures, and Other Indoor Devices Weighted Energy Interactive Effects Factor Weighted Peak Demand Interactive Effects Factor In...
AI summary Table 21 outlines the 2024 Instant Savings Interactive Effects Factors for various lighting products, including LED lamps, fixtures, and motion sensors. The table provides weighted energy and peak demand interactive effects factors, as well as indoor and outdoor percentages for each product category.
7.2.5 Effective Useful Life The Evaluator validated the EUL values based on the 2024-2025 DSM MA. The EUL values are used in the calculation of electrical energy savings that are expected to persist over time. The baseline for LED lamps re...
AI summary The Evaluator validated Effective Useful Life (EUL) values based on the 2024-2025 DSM MA, noting that LED lamps will become the baseline starting in 2025. The EUL values are used to calculate electrical energy savings over time, with revised values for product categories rebated through Instant Savings, while other measures remain unchanged. The weighted average gross and net EUL values are 3.8 and 4.4 years, respectively.
Table 22: 2024 Instant Savings Equivalent EUL and Gross Lifetime Unitary Savings Values Product Tracked Equivalent EUL [years] Evaluated Equivalent EUL [years] Evaluated Gross Lifetime Unitary Savings [kWh] ENERGY STAR Certified LED Non-A-...
AI summary Table 22 presents 2024 Instant Savings Equivalent EUL and Gross Lifetime Unitary Savings Values for various energy-efficient products, including LED lamps, fixtures, and heat pump water heaters. The table compares tracked and evaluated Equivalent Useful Life (EUL) and evaluated gross lifetime unitary savings in kWh.
Evaluated 2024 Instant Savings Gross Electrical Energy and Peak Demand Savings (Continued) Smart Heavy- Smart Thermostats Efficient Efficient Product Category Power Bars duty Outdoor Timers Programmable Thermostats Electric Baseboards MSHP...
AI summary The document presents data on energy and peak demand savings from various efficiency measures in Nova Scotia for 2024, including the number of units installed, energy savings at the meter and generator, and effective useful life of the measures. The data is organized by product category and includes metrics like installation rates and line loss factors.
Evaluated 2024 Instant Savings Gross Electrical Energy and Peak Demand Savings (Continued) Product Category Efficient Combined Washers/Dryers Room Air Purifiers Dehumidifiers Pool Pumps Heat Pump Water Heaters High-efficiency Dishwashers B...
AI summary The document presents a detailed analysis of the 2024 Instant Savings program, highlighting gross electrical energy and peak demand savings across various product categories. It includes metrics such as energy savings, installation rates, effective useful life, and peak demand savings, providing a comprehensive overview of the program's impact.
[Figure](#page-118-0) 8 and [Figure](#page-119-0) 9 below compare tracked unitary electrical energy and peak demand savings to evaluated gross savings. Both sets of savings values include adjustments to account for interactive effects. As...
AI summary The text compares tracked unitary electrical energy and peak demand savings to evaluated gross savings, highlighting adjustments for interactive effects, particularly for LED fixtures, solar fixtures, and room air purifiers. GHG emission reductions are calculated using a Nova Scotia-specific factor applied to Instant Savings gross savings.
Table 24: Evaluated 2024 Instant Savings Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 26.884 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annua...
AI summary Table 24 presents the evaluated 2024 Instant Savings Gross GHG Emission Reductions, showing gross energy savings, the Nova Scotia-specific GHG emissions factor, and the resulting annual GHG emission reductions. Section 7.3 discusses net savings related to these reductions.
Table 30: 2024 Instant Savings Spillover Levels Product Category Spillover Level LED Lamps 9% LED Fixtures 2% All Other Products - 7.3.3 Net-to-gross Ratio Calculations
AI summary Table 30 outlines the 2024 Instant Savings Spillover Levels for various product categories, including LED Lamps and LED Fixtures. Section 7.3.3 discusses Net-to-gross Ratio Calculations, indicating a focus on energy efficiency program metrics.
Table 32: Evaluated 2024 Instant Savings Net Energy and Peak Demand Savings LED Non-A-ty /pe Lamps LED Recessed LED ENI ERGY STAR Fixture es . Dimmer Indoor Outdoor Motion Sensors Product Category R, BR, and Decorative Others Downlight Fix...
AI summary Table 32 presents the evaluated 2024 Instant Savings Net Energy and Peak Demand Savings for various product categories. It includes gross and net energy savings at the meter and generator, effective useful life, and peak demand savings, providing data on energy efficiency measures.
Evaluated 2024 Instant Savings Net Energy and Peak Demand Savings (Continued) Product Category Efficient Combined Washers/Dryers Room Air Purifiers Dehumidifiers Pool Pumps Heat Pump Water Heaters High Efficiency Dishwashers Bathroom & Uti...
AI summary The 2024 Instant Savings program exceeded its energy and peak demand savings targets by 77% and 45%, respectively. The table provides detailed energy and peak demand savings across various product categories, including gross and net savings at the meter and generator, as well as effective useful life and lifetime energy savings.
7.4 Realization Rate [Table](#page-127-2) 33 below compares the energy and peak demand savings established through this evaluation to those tracked by E1. It also includes the realization rate, representing the ratio of evaluated net savin...
AI summary This section introduces the concept of realization rate, comparing energy and peak demand savings evaluated by the process to those tracked by E1. The realization rate is defined as the ratio of evaluated net savings to tracked net savings for both energy and peak demand.
Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Unit Value Energy Savings Tracked Savings by E1 29.151 GWh 0.66 19.129 GWh 116% Evaluation Results 26.884 GWh 0.83 22.252 GWh Peak Demand Savings Tracked Savings by E1...
AI summary The table presents energy and peak demand savings tracked by E1 and evaluation results, including gross savings, net-to-gross ratio (NTGR), net savings, and realization rates. The data highlights the performance of energy efficiency measures in Nova Scotia.
Particip ation Level Gross Savings NTGR Net S Savings Value Unit Value Unit Value Value Unit ARet Energy Savings 4.195 GWh 0.56 2.365 GWh Lifetime Energy Savings 16.729 GWh 0.56 9.433 GWh Peak Demand Savings 5,941 Appliances 0.598 MW 0.56...
AI summary The Residential Efficient Product Rebates program exceeded its 2024 energy and peak demand savings targets by 70% and 41%, respectively, primarily due to the contribution of Instant Savings. The program achieved 24.617 GWh in net electrical energy savings and 2.765 MW in net peak demand savings.
A. Identification and Screening of Respondent Thank you for taking the time to answer the following short survey about energy efficiency. We are gathering information from customers who purchased certain energy-efficient LED bulbs or LED f...
AI summary The text is a survey targeting customers who purchased LED bulbs or fixtures between September 23rd and November 17th. It asks for purchase locations and SKU numbers, with conditional routing based on SKU type. The purpose is to gather data for energy efficiency initiatives.
D. Free-Ridership - LED Bulbs - D1. Efficiency Nova Scotia offered a discount on non-pear-shaped LED bulbs. Before paying at the cash register, were you aware that a discount was offered on the purchase of LEDs? [ALLOW ONLY ONE CODE] - 1....
AI summary This section of the proceeding explores customer awareness and behavior related to discounts on LED bulbs offered by Efficiency Nova Scotia. It includes questions about whether respondents knew about the discount, whether they delayed purchases, and what they would have bought if the discount was not available.
E3. Did you purchase these fixtures for your own use (for example, for your home or cottage)? [ALLOW ONE RESPONSE ONLY] 1. I purchased them for my own use 96. Other, please specify [] E4. Are there any LED fixtures currently installed in y...
AI summary The text contains a series of survey questions related to the purchase and installation of LED fixtures, including whether they are for personal use, existing LED fixtures in the home, installation location, and reasons for purchase.
[ASK THE FOLLOWING QUESTIONS IF AWARE OF THE DISCOUNT [(G1=](#page-148-2)1) OR [(G2=](#page-148-1)1), OTHERWISE SKIP TO NEXT SECTION] - G4. Were you aware that this would be the last year to take advantage of Efficiency Nova Scotia discoun...
AI summary This section asks respondents if they were aware that this would be the last year to take advantage of Efficiency Nova Scotia discounts on LED bulbs and what they would have purchased if the discount had not been offered. It also asks about alternative bulb types if they had not chosen LED fixtures.
H. Cross-Influence ROTATE [(H1+](#page-151-1) [H2-](#page-151-2)[H3)](#page-151-3) AND [(H4](#page-151-4) + [H5-](#page-151-5)[H6)](#page-151-6) SEQUENCES; SHOW [H1](#page-151-1) TO [H3](#page-151-3) ON SAME SCREEN AND H4 TO [H6](#page-151...
AI summary The section includes survey questions assessing how prior participation in Efficiency Nova Scotia programs and exposure to promotional materials influenced customers' decisions to purchase LED lighting products.
B3. Did you purchase these bulbs for your own use (for example, for your home or cottage)? 2024 2023 2022 2021 Sample Size 41 81 49 67 I purchased them for my own use 98% 96% 98% 100% Others 2% 4% 2% 0% B4. Are there any non-pear-shaped LE...
AI summary The text presents survey results about bulb purchases and LED bulb installations in homes. Most respondents purchased bulbs for personal use, and a significant percentage have non-pear-shaped LED bulbs installed in their homes.
- B8. [ASK IF B1 (MORE THAN 1 BULB)] You bought [INSERT NUMBER OF LEDS FROM B1] LED bulbs? How many, if any, of these [INSERT NUMBER OF LEDS FROM B1] LED bulbs will be installed… 2024 2023 2022 2021 Sample Size 41 81 49 67 To replace anoth...
AI summary The text presents survey data on LED bulb installation intentions, including replacement of existing LED bulbs and non-LED bulbs across different years. Respondents indicate whether they plan to replace bulbs when they burn out, replace working bulbs, or use them for new fixtures.
C1 / F1. Have you ever heard of the Efficiency Nova Scotia program that offers instant savings at the cash register for the purchase of energy-efficient lighting, controls or appliances? 2024 2023 2022 2021 200 122 177 120 70% 65% 65% 58%...
AI summary The Efficiency Nova Scotia program offers instant savings at the cash register for purchasing energy-efficient products. The data shows varying awareness and participation rates across different years, with in-store promotions and store personnel being the primary sources of information about the program.
D4. Were you aware that this would be the last year to take advantage of Efficiency Nova Scotia discounts on LED bulbs? 2024 Sample Size 5 (#) Yes 2 No 3 Base: Respondents who were aware of discounts on LED bulbs this fall New question in...
AI summary The text discusses respondents' awareness of Efficiency Nova Scotia discounts on LED bulbs in 2024, with a sample size of 5. Only 2 respondents were aware it would be the last year for discounts, and 2 delayed purchases to take advantage of the rebate campaign.
D6. If the discount on LEDs had NOT been offered, what would you have bought? Would you have… 2024 2023 2022 2021 Sample Size 30 40 33 35 Bought LEDs anyway 40% 60% 45% 89% Bought another type of bulb 17% 23% 6% 3% Not bought any bulbs 43%...
AI summary The data shows that a significant percentage of respondents would have purchased LED bulbs even without the discount, with the percentage decreasing over time. A smaller portion would have bought other types of bulbs, while the majority would have not purchased any bulbs.
D7. Which type(s) of bulb would you have purchased instead? 2024 2023 2022 2021 Sample Size 5 (#) 9 (#) 2 (#) 1 (#) Incandescent 3 4 1 - Halogen 1 5 - - CFL 1 - 1 1 Base: Respondents who purchased non-A-type LED bulbs who would have purcha...
AI summary The question asks respondents who purchased non-A-type LED bulbs about the type of bulb they would have purchased instead, with data provided for the years 2021 to 2024. The table shows the number of respondents for each bulb type across the years.
D10. Without the discount, would you have definitely purchased the same number of LED bulbs, probably purchased the same number, probably purchased fewer or definitely purchased fewer? 2024 2023 2022 2021 Sample Size 23 29 29 32 Definitely...
AI summary The data shows varying customer responses to LED bulb discounts over the years, with a decrease in the percentage of customers who would definitely purchase the same number of bulbs without the discount, and an increase in those who would probably or definitely purchase fewer bulbs.
D11. You bought [INSERT NUMBER OF LEDS FROM B1 (IF CORRECT) OR B2.2] LED bulbs, what proportion of these bulbs do you expect to install in the next 12 months? 2024 Sample Size 2 (#) All or nearly all 1 Less than half 1 Base: Respondents wh...
AI summary The question asks respondents about their expected installation rate of LED bulbs purchased in the next 12 months, with a sample size of 2. One respondent expects to install all or nearly all bulbs, while the other expects to install less than half. The context is related to the last year for Efficiency Nova Scotia discounts on LED bulbs.
E5. Will the LED fixture(s) you bought be installed indoor or outdoor? 2024 2023 2022 2021 Sample Size 159 41 128 53 Indoor 82% 95% 91% 89% Outdoor 4% 2% 4% 8% Both 14% 2% 5% 4% Base: Respondents who purchased LED fixtures
AI summary The table shows the distribution of LED fixture installations between indoor, outdoor, and both locations across the years 2021 to 2024. The majority of installations are for indoor use, with a slight decline in outdoor and both categories over time.
- G1. Efficiency Nova Scotia offered a discount on LED fixtures. Before paying at the cash register, were you aware that a discount was offered on the purchase of LED fixtures?
AI summary Efficiency Nova Scotia provided a discount on LED fixtures, and the question seeks to determine if the individual was aware of this discount before making the purchase.
- G2. [DO NOT ASK IF 'YES' IN G1] To confirm, you did not know about the discount on specific LED fixtures before paying at the register? 2024 2023 2022 2021 Sample Size 159 41 128 53 Yes, were aware of the discount before paying 82% 71% 4...
AI summary The text presents survey results on customer awareness and behavior regarding discounts on LED fixtures offered by Efficiency Nova Scotia. It shows that awareness of the discount increased over time, but most respondents were not aware of the discount before purchasing. Many indicated they would not have purchased fixtures without the discount.
Multiple responses G7. How likely would you have been to buy the LED fixtures that you purchased if you had to pay the full price? Please answer on a scale of 0 to 10, with a 0 indicating that you "Definitely Would Not Have Bought these LE...
AI summary The question asks respondents how likely they would have been to purchase LED fixtures at full price, using a scale from 0 to 10, where 0 means they definitely would not have bought them and 10 means they definitely would have.
Likelihood of Buying LEDs without Discount 2024 2023 2022 2021 Sample Size 131 30 55 35 MEAN 3.4 6.2 5.7 6.2 Base: Respondents who purchased LED fixtures who were aware of discount prior to purchase Don't know/Refused excluded from calcula...
AI summary The table shows the likelihood of purchasing LEDs without a discount over the years 2021 to 2024, with sample sizes and mean values provided. The data is based on respondents who purchased LED fixtures and were aware of discounts prior to purchase, excluding those who didn't know or refused to answer.
G8. If the discount had NOT been offered, when would you have purchased the LED fixtures that you did? 2024 2023 2022 2021 Sample Size 131 30 55 35 Earlier 1% 2% - - Definitely on the same day 5% 20% 11% 20% Probably on the same day 7% 17%...
AI summary The table shows the distribution of responses to when respondents would have purchased LED fixtures if a discount had not been offered, with data from 2021 to 2024. Most respondents indicated they would have purchased the fixtures at a later date or not at all.
H1. Before your recent purchase, had you at any time in the past benefitted from a discount on energy efficient products or participated in other programs offered by Efficiency Nova Scotia? 2024 2023 2022 2021 Sample Size 197 122 176 118 Y...
AI summary The question asks if respondents had previously benefited from discounts on energy-efficient products or participated in Efficiency Nova Scotia programs. The table shows participation rates over several years, with a majority of respondents reporting 'Yes' in each year.
H2. Your previous experience with Efficiency Nova Scotia programs was a major factor in your decision to purchase [LED BULBS/FIXTURES]. 61 100 66 66% 65% 70% 34% 35% 30% 80% 20% H3. Because of your previous experience with Efficiency Nova...
AI summary The text discusses customer experiences with Efficiency Nova Scotia programs, particularly how these programs influenced their decision to purchase LED bulbs or fixtures. It highlights the impact of promotional materials and energy savings on customer choices over multiple years.
H6. The Efficiency Nova Scotia promotional materials you saw prompted you to take into account the savings on your energy bill when choosing different lighting options for your home. 2024 2023 2022 2021 Sample Size 132 78 118 78 Agree 86%...
AI summary The Efficiency Nova Scotia promotional materials influenced respondents to consider energy savings when selecting lighting options for their homes. The data shows a high percentage of agreement across multiple years, with slight variations in response rates.
Table 1: 2024 Instant Savings Corrected Tracked Savings Value Tracked by E1 Program Component Results Corrected Tracked Value Relative Difference Value Unit Value Unit Value Instant Savings Gross Energy Savings at the Generator 28.519 GWh...
AI summary The Evaluator identified discrepancies between tracked and corrected tracked values in the 2024 Instant Savings program, primarily due to incorrect product type categories in three lighting models and errors in the net energy savings calculation for ENERGY STAR® certified clothes dryers.
Table 2: ME Algorithm - LED bulbs Total Non-A Type Sales Non-A type LED bulbs sold from January – December 2024(extrapolated from retailer data and responses in interview) #LEDJan-Dec LED Sales During Instant Savings' Campaigns LED Bulb Sa...
AI summary The text presents a table detailing the calculation of final market effects for LED bulb sales, including the influence of Efficiency Nova Scotia's programs and the determination of free-ridership levels based on customer awareness of discounts.
Table 1: Summary of 2024 Existing Residential Program Evaluation Program Evaluation Type Methodology Component Impact Process Market AMH Comprehensive X › Program staff interviews › Energy auditor (EA) interviews › Participant, dropped-out...
AI summary The document provides a summary of the 2024 evaluation of existing residential programs, detailing the evaluation types, methodologies, and components for various programs such as AMH, ASFH, EPI, Green Heat, HEA, MHEEP, and Residential Behaviour. The evaluation includes interviews, tracking sheet audits, billing analysis, and GHG emission reduction calculations.
[Table](#page-194-0) 2 below presents the participation levels, NTGRs, evaluated gross and net savings at the generator, annual GHG emission reductions, as well EUL values for each program component and for Existing Residential as a whole.
AI summary The table presents participation levels, NTGRs, evaluated gross and net savings at the generator, annual GHG emission reductions, and EUL values for each program component and for Existing Residential as a whole.
Table 2: Overall 2024 Existing Residential Participation and Evaluated Savings Participation Level Gross Savings NTGR Net Savings Value Unit Value Unit Value Value Unit AMH Energy Savings 83 Projects 1.159 GWh 1.00 1.159 GWh Lifetime Energ...
AI summary Table 2 presents the 2024 participation levels and evaluated savings for various residential programs, including energy savings, peak demand savings, GHG emission reductions, and energy efficiency measures. The data includes metrics like gross and net savings, as well as program-specific participation numbers.
ts (64 prescriptive and 19 comprehensive) generated electrical savings in 2024. Together, AMH paths generated 21% and 23% fewer electrical energy and peak demand savings respectively compared to 2023. 2024 AMH-Finding: Following project re...
AI summary In 2024, AMH programs achieved 21% and 23% lower electrical energy and peak demand savings compared to 2023. The Evaluator adjusted energy savings upward and peak demand savings downward, with discrepancies between evaluated and E1-tracked savings attributed to these adjustments.
HEA Findings and Recommendations 2024 HEA-Finding: HEA net electrical energy savings exceeded the target of 19.012 GWh by 68%, and the planned net peak demand savings of 4.799 MW by 81%. 2024 HEA-Finding: With 5,367 projects, the 2024 part...
AI summary The 2024 HEA exceeded energy savings targets by 68% and peak demand savings by 81%, with record participation. The CGH Grant's closure may reduce future savings. Discrepancies in savings calculations were addressed, and low-saving wood/pellet fireplaces are recommended for removal from HEA offers.
MHEEP Findings and Recommendations This subsection presents the key findings from the MHEEP evaluation. The Evaluator has no specific recommendation for MHEEP. 2024 MHEEP-Finding: MHEEP net electrical energy savings fell short of targets b...
AI summary The MHEEP program underperformed in 2024, achieving 35% less net energy savings than targets but exceeding peak demand savings by 189%. Participation increased by 19%, yet energy savings per participant fell by 41%. Discrepancies with E1's data stemmed from revised adjustment ratios and heat pump peak demand metrics.
Residential Behaviour Findings and Recommendations This subsection presents the key findings from the 2024 Residential Behaviour evaluation. The Evaluator has no specific recommendation for Residential Behaviour. 2024 Residential Behaviour...
AI summary The 2024 Residential Behaviour program achieved 6.270 GWh in energy savings, below its 8.000 GWh target, but shows promise as it scales. Attrition rates reached 5.2-7.0% among participants, and treatment group customers showed higher engagement in other programs compared to controls.
EfficiencyOne (E1), an independent, non-profit organization, is responsible for helping Nova Scotians improve the energy efficiency of their homes and workplaces by designing, marketing, and delivering demand-side management (DSM) for Nova...
AI summary EfficiencyOne (E1), a non-profit organization, manages energy efficiency and demand-side management (DSM) programs in Nova Scotia through the Efficiency Nova Scotia (ENS) franchise. E1's 2024 DSM program portfolio includes residential and BNI programs, and an evaluation report was commissioned by E1 to assess these programs. The evaluation focuses on impact assessments, including baseline definitions, savings calculation methodologies, and parameter values.
Table 4: Types of Evaluations Conducted for Each Program Component, 2024 2024 Program Program Component Process Market Impact Existing Residential AMH X Comprehensive ASFH X Condensed EPI X Comprehensive Green Heat Comprehensive HEA Compre...
AI summary Table 4 outlines the types of evaluations conducted for each program component in 2024, including details on market and impact assessments. The Evaluator prepared a DSM evaluation report that includes findings on energy savings, peak demand savings, and GHG emissions for each component.
1.3 Participation History Since 2021, AMH savings are generated by two types of projects, namely comprehensive and prescriptive projects. In 2024, 83 projects generating electrical energy savings were completed under AMH, including 19 comp...
AI summary The Affordable Multifamily Housing (AMH) program in Nova Scotia saw 83 projects completed in 2024, generating 1.159 GWh of electrical energy savings and 0.570 MW of peak demand savings. Prescriptive projects dominated (80% of savings), though savings per project decreased compared to 2023. Comprehensive projects increased from 11 to 19, reflecting stabilization after prior growth driven by heat pump projects.
3.2.1 Motivations for Participating in AMH Cost savings were the primary motivator for participating in AMH with seven out of 10 mentioning the rebates offered , and six of 10 mentioning saving money on energy bills . Reasons for taking pa...
AI summary Participants in AMH cited cost savings (rebates, energy bill reductions) as primary motivators, with secondary reasons including tenant comfort and energy efficiency. EAs noted rebates help non-profits maintain affordable housing, while GHG reduction was a minor factor. Figure 5 visualizes these reasons.
3.2.2 Reasons for Initial Interest Among Dropped-out Participants and Non-participants As seen above among participants, when it comes to why dropped-out participants and non-participants were initially interested in AMH, cost-related fact...
AI summary Dropped-out participants and non-participants in AMH were primarily motivated by rebates/financial support, followed by energy efficiency and cost savings. Expectations were vague, with most anticipating financial incentives but unclear on specifics. Negative past rebate experiences tempered some expectations.
3.3.2 Energy Auditor Satisfaction As with AMH participants, EAs appear satisfied overall with AMH as illustrated in [Figure](#page-21-0) 12 below. They are particularly content with the selection of upgrades available through the program c...
AI summary Energy auditors (EAs) are generally satisfied with the AMH program, particularly with the selection of upgrades and communication with EfficiencyOne (E1). However, dissatisfaction arises from the 10-day reporting timeframe, the simulator software, and the non-user-friendly Word-based reporting templates. EAs also noted a lack of information on building systems prior to visits.
Table 7: 2024 Elements of Dissatisfaction and Justifications Among EAs Element of Dissatisfaction (Score of <8) Reasons for Dissatisfaction (#) n=4 Initial audit reporting template › Template is not user-friendly/awkward/lengthy to fill ou...
AI summary The table highlights dissatisfaction among Energy Auditors (EAs) with various aspects of program delivery, including audit reporting templates, simulator software, information provided at the start of projects, and communication processes. Key issues include non-user-friendly templates, limited flexibility, and challenges with software tools like R2000 and RETScreen.
3.3.5 Participant Questions and Concerns Participants' questions to EAs during the initial energy audit visit vary based on their level of understanding of AMH, their knowledge of their building's construction, and/or their interest in the...
AI summary Participants ask Energy Auditors about AMH rebates, next steps, and building operations, with heating systems and insulation being the most common topics. Questions include backup heating, insulation costs, and electrical system compatibility.
3.4 Participant and EA Suggestions for Improvements AMH participants were presented with a list of seven tools and supports that could be offered to help them navigate the program component. Two of the top three tools/supports mentioned as...
AI summary AMH participants emphasized affordability tools like co-funding and low-interest financing as critical. EAs suggested administrative improvements (e.g., delivery agent portals, streamlined reporting) and training enhancements. Additional recommendations included heat pump tutorials, window upgrades, and solar panel eligibility.
3.5 Alternatives for Implementing Other Energy Efficiency Measures
AI summary The section outlines alternatives for implementing energy efficiency measures, though no specific details or proposals are provided in the text. It likely explores options such as demand-side management, appliance retirement, and other DSM initiatives, but content is limited to the heading.
Alternative Programs Two dropped-out participants and five non-participants stated that they either had taken part in a program other than AMH or had plans to do so in the near future. One dropped-out participant noted that they had not ex...
AI summary Participants and non-participants in the AMH program cited administrative burdens and eligibility issues as barriers to engagement. Some opted for alternative programs like E1 (targeting affordable housing) or CMHC initiatives. Interviewees expressed interest in reapplying to AMH if other programs didn’t conflict. Limited funding sources were reported, with Housing Nova Scotia and CMHC funds mentioned as supports.
Energy Efficiency Upgrades Only three interviewees noted having completed energy efficiency upgrades in the past year: One droppedout participant had made several energy efficiency upgrades, including new insulation, installing heat pumps,...
AI summary Three interviewees reported completing energy efficiency upgrades in the past year, including insulation, heat pumps, and appliance replacements. One participant worked with Housing Nova Scotia, while others utilized an E1 residential program or discounted contractor services.
AMH Strengths: - › Financial support for affordable housing - › Provides a comprehensive list of upgrades that can be implemented over time - › 50% incentive received before project end - › Potential energy cost savings - › High overall sa...
AI summary The AMH program offers financial support, 50% upfront incentives, energy cost savings, and high participant and EA satisfaction. It features clear forms, a 100 NPS, and no concerns about agreement terms, highlighting its effectiveness and user-friendliness in multifamily housing upgrades.
4 AMH Impact Evaluation The objectives of the 2024 AMH impact evaluation were to determine gross and net electrical energy and peak demand savings, annually avoided GHG emissions, as well as the EUL and associated lifetime energy savings.
AI summary The 2024 AMH impact evaluation aimed to assess gross and net electrical energy and peak demand savings, annually avoided GHG emissions, and the Effective Useful Life (EUL) of AMH programs alongside their lifetime energy savings.
4.2 Gross Savings Gross savings correspond to the change in energy consumption resulting from various electrical energy saving upgrades such as building envelope measures, space heating measures, and domestic hot water (DHW) measures imple...
AI summary Gross savings reflect energy consumption reductions from electrical upgrades by AMH participants, including building envelope, heating, and DHW measures. Methodology for evaluating 2024 AMH gross savings includes assessing interactive effects and EUL values.
Comprehensive Path Project Desk Review Findings Through the 2024 comprehensive path project desk reviews, the Evaluator made three types of adjustments: - › The impacts of some measures on other systems, which correspond to interactive eff...
AI summary The 2024 Comprehensive Path Project desk reviews identified modeling errors, unimplemented measures, and parameter discrepancies across five projects. Adjustments reduced energy savings estimates by up to 25%, leading to an overall 0.873 adjustment ratio. Due to a 18% margin of error, non-reviewed projects used tracked savings instead of extrapolated ratios.
Prescriptive Path Project Desk Review Findings Energy savings for AMH prescriptive path projects are calculated using the 2024-2025 DSM MA equations. Among the reviewed prescriptive path projects, four were lighting projects and six were h...
AI summary The Prescriptive Path Project Desk Review evaluates energy savings calculations for AMH projects, noting that lighting projects required no adjustment ratios while heat pump projects saw 6% increased savings due to HSPF2 adjustments. One project's energy savings decreased by 10% due to a regional HSPF2 mismatch. The overall adjustment ratio was 1.016 (margin of error 2.8%), below the 10% threshold, leading to its use only in 2024 evaluations.
Prescriptive Project Review Findings Similarly to energy savings, peak demand savings for AMH prescriptive projects are calculated using the 2024-2025 DSM MA equations. For lighting projects, project reviews revealed that E1 used a peak co...
AI summary The review found that peak demand savings for AMH projects used 2024-2025 DSM MA equations. Lighting projects had a 32% reduction in peak savings after adjusting coincidence factors, but margin of error limited extrapolation. Heat pump projects had no adjustments, leading to equal evaluated and tracked savings. No adjustment ratios were extrapolated for non-reviewed projects.
4.2.3 Interactive Effects In a home, interactive effects occur when the implementation of energy efficiency measures has an impact on the energy consumption of other factors such as heating and cooling. The interactive effects of space hea...
AI summary Interactive effects in energy efficiency measures, such as heating and cooling, are addressed in savings calculations for comprehensive projects. The 2024-2025 DSM MA includes these effects for prescriptive projects. Evaluators assumed lamps operating 10+ hours daily coincided with peak hours, using a peak coincidence factor of 1, while others used annual operating hours divided by total yearly hours.
The annual gross savings at the generator are presented in [Table](#page-34-0) 11 below. The gross energy savings at the generator were estimated by using different line loss factors for each participant based on their rate code. The line...
AI summary The document presents annual gross energy savings at the generator, calculated using line loss factors specific to each participant's rate code. These factors were submitted to the NSUARB as part of the 2014 Cost of Service Study Progress Update by Nova Scotia Power. The total gross electrical energy savings are 1.159 GWh annually and 19.397 GWh over the lifetime, with an average EUL of 16.7 years for AMH in 2024.
Table 11: Evaluated 2024 AMH Gross Energy and Peak Demand Savings Prescriptive Comprehensive Heat Pumps Lighting Total Number of Projects 19 57 7 83 Energy Savings Tracked Gross Energy Savings – at the Meter (GWh) 0.226 0.681 0.153 1.061 A...
AI summary Table 11 presents the evaluated 2024 AMH gross energy and peak demand savings, including tracked energy savings, adjustments, and lifetime energy savings. It also outlines peak demand savings and their adjustments. GHG emissions reductions are calculated using a Nova Scotia-specific factor applied to the energy savings results.
4.3.1 Evaluated Net Savings Net savings are defined as the changes in energy use that are specifically attributable to AMH. Since spillover and free-ridership effects were considered nil, the net energy savings are equal to the gross savin...
AI summary The section defines net savings for AMH (Affordable Multifamily Housing) as gross savings, assuming no spillover or free-ridership effects. However, AMH missed its 2024 electrical energy and peak demand savings targets by 39% and 64%, respectively, as shown in Figure 14.
Table 13: Comparison of 2024 AMH Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Unit Value Energy Savings Tracked Savings by E1 1.158 GWh 1.00 1.158 GWh Evaluation Resu...
AI summary Table 13 compares the 2024 AMH tracked and evaluated savings at the generator, showing that net evaluated savings are nearly identical to tracked savings, with minor differences attributed to the application of the adjustment ratio and one-time adjustments.
2024 AMH-Finding: Following project reviews, the Evaluator made an overall upward adjustment to electrical energy savings and a downward adjustment to peak demand savings. The 2024 AMH project reviews led to two adjustments for electrical...
AI summary The 2024 AMH project reviews resulted in an upward adjustment to electrical energy savings via a 1.016 AR for prescriptive heat pump projects due to HSPF2 factor changes, and a downward adjustment to peak demand savings from revised peak coincidence factors and comprehensive project modelling errors. Adjustments largely offset each other, yielding negligible net differences.
6.1 ASFH Description ASFH provides energy efficient retrofits and heat pump installations to income-qualified Nova Scotian owners of both electrically heated and non-electrically heated homes at no cost to participants. The program compone...
AI summary The Affordable Single-family Homes (ASFH) program offers no-cost energy-efficient retrofits and heat pump installations to income-qualified Nova Scotian homeowners. It includes building envelope upgrades, moisture management, and appliance replacements via the E1 Appliance Retirement program. E1 manages HomeWarming, supported by delivery agents and contractors, with energy assessments conducted by EAs and retrofits approved by E1. Heat pump installations are handled separately by contractors.
6.3 Participation History For ASFH, participation is defined as participants (homes) that have completed a project and have positive electrical energy savings, participants that completed a project with no savings, and all participants tha...
AI summary The ASFH program saw a significant increase in participation from 2023 to 2024, with 1,210 homes participating. However, average savings per participant decreased by 48% due to updated adjustment ratios and a shift in project types, including more smart thermostats and non-modelled heat pumps. 43 appliances were replaced, and 17 homes had no energy savings.
7 ASFH Evaluation Approach The 2024 evaluation consisted of a condensed impact evaluation and a process evaluation. The main objectives of the 2024 ASFH evaluation were as follows: - › Collect information on program staff, partner, and par...
AI summary The 2024 evaluation of the Affordable Single-family Homes (ASFH) program focused on collecting perspectives from program staff, partners, and participants, as well as calculating gross and net energy savings, peak demand savings, and avoided GHG emissions. The evaluation included both impact and process components, with key research questions, methods, and sample sizes outlined in a table.
Table 14: 2024 ASFH Evaluation Approach Evaluation Objectives Research Questions Methodology Collect information on program staff, partner, and participant perspectives › How did participants become aware of ASFH? › What are the participan...
AI summary This chunk outlines the evaluation approach for the 2024 Affordable Single-family Homes (ASFH) program, focusing on collecting participant perspectives and calculating gross and net results. It includes survey and interview methods for program evaluation and outlines the use of tools like HOT2000 and the net-to-gross ratio (NTGR) for calculating savings and GHG emission reductions.
GHG Emission Reduction Calculations To obtain net avoided GHG emissions in CO2 eq for ASFH, the Evaluator multiplied net energy savings by the latest Nova Scotia-specific factor for GHG emissions generated by electricity production. This f...
AI summary The Evaluator calculates net avoided GHG emissions for Affordable Single-family Homes (ASFH) by multiplying energy savings with a Nova Scotia-specific factor derived from NS Power data. The 2024-2025 DSM MA serves as a reference for evaluating energy and peak demand savings parameters within E1's DSM program.
Motivations for Participating in ASFH Modelled participants mainly wanted to participate in ASFH to save on energy or reduce energy costs (60%). Distant seconds were the intention to upgrade or replace a heating system (13%) and upgrade or...
AI summary Modelled participants in the Affordable Single-family Homes (ASFH) program primarily aimed to save on energy costs (60%), with 13% each seeking heating system upgrades and insulation improvements. Heat pump participants from the HomeWarming program were excluded from this question as they were directly contacted by E1.
allation services provided. Figure 29: Satisfaction with Contractor/EA Interactions and Communications, 2024 – Heat Pump Only Participants As illustrated i[n Figure](#page-59-0) 30 below, heat pump only participants generally agreed that t...
AI summary Participants in the ASFH program report high satisfaction with information received about heat pump installations (87%), though 30% remain uncertain about operation and maintenance. 87% agree their homes are more comfortable post-upgrades, but fewer can confirm cost savings or winter warmth. A minority (43%) now use previously uncomfortable spaces due to ASHP installations.
9.2.1 Electrical Energy Savings For ASFH, electrical energy savings are calculated based on HOT2000 simulation results adjusted with billing analysis results and unitary savings values for prescriptive measures, as shown in the equation be...
AI summary Electrical energy savings for Affordable Single-family Homes (ASFH) are calculated using HOT2000 simulation results adjusted with billing analysis and unitary savings values for prescriptive measures, as outlined in the provided equation.
Where: - › and correspond to the modelled energy consumption levels obtained in HOT2000 during the pre-retrofit (D) and post-retrofit (E) assessments respectively. Since modelled energy consumption levels were not directly available in the...
AI summary The text outlines a methodology for calculating energy savings using EnerGuide ratings, adjustment ratios (ARs) derived from 2024 billing analyses, and prescriptive measures in ASFH. It references HOT2000 modelled consumption, HEA evaluations, and DA assessments for space heating estimates.
Modelled Energy Savings After the D and E assessments, the EAs model the house in the HOT2000 energy simulation software to obtain the initial and final EnerGuide ratings of that house. These ratings were used to determine the electrical e...
AI summary The document outlines the methodology for calculating modelled energy savings using HOT2000 simulations and adjustment ratios (ARs) derived from billing analyses. It details changes to the savings calculation approach in 2024, including distinct ARs for heat pump scenarios and the use of whole-home consumption data instead of space heating-only metrics.
Table 17: Tracked and Evaluated 2024 ASFH Unitary Energy Savings Measure Tracked Savings [kWh/year] Evaluated Savings [kWh/year] Smart Thermostats with Heat Pump Baseline 514 564 Appliance Replacement Refrigerators 735 674 Freezers 2,006 1...
AI summary Table 17 presents tracked and evaluated energy savings for 2024 in the Affordable Single-Family Housing (ASFH) program, including savings from smart thermostats, refrigerators, freezers, and dehumidifiers. The data shows discrepancies between tracked and evaluated savings, indicating potential issues with measurement or evaluation methods.
participants that installed a heat pump and had no modelled energy savings, peak demand savings were calculated using the Green Heat calculation approach (see Subsection [19.2.3](#page-135-0) below). Smart thermostats and replaced applianc...
AI summary The document discusses the calculation of peak demand savings for heat pumps and other measures under the Affordable Single-Family Housing (ASFH) program. It references the Green Heat calculation approach and notes that smart thermostats and replaced appliances are not modelled in HOT2000, with unitary peak demand savings values reviewed and updated in the 2024-2025 DSM MA.
Table 18: 2024 Appliance Replacement Tracked and Evaluated Unitary Peak Demand Savings Tracked Savings [W/year] Evaluated Savings [W/year] Refrigerators 101 93.0 Freezers 277 190 Dehumidifiers 202 206 9.2.3 Interactive Effects
AI summary Table 18 presents the tracked and evaluated unitary peak demand savings from appliance replacements in 2024, including refrigerators, freezers, and dehumidifiers. Section 9.2.3 discusses interactive effects, likely referring to how different appliances or programs may influence each other's energy savings outcomes.
9.2.4 Effective Useful Life As part of the 2024-2025 DSM MA activities, the Evaluator reviewed the EUL values used in the calculation of electrical energy savings that are expected to persist over time; the EUL values were not revised for...
AI summary The Evaluator reviewed Effective Useful Life (EUL) values for electrical energy savings in the 2024-2025 DSM MA activities. EUL values were not revised for most measure categories except modelled measures, such as building envelope upgrades and modelled space heating equipment. Table 19 shows the EUL values changed in 2024.
Table 20: Evaluated 2024 ASFH Modelled Measure Gross Energy and Peak Demand Savings Total Energy Savings Gross Energy Savings Without Adjustment Ratio (AR) – at the Meter (GWh) 4.484 Gross Energy Savings with AR – at the Meter (GWh) 3.111...
AI summary Table 20 and Table 21 present energy and peak demand savings from the 2024 Affordable Single-Family Housing (ASFH) program. The tables include modeled and non-modeled measures, with energy savings calculated using line loss factors provided by NS Power. The data highlights the impact of various efficiency measures on energy and peak demand, including heat pumps and appliance replacements.
As presented in [Table](#page-70-0) 22 below, appliances replaced through Appliance Replacement (refrigerator, freezer, and dehumidifier replacements) resulted in gross electrical energy savings at the generator of 0.045 GWh and gross peak...
AI summary Appliance replacements in Nova Scotia resulted in significant energy savings, with 0.045 GWh of gross electrical energy savings and 0.008 MW of peak demand savings. The average Effective Useful Life (EUL) for Affordable Single-Family Housing (ASFH) was 20.0 years in 2024.
Table 22: Evaluated 2024 ASFH Gross Electrical Energy and Peak Demand Savings Measure Category Modelled Measures Non-modelled Heat Pumps Smart Thermostats Appliance Replacements Total Number of Participants with Savings 880 254 79 - 1,193...
AI summary Table 22 presents the evaluated 2024 energy and peak demand savings from the Affordable Single-Family Housing (ASFH) program. The table includes data on the number of participants, gross energy savings, effective useful life, and gross peak demand savings across various measure categories such as heat pumps, smart thermostats, and appliance replacements.
Table 23: Evaluated 2024 ASFH Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 3.719 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annual GHG Emissi...
AI summary Table 23 evaluates the 2024 gross GHG emission reductions from Affordable Single-Family Housing (ASFH) programs in Nova Scotia. It calculates these reductions using energy savings and a Nova Scotia-specific GHG emissions factor for electricity production, based on data from Nova Scotia Power and Emera Inc.
Table 24: Comparison of 2024 ASFH Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Unit Value Energy Savings Tracked Savings by E1 4.693 GWh 1.00 4.693 GWh 79% Evaluation...
AI summary Table 24 compares 2024 energy and peak demand savings tracked by E1 and evaluated by the Evaluator. Evaluated savings were 21% and 3% lower than tracked savings, primarily due to revised adjustment ratios and updated unitary savings.
2024 ASFH-Finding: ASFH exceeded its electrical energy and peak demand savings targets. ASFH achieved 3.719 GWh in net electrical energy savings and 2.089 MW in net peak demand savings at the generator in 2024, thus exceeding the planned t...
AI summary In 2024, ASFH achieved 3.719 GWh in net electrical energy savings and 2.089 MW in net peak demand savings, exceeding targets of 2.825 GWh and 1.046 MW by 32% and 100%, respectively.
2024 ASFH-Finding: In 2024, 1,210 homes participated in ASFH, nearly five times the number recorded in 2023. Among the 1,210 ASFH participants, 880 implemented building envelope measures, with 696 of them also installing a heat pump. Addit...
AI summary In 2024, 1,210 homes participated in ASFH, a fivefold increase from 2023. Participants implemented building envelope measures, heat pumps, and smart thermostats. While gross energy savings rose 158% and peak demand savings 233%, average savings per participant fell 48% due to updated adjustment ratios and a shift toward projects with lower impact, like smart thermostats and non-modelled heat pumps.
Table 25: 2024 EPI List of Eligible Products Products Electrical Savings Non-electrical Savings Lighting Products LED Lamps Including A-types, Reflectors, and Chandeliers X - LED Nightlights X - Solar Security Fixtures X - Motion Sensors X...
AI summary Table 25 outlines the 2024 EPI list of eligible products, categorizing them under electrical and non-electrical savings. It includes items such as LED lamps, smart thermostats, air sealing products, and others, with some requiring electrician installation. Certain products were introduced in previous years with limited scope.
11.3 Participation History As presented in [Figure](#page-78-0) 36 below, EPI had 9,993 DSM participants, which represents a 2.4% increase in participation compared to 2023.[28](#page-77-2) In 2024, 150,722 efficient products were installe...
AI summary EPI (Efficient Product Installation) reported 9,993 DSM participants in 2024, a 2.4% increase from 2023. However, efficient product installations decreased by 2%, with LED lamps remaining the top product type (74% of installs). Average savings per participant fell 6.3%, and gross energy savings in 2024 were slightly lower than 2023 despite higher participation.
12 EPI Evaluation Approach The 2024 EPI evaluation comprised a comprehensive impact evaluation. The main objectives of the 2024 EPI evaluation were as follows: - › Collect information on participant perspectives - › Calculate gross and net...
AI summary The 2024 EPI evaluation aimed to collect participant perspectives, calculate energy savings and GHG emissions, and analyze market opportunities through defined research questions and methods.
Table 26: 2024 EPI Evaluation Approach Evaluation Objectives Research Questions Methodology Collect information on participant perspectives › How do participants become aware of EPI? › What is the level of satisfaction with the program com...
AI summary This section outlines the 2024 EPI Evaluation Approach, focusing on participant perspectives, gross and net results calculation, and identifying new opportunities for electrician-installed measures. The evaluation includes surveys, tracking sheet audits, site visits, and jurisdictional scans.
EUL Update The Evaluator updated the EUL values of lighting products given the rapid evolution of the lighting market. The 2024-2025 DSM MA was updated accordingly.
AI summary The Evaluator updated Effective Useful Life (EUL) values for lighting products due to rapid market changes, leading to revisions in the 2024-2025 Demand-side Management Measure Assessment (DSM MA).
14.2 Gross Savings For EPI, gross savings correspond to the change in energy consumption resulting from installing energy efficient products in participant homes regardless of why they participated.[35](#page-83-2) The Evaluator relied on...
AI summary Gross savings for EPI are calculated based on energy consumption changes from efficient product installations, using the 2024-2025 DSM MA and a 2019 adjustment ratio. EUL values for lighting products were updated, with other product EUL values sourced from the same DSM MA.
14.2.1 Installation Rates Installation rates represent the proportions of products recorded in the tracking sheet that remain installed in participant homes. During the 2024 evaluation, the Evaluator conducted 60 on-site visits to update i...
AI summary The 2024 evaluation of installation rates for EPI measures involved 60 on-site visits, with some products having unreliable rates. Thermostatic shower valves retained an 89% rate due to proximity to prior data, while smart thermostats for MSHPs had 84% due to participant disconnections. Margins of error influenced these decisions.
Table 27: EPI Product Installation Rates Product Installation Rate Applied to Gross Savings Margin of Error Reference Lighting Products LED Lamps 94% 3.0% 2024 EPI on-site visits LED Nightlights 94% 3.0% 2024 EPI on-site visits Dimmer Swit...
AI summary Table 27 provides installation rates and margins of error for various energy efficiency products under the Efficient Product Installation (EPI) program. The data includes both on-site visits and assumptions, with some products having no margin of error or based on external references like the National Renewable Energy Laboratory.
Table 28: 2024 EPI Updated Tracked and Evaluated Unitary Energy Savings EPI – Single-family Homes EPI – Apartments Product Tracked Savings [kWh/yr] Evaluated Savings [kWh/yr] Tracked Savings [kWh/yr] Evaluated Savings [kWh/yr] LED Lamps 9...
AI summary Table 28 presents the 2024 EPI updated tracked and evaluated unitary energy savings for various LED lamp replacements in single-family homes and apartments. The data includes tracked and evaluated savings in kWh/yr for different wattage replacements, with a note that EPI now offers 4.5 W G25 lamps instead of 7 W lamps.
Table 29: 2024 EPI Updated Tracked and Evaluated Unitary Peak Demand Savings Values EPI – Single-family Homes EPI – Apartments Product Tracked Savings [W/yr] Evaluated Savings [W/yr] Tracked Savings [W/yr] Evaluated Savings [W/yr] LED Lamp...
AI summary Table 29 presents the 2024 EPI updated tracked and evaluated unitary peak demand savings values for various products in single-family homes and apartments. The table details the savings for different lighting products, air sealing products, and thermostats, measured in watts per year.
14.2.5 Adjustment Ratio As part of the 2019 evaluation, the Evaluator conducted on-site visits (n = 28) to establish an overview of the types of lamps used in homes and verify that replaced A-type lamps were properly tracked. The on-site v...
AI summary The 2019 evaluation found discrepancies in tracked savings for A-type lamp replacements, leading to an adjustment ratio of 96% (±5%). In 2024, E1 introduced new product categories to track LED lamps more accurately, but no data collection was conducted to update the adjustment ratio. The 2019 ratio was reapplied due to limited tracking under new categories.
Table 30: 2024 EPI Equivalent EUL and Gross Lifetime Unitary Savings Values Product Tracked Evaluated Equivalent EUL Equivalent EUL [years] [years] Evaluated Gross Lifetime Unitary Savings [kWh] LED A19 Lamps 9 W Replacing 25 W 2.0 1.0 15....
AI summary Table 30 presents data on the Equivalent Useful Life (EUL) and Gross Lifetime Unitary Savings for various energy-efficient products under the Efficient Product Installation (EPI) program in 2024. The table includes LED lamps, motion sensors, thermostats, and other lighting products, providing insights into their energy savings and longevity.
14.2.7 Evaluated Gross Savings [Table](#page-93-0) 31 an[d Table](#page-101-0) 32 below present the annual gross savings results per product category and dwelling for the main EPI offering, including the smart thermostat for electric baseb...
AI summary The document presents annual gross savings results for the main EPI offering, including the smart thermostat for electric baseboard pilot measure. Total gross energy and peak demand savings are reported, along with the weighted average EUL value for gross electrical energy savings. Line loss factors used in the estimation are referenced from a 2014 study submitted to the NSUARB.
Table 31: Evaluated 2024 EPI Gross Electrical Energy and Peak Demand Savings per Measure - Single-family Homes LED Lamps Product Category 9 W Replacing 25 W 29 W 40 W 43 W 60 W 72 W 100 W 150 W Number of Units Number of Units 1,293 364 16,...
AI summary This table evaluates the energy and peak demand savings from the Efficient Product Installation (EPI) program in single-family homes in 2024. It details the number of units installed, energy savings, and peak demand reductions for various LED lamp wattages.
LED Lamps Product Category 18 W Replacing 100 W PAR20 7 W Replacing 50 W PAR38 15 W Replacing 90 W PAR38 15 W Replacing 120 W PAR38 15 W Replacing 150 W Number of Units Number of Units 1,031 4,260 362 98 1,286 Installation Rate (%) 94% 94%...
AI summary The table presents energy savings data for various LED lamp installations, including the number of units installed, energy savings at the meter and generator, peak demand savings, and factors such as interactive effects and line loss. The data reflects efficiency improvements from replacing traditional lamps with LED alternatives.
LED Lamps Product Category Nightlights GU10 7 W Replacing 35 W GU10 7 W Replacing 50 W G25 4.5 W Replacing 40 W E12 5 W Chandelier Replacing 40 W Number of Units Number of Units 11,093 720 3,430 3,399 11,146 Installation Rate (%) 94% 94% 9...
AI summary The document provides a detailed table outlining the energy savings and performance metrics for various LED lamp products installed in different categories. It includes data on the number of units, installation rates, energy savings, and factors affecting these savings such as interactive effects and line loss.
Thermostatic Low-flow Showerheads Product Category Faucet Aerators Shower Valves 2.5 gpm 0.5 gpm Reduction 0.75 gpm Reduction 1.0 gpm Reduction Number of Units Number of Units 3,892 329 325 183 1,995 Installation Rate (%) 92% 89% 95% 95% 9...
AI summary The table presents data on energy and peak demand savings from the installation of thermostatic faucet aerators and low-flow showerheads. It includes metrics such as the number of units installed, energy savings, effective useful life, and peak demand savings across various product categories and flow rate reductions.
Product Category Pipe Insulation (per foot) Hot Water Tank Wraps Smart Thermostats for Electric Baseboards Smart Thermostats for MSHPs Advanced Learning Thermostats for Central Electric Heating without a Heat Pump Advanced Learning Thermos...
AI summary The table presents energy savings and installation data for various energy efficiency products, including pipe insulation, hot water tank wraps, and smart thermostats, across different categories and technologies, such as MSHPs and central electric heating systems.
Consumer Electronics and Accessory Lighting Product Category Solar Security Fixtures Indoor Motion Sensors Outdoor Motion Sensors Dimmer Switches Humidity Sensors Smart Power Controllers Number of Units Number of Units 592 631 250 1,646 55...
AI summary The table presents energy savings and installation data for various consumer electronics and lighting products, including solar security fixtures, motion sensors, dimmer switches, and smart power controllers. It details the number of units installed, energy savings, and peak demand savings, along with factors like interactive effects and line loss.
Air Sealing Products – Electric Resistance Heating Product Category Foam Gaskets (per pack of 10) Door Sweeps Window Air Sealing (per 15 ft) Window Film Kits Door Weather Stripping (per 17 ft) Number of Units Number of Units 1,217 9 85 661...
AI summary The table presents data on the installation and energy savings of various energy efficiency products, including air sealing products and electric resistance heating measures. It includes metrics such as the number of units installed, energy savings, and peak demand savings, along with factors like line loss and effective useful life.
А ir Sealing Pr oducts – Heat Pump Heatir ng Total for Product Category Foam Gaskets (per pack of 10) Door Sweeps Window Air Sealing (per 15ft) Window Film Kits Door Weather Stripping (per 17 ft) Total for Single-family Homes Number of Uni...
AI summary The table presents data on energy savings and installation rates for various energy efficiency products in single-family homes, including foam gaskets, door sweeps, window air sealing, window film kits, and door weather stripping. It includes metrics such as unitary savings value, gross energy savings, effective useful life, and peak demand savings.
Table 32: Evaluated 2024 EPI Gross Electrical Energy and Peak Demand Savings per Measure – Apartments LED Lamps Product Category 9 W Replacing 25 W 29 W 40 W 43 W 60 W 72 W 100 W 150 W Number of Units Number of Units 39 13 493 16 2,799 2 5...
AI summary Table 32 evaluates the 2024 EPI Gross Electrical Energy and Peak Demand Savings per Measure in apartments, focusing on LED lamps replacing various wattage bulbs. It includes metrics like energy savings, interactive effects factors, and peak demand savings, with data on installation rates and effective useful life.
LED Lamps Product Category 18 W Replacing 100 W PAR20 7 W Replacing 50 W PAR38 15 W Replacing 90 W PAR38 15 W Replacing 120 W PAR38 15 W Replacing 150 W Number of Units Number of Units 56 35 - - - Installation Rate (%) 94% 94% 94% 94% 94%...
AI summary The document presents a table detailing energy savings from LED lamp installations across various product categories. It includes metrics such as number of units, installation rates, energy savings, and peak demand savings, along with factors like interactive effects and line loss.
LED Lamps Product Category Nightlights GU10 7 W Replacing 35 W GU10 7 W Replacing 50 W G25 4.5 W Replacing 40 W E12 5 W Chandelier Replacing 40 W Number of Units Number of Units 1,028 6 43 485 337 Installation Rate (%) 94% 94% 94% 94% 94%...
AI summary The table presents energy savings data for various LED lamp installations, including unitary savings values, interactive effects factors, and gross energy savings at both the meter and generator levels. The data includes different product categories and their respective energy and peak demand savings calculations.
Thermostatic Low-flow Showerheads Product Category Faucet Aerators Shower Valves 2.5 gpm 0.5 gpm Reduction 0.75 gpm Reduction 1.0 gpm Reduction Number of Units Number of Units 205 3 24 11 78 Installation Rate (%) 92% 89% 95% 95% 95% Number...
AI summary The table presents data on energy and peak demand savings from the installation of thermostatic faucets, aerators, and low-flow showerheads in various categories. It includes metrics such as the number of units installed, energy savings, effective useful life, and peak demand savings, with adjustments for line loss and interactive effects.
Product Category Pipe Insulation (per foot) Hot Water Tank Wraps Smart Thermostats for Electric Baseboards Smart Thermostats for MSHPs Advanced Learning Thermostats for Central Electric Heating Without a Heat Pump Advanced Learning Thermos...
AI summary The document presents a table detailing energy savings and installation data for various energy efficiency products, such as pipe insulation, hot water tank wraps, and smart thermostats for different heating systems. It includes metrics like unitary savings value, energy savings, peak demand savings, and effective useful life for each product category.
Consumer Electronics and Accessory Lighting Product Category Solar Security Fixtures Indoor Motion Sensors Outdoor Motion Sensors Dimmer Switches Humidity Sensors Smart Power Controllers Number of Units Number of Units 8 24 6 86 25 - Insta...
AI summary The table presents energy savings data for various consumer electronics and lighting products, including installation rates, unitary savings values, and energy savings at the meter and generator. It also includes factors like interactive effects and line loss for each product category.
Air Sealing Products – Electric Resistance Heating Product Category Foam Gaskets (per pack of 10) Door Sweeps Window Air Sealing (per 15 ft) Window Film Kits Door Weather Stripping (per 17 ft) Number of Units Number of Units 140 - 10 75 13...
AI summary The table presents data on energy savings from various air sealing and electric resistance heating products, including installation rates, unitary savings values, and gross energy and peak demand savings at both the meter and generator levels. It also includes factors such as line loss and effective useful life for each product category.
Air Sealing Products - Heat I Pump Heating g Product Category Foam Gaskets (per pack of 10) Door Sweeps Window Air Sealing (per 15 ft) Window Film Kits Door Weather Stripping (per 17 ft) Total for Apartments Number of Units Number of Units...
AI summary The text presents a table summarizing the installation and energy savings of various energy efficiency products in apartments, including air sealing, heat pumps, and weather stripping. It details metrics such as installation rates, energy savings, and effective useful life for each product category.
Table 33: Evaluated 2024 EPI Gross Electrical Energy and Peak Demand Savings Total for Single family Homes Total for Apartments Grand Total Number of Units Number of Units 144,145 6,577 150,722 Installation Rate (%) 91% 92% 91% Number of U...
AI summary Table 33 presents the evaluated 2024 EPI gross electrical energy and peak demand savings, including data on the number of units installed, energy savings at the meter and generator, and peak demand savings. It also includes factors like line loss and effective useful life for different housing types.
[Figure](#page-110-0) 39 below compares the tracked and evaluated gross electrical energy savings at the generator, while [Figure](#page-111-0) 40 further below compares the tracked and evaluated gross peak demand savings at the generator....
AI summary The text discusses the comparison of tracked and evaluated gross electrical energy savings and gross peak demand savings at the generator, as illustrated in Figures 39 and 40. It also mentions the calculation of GHG emission reductions using a Nova Scotia-specific factor applied to EPI gross savings results, as presented in Table 34.
Table 34: Evaluated 2024 EPI Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 9.093 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annual GHG Emissio...
AI summary This table presents the evaluated 2024 EPI gross GHG emission reductions, including energy savings and emissions factors. The data is based on Nova Scotia Power's 2023 emissions and generation data, with sources cited for accuracy.
14.3.1 Free-ridership For EPI, free-ridership occurs when participants would have installed the same energy efficient products in the absence of the program component. For low-income participants, the free-ridership level is assumed to be...
AI summary The document discusses free-ridership in EPI, noting that non-low-income participants were surveyed to assess program impact, while literature reviews informed air sealing product free-ridership levels. A 12% rate was selected for air sealing based on Massachusetts data, reflecting lower adoption likelihood without the program.
14.3.2 Participant Spillover For EPI, participant spillover occurs when participants purchase and install additional energy efficient products due to the influence of having participated in the program component without receiving any addit...
AI summary The document discusses participant spillover in the EPI program, where participants install additional energy-efficient products post-program participation without additional support. The 2024 evaluation identified LED lamps, fixtures, and heat pump water heaters as the main products driving spillover, with 17 out of 100 surveyed participants reporting such behavior.
Table 36: 2024 EPI Participant Spillover Levels Average Participant Spillover Level Margin of Error Low-income Participants All Products 0% N/A Non-low-income Participants All Products 8% 3.8% In comparison, the 8% spillover level establis...
AI summary Table 36 presents the 2024 EPI Participant Spillover Levels, showing 0% for low-income participants and 8% for non-low-income participants, with a margin of error of 3.8%. This spillover level is comparable to the 10% established in the 2021 evaluation.
Table 37: 2024 EPI Net-to-gross Ratios by Product Category Products Participant Type NTGR Proportion of Product Category Gross Savings by Participant Type Overall NTGR Values LED Lamps and Lighting Non-low-income Participants 0.92 32% Rela...
AI summary Table 37 presents the 2024 EPI net-to-gross ratios by product category, showing the effectiveness of energy efficiency programs for different participant types. It highlights the NTGR for various products, such as LED lamps, smart thermostats, and air sealing products, with varying ratios for low-income and non-low-income participants.
The detailed results per measure are presented in [Table](#page-115-0) 38 below. The net energy savings resulted in 4,225 tonnes of CO2 eq in net annual GHG emission reductions. Table 38: Evaluated 2024 EPI Net Electrical Energy and Peak D...
AI summary The document presents detailed results of energy savings from LED lamp replacements under the 2024 EPI program. It highlights net annual GHG emission reductions of 4,225 tonnes of CO2 eq and provides data on energy and peak demand savings across various product categories and wattages.
Evaluated 2024 EPI Net Electrical Energy and Peak Demand Savings per Measure (Continued) LED Lamps Product Category Nightlights GU10 7 W Replacing 35 W GU10 7 W Replacing 50 W G25 4.5 W Replacing 40 W E12 5 W Chandelier Replacing 40 W Ener...
AI summary The document presents a table evaluating the 2024 EPI (Efficient Product Installation) net electrical energy and peak demand savings per measure, including LED lamps and water-saving devices. The table includes metrics such as gross and net energy savings, NTGR (net-to-gross ratio), line loss factors, and effective useful life for various products.
Evaluated 2024 EPI Net Energy and Peak Demand Savings per Measure (Continued) Air Sealing Products – Heat Pump Heating Product Category Foam Gaskets Door Sweeps Window Air Sealing Window Film Kits Door Weather Stripping Grand Total Energy...
AI summary The document presents a continuation of the evaluated 2024 EPI net energy and peak demand savings per measure, showing results for various air sealing products. EPI fell short of its electrical energy and peak demand savings targets by 15% and 22%, respectively.
Table 39: Comparison of 2024 EPI Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Value Unit Value Value Unit Energy Savings Tracked Savings by E1 9.516 GWh 1.00 9.519 GWh 94% Evaluation...
AI summary Table 39 compares tracked and evaluated energy and peak demand savings from the 2024 Efficient Product Installation (EPI) program. Tracked savings by EfficiencyOne (E1) are compared with evaluation results, showing slight differences in gross and net savings, as well as realization rates for energy and peak demand.
n EPI or outside the category of electrician-installed measures (e.g. appliances). Globally, the scan revealed only a few measures to be considered for the EPI electrician-installed offer as follows: - › Advanced heat recovery ventilator (...
AI summary The jurisdictional scan identifies specific energy efficiency measures for EPI, including advanced HRV controls, efficient bathroom fans, block heater timers, and heat reflector panels. These measures offer energy savings through reduced runtime, improved efficiency, or heat retention, with varying applicability and installation requirements.
2024 EPI Jurisdictional Scan Highlights - › The EPI offering includes most measures found in direct install programs that have some potential for the EPI electrician-installed offer. - › Advanced heat recovery ventilator controls, bathroom...
AI summary The EPI program's electrician-installed offerings include measures like heat recovery ventilator controls and smart devices, with potential for future expansion. Tune-ups require installer certification, and studies are needed to validate energy savings for smart technologies.
16 EPI Key Findings and Recommendations As mentioned previously, the main objectives of the 2024 EPI evaluation were as follows: - › Collect information on participant perspectives - › Calculate gross and net EPI results, namely electrical...
AI summary The 2024 EPI evaluation aimed to collect participant perspectives, calculate energy and GHG savings, and analyze market opportunities. This section outlines key findings and recommendations related to these objectives.
2024 EPI-Finding: Evaluated net electrical energy and peak demand savings were respectively lower and slightly higher than the values tracked by E1. The evaluated net electrical energy savings were 6% lower than the tracked net electrical...
AI summary The 2024 EPI-Finding reports evaluated net electrical energy savings were 6% lower than E1-tracked values, while peak demand savings were 1% higher. Key factors include a 16% lower smart thermostat installation rate for MSHPs and a 4% reduction in LED lamp usage hours. The NTGR value for 2024 was slightly lower than in 2023.
17.1 Green Heat Description The Green Heat component of the Existing Residential program is aimed at encouraging the installation of energy efficient heating systems as well as heating systems for which fuel is provided from renewable reso...
AI summary The Green Heat component of the Existing Residential program encourages the installation of energy-efficient heating systems in Nova Scotia homes, offering financial incentives for high-efficiency heat pumps, biomass heating systems, solar heating systems, and demand reduction measures. Incentives were updated in February 2024 and a pilot program for three-element water heaters was discontinued in March 2024.
17.2 Follow-up on Past Evaluation Report Recommendations The Evaluator evaluated Green Heat in previous years and issued improvement recommendations[. Table](#page-128-0) 41 below provides a summary of the implementation status of past rec...
AI summary This section discusses the follow-up on past evaluation report recommendations related to the Green Heat program, summarizing the implementation status of carried-forward recommendations in Table 41.
Table 41: Implementation Status of Past Recommendations for Green Heat # Past Recommendations Status Comments 2023-GH-R1 It would be in E1's best interest to ensure that Green Heat marketing materials are available to contractors and parti...
AI summary Table 41 details the implementation status of past recommendations for Green Heat. E1 has made progress on several recommendations, including creating marketing materials, redesigning the Green Heat website, and improving communication with contractors and participants. However, some recommendations, such as offering increased incentives for low and moderate-income households, are still in progress.
18 Green Heat Evaluation Approach The 2024 Green Heat evaluation comprised a comprehensive impact evaluation. The main objectives of the evaluation were as follows: › Calculate gross and net results, namely electrical first-year and lifeti...
AI summary The 2024 Green Heat evaluation aimed to calculate gross and net results, including energy savings, peak demand savings, and avoided GHG emissions. Research questions were identified to achieve these objectives, with methods detailed in a table.
Table 42: 2024 Green Heat Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate gross results › Are the data in the tracking sheet complete, accurate, and consistent? › Which participants did not add an extensi...
AI summary This section outlines the evaluation approach for the 2024 Green Heat program, focusing on calculating gross and net results through methods such as tracking sheet audits, billing analysis, and GHG emission reduction calculations. It addresses research questions related to data accuracy, savings from mini-split heat pumps, and the evaluation of first-year and lifetime energy savings.
Measure Population Included in Billing Analysis Sample Size Sampling Margin of Error at 90% Confidence Level MSHPs 1,132 204 ±5.2% Biomass 213 36 ±12.9% Unitary Savings Review
AI summary The table presents data on the sampling margin of error for two measures: MSHPs and Biomass. The data is part of a Unitary Savings Review, which evaluates the effectiveness of energy efficiency measures.
19 Green Heat Impact Evaluation The objectives of the 2024 Green Heat impact evaluation were to determine gross and net electrical energy and peak demand savings, annually avoided GHG emissions, as well as effective useful life (EUL) value...
AI summary The 2024 Green Heat Impact Evaluation aims to assess gross and net electrical energy savings, peak demand reductions, annual GHG emission avoidance, effective useful life (EUL) values, and lifetime energy savings from the program.
19.2.1 Installation Rates Installation rates represent the proportion of measures recorded in the tracking sheet and that remains installed in participants' homes. Installation rates for all energy efficient heating systems under Green Hea...
AI summary Installation rates for Green Heat energy-efficient heating systems are estimated at 100% due to their high cost, with this assumption unchanged during the 2024-2025 DSM MA update. The rate reflects the proportion of measures installed in participants' homes.
19.2.2 Unitary Energy Savings To establish Green Heat unitary savings, the Evaluator relied on a combination of billing analyses, energy models, engineering algorithms, and literature reviews. The 2024-2025 DSM MA provides a detailed descr...
AI summary The Evaluator used billing analyses, energy models, engineering algorithms, and literature reviews to establish Green Heat unitary savings. The 2024-2025 DSM MA details inputs and calculations for measure categories, with subsections focusing on MSHP measures, wood/pellet stoves, and literature-based updates to unitary savings.
Table 44: 2024 Green Heat Tracked and Evaluated Unitary Energy Savings Measure Tracked Savings Evaluated Savings Heat Pumps MSHPs – Fully Electrically Heated 0.179 kWh/Btu/h 0.0855 kWh/Btu/h MSHPs – Mainly Electrically Heated 0.060 kWh/Btu...
AI summary Table 44 presents energy savings data for various heating measures in 2024, including heat pumps and biomass systems. It compares tracked and evaluated savings, highlighting differences in energy efficiency between different heating technologies and baselines.
19.2.3 Unitary Peak Demand Savings Peak demand savings correspond to the demand savings that coincide in time with the peak demand period of the electricity system. The projected electricity peak demand period in Nova Scotia is defined as...
AI summary The text explains how unitary peak demand savings are calculated for heating systems in Nova Scotia, noting that MSHPs showed no savings due to nil energy results, while wood/pellet stoves had adjusted savings based on billing analysis. Adjustments were made using energy savings ratios, referencing the 2024-2025 DSM MA and Econoler's 2014 report.
Table 46: Evaluated 2024 Green Heat Gross Electrical Energy and Peak Demand Savings Measure MSH IPs Fully Electrical Mainly Electrical CASHPs Air-to-water Heat Pumps Number of Units 793 162 16 1 Energy Savings Unitary Energy Savings (kWh)...
AI summary Table 46 evaluates the 2024 Green Heat program's electrical energy and peak demand savings, comparing different measures such as mini-split heat pumps, wood stoves, and pellet stoves. It provides data on energy savings, unitary savings, gross energy savings, and effective useful life for each measure.
Figure 45: 2024 Green Heat Tracked and Evaluated Gross Electrical Energy Savings at the Generator (GWh) [Figure](#page-141-1) 46 below compares tracked gross peak demand savings to evaluated gross peak demand savings at the generator. A si...
AI summary Figures 45 and 46 compare tracked and evaluated gross electrical energy and peak demand savings from Green Heat initiatives in 2024, showing lower evaluated savings for biomass and MSHPs. Table 47 outlines GHG emission reductions calculated using a Nova Scotia-specific factor applied to electrical energy savings.
Table 49: 2024 Green Heat NTGRs Measure Free-ridership NTGR MSHPs 48% 0.52 Biomass and Solar Measures 47% 0.53 Demand Reduction Measures 9% 0.91 CASHPs and AWHPs 33% 0.67 19.3.3 Evaluated Net Savings
AI summary Table 49 presents the 2024 Green Heat NTGRs for various measures, including MSHPs, Biomass and Solar Measures, Demand Reduction Measures, and CASHPs and AWHPs. The table shows free-ridership percentages and corresponding NTGR values for each measure. Section 19.3.3 discusses the evaluated net savings related to these measures.
Table 50: Evaluated 2024 Green Heat Net Electrical Energy and Peak Demand Savings MSHPs Measure Fully Electrical Mainly Electrical CASHPs AWHPs Energy Savings Gross Energy Savings – at the Meter (GWh) 1.174 - 0.056 0.007 NTGR 0.52 0.52 0.6...
AI summary Table 50 evaluates the 2024 Green Heat Net Electrical Energy and Peak Demand Savings, comparing various heating measures such as MSHPs, CASHPs, AWHPs, and wood and pellet stoves. The table includes gross and net energy savings at the meter and generator, as well as peak demand savings and line loss factors for each measure.
19.4 Realization Rate [Table](#page-147-1) 51 below compares the energy and peak demand savings established through the 2024 evaluation to those calculated in the 2024 tracking sheet. It also includes the realization rate, representing the...
AI summary This section discusses the realization rate, comparing energy and peak demand savings from the 2024 evaluation to those in the 2024 tracking sheet, and includes the ratio of evaluated net savings to tracked net savings.
Table 51: Comparison of 2024 Green Heat Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Value Unit Value Unit Rate Energy Savings Tracked Savings by E1 4.711 GWh 0.53 2.478 GWh Evaluation Results 1...
AI summary Table 51 compares the tracked and evaluated energy and peak demand savings from the 2024 Green Heat program. It shows that energy savings were 4.711 GWh tracked and 1.651 GWh evaluated, with a realization rate of 35%. Peak demand savings were 3.915 MW tracked and 2.748 MW evaluated, with a realization rate of 71%.
21.2 Follow-up on Past Evaluation Report Recommendations The Evaluator evaluated HEA in previous years and issued improvement recommendations. [Table](#page-150-0) 52 below provides a summary of the implementation status of past recommenda...
AI summary The Evaluator reviewed past recommendations related to the Home Energy Assessment (HEA) and noted that all remaining recommendations were completed in 2024. A table summarizes the implementation status of these recommendations.
22 HEA Evaluation Approach The 2024 HEA evaluation comprised a comprehensive impact evaluation. The main objectives of the 2024 HEA evaluation were to: › Calculate gross and net results, namely electrical first-year and lifetime energy sav...
AI summary The 2024 HEA evaluation aimed to calculate gross and net results, including energy savings, peak demand savings, and avoided GHG emissions. The evaluation involved research questions, methods, and sample sizes outlined in Table 53.
Site Visits A total of 19 site visits were completed by EAs among surveyed expired participants who declared not having completed a final home energy assessment but still had some recommended measures installed. The site visits consisted o...
AI summary Nineteen site visits were conducted by Energy Auditors (EAs) for expired participants who had not completed final home energy assessments but had installed some recommended measures. The visits aimed to perform final assessments, confirm installations, and calculate energy simulation results using HOT2000.
Calculations Using Evaluation Results Building on all the above methods and collected data, the Evaluator calculated the first-year and lifetime electrical energy and peak demand savings as per the calculation methodology presented in Sect...
AI summary The Evaluator calculated first-year and lifetime electrical energy and peak demand savings using a methodology outlined in Section 23. These calculations build on prior data collection and evaluation methods to quantify program impacts.
GHG Emission Reduction Calculations To obtain net avoided GHG emissions in CO2 eq for HEA, the Evaluator multiplied the net energy savings by the latest Nova Scotia-specific factor for GHG emissions generated by electricity production. Thi...
AI summary The Evaluator calculated net avoided GHG emissions by multiplying energy savings from Home Energy Assessments (HEA) by a Nova Scotia-specific factor derived from Nova Scotia Power (NS Power) data.
23 HEA Impact Evaluation The objectives of the 2024 HEA impact evaluation were to determine gross and net electrical energy and peak demand savings, annually avoided GHG emissions, as well as EUL values and associated lifetime energy savin...
AI summary The 2024 HEA impact evaluation aimed to assess gross and net electrical energy savings, peak demand reductions, annual GHG emissions avoided, and Effective Useful Life (EUL) values with associated lifetime energy savings from Home Energy Assessments.
23.1 Tracking Sheet Audit To ensure program component results were reliably compiled, the Evaluator first performed a tracking sheet audit aimed at verifying the completeness and consistency of the data submitted by E1. The verification an...
AI summary The Evaluator conducted a tracking sheet audit to verify the completeness and consistency of data submitted by E1. The audit revealed the complexity of the HEA tracking sheet, prompting the development of a new savings calculation approach. Transitioning to E1's Customer Information System (CIS) is expected to simplify data tracking, particularly for heat pump parameters, by enabling automated validation against NEEP's specifications.
23.2 Gross Savings For HEA, gross savings correspond to the change in energy consumption resulting from measures implemented by HEA participants regardless of their reasons for participating.[59](#page-156-1) The following subsections desc...
AI summary Gross savings for HEA (Home Energy Assessment) represent energy consumption changes from implemented measures, regardless of participation reasons. The methodology for calculating these savings is detailed in subsequent subsections.
23.2.2 Energy Savings HEA energy savings are calculated based on HOT2000 simulation results adjusted with billing analysis results and unitary savings values for prescriptive measures, as shown in the equation below. (ℎ) = ( (ℎ) − (ℎ) − (ℎ...
AI summary HEA energy savings are calculated using HOT2000 simulation results adjusted by billing analysis and prescriptive measure unitary savings values, as represented in the provided equation.
Where: - › and correspond to the modelled electrical energy consumption levels respectively obtained in HOT2000 during the D and E assessments. - › (ℎ) correspond to the unitary savings value established for heat pump water heaters (HPWHs)...
AI summary The text explains how adjustment ratios (ARs) are calculated using billing analysis from HOT2000 and HEA data. ARs adjust savings based on differences between modeled electrical energy consumption during D and E assessments, varying by space heating system scenarios. Unitary savings values for HPWHs and prescriptive measures are also referenced.
For some measures installed under HEA, instead of using a performance approach based on energy simulation results, energy savings are calculated using a prescriptive approach based on unitary energy savings values. This is the case for: -...
AI summary The document explains how energy savings for certain measures installed under HEA are calculated using a prescriptive approach based on unitary energy savings values rather than performance-based simulations. This applies to wood burning equipment, smart thermostats, solar PV systems, and HPWHs. The approach for HPWHs is adjusted to avoid double counting and facilitate future savings accounting.
Table 55: 2024 HEA Tracked and Evaluated Unitary Energy Savings for Prescriptive Measures Measure Tracked Savings [kWh/year] Evaluated Savings [kWh/year] Wood Stoves or Fireplace Inserts with Electric Resistance Baseline 10,443 1,461 Wood...
AI summary Table 55 presents evaluated energy savings for wood and pellet stoves and fireplace inserts under the Home Energy Assessment (HEA) program. Due to limitations in tracking separate savings for these measures, a unitary energy savings value was applied. The Evaluator recommends removing fireplace inserts from future offers due to low savings.
Reporting Requirements HEA incentives originate from three sources of funding: Nova Scotia Power ratepayers for DSM, the Province of Nova Scotia, and the Government of Canada (CGH Grant). The incorporation of the CGH Grant, as a cofunder o...
AI summary HEA incentives are funded by Nova Scotia Power ratepayers, the Province of Nova Scotia, and the Canadian government (CGH Grant). Savings are reported to NSUARB and the Province via separate evaluations, focusing on electrical savings (DSM) and participation/GHG reductions (government). Equations prevent double-counting, and solar PV savings are included in DSM reports regardless of heating source.
23.2.3 Peak Demand Savings Peak demand savings correspond to the demand savings that coincide in time with the peak demand period of the electricity system. The projected electricity demand peak period in Nova Scotia is defined as the cold...
AI summary Peak demand savings in Nova Scotia are defined as demand reductions during the coldest days (−15°C) between 5 p.m. and 7 p.m. in December to February. Calculation methods differ for measures modeled in HOT2000 and prescriptive approaches within Home Energy Assessments (HEA).
Table 57: 2024 HEA Tracked and Evaluated Unitary Peak Demand Savings for Prescriptive Measures Measure Tracked Savings [W] Evaluated Savings [W] Wood or pellet stoves or fireplace inserts with electric resistance or heat pump baseline 4,00...
AI summary Table 57 presents tracked and evaluated unitary peak demand savings for prescriptive measures under the 2024 Home Energy Assessment (HEA). The table includes data for wood or pellet stoves and fireplace inserts with electric resistance or heat pump baselines, showing tracked savings of 4,000 W and evaluated savings of 828 W.
23.2.4 Supplemental File Adjustments Supplemental files refer to participants that have multiple files (or lines) in the tracking sheet. Supplemental files occur for multiple reasons that may or may not result in incremental energy savings...
AI summary Supplemental files in energy efficiency programs may arise from administrative issues or home remodeling, impacting energy savings. E1 analyzed 2024 adjustments, identifying incremental savings from updated files. The Evaluator deems E1's approach thorough, yielding positive adjustments to gross savings, as shown in Table 58.
23.2.5 Interactive Effects In a home, interactive effects occur when the implementation of energy efficiency measures has an impact on the energy consumption of other elements such as heating and cooling. Since the vast majority of HEA mea...
AI summary The text explains that interactive effects in energy efficiency measures, such as those in HEA, are already accounted for through simulations. Wood burning equipment and solar PV systems are specifically noted as not requiring additional considerations for interactive effects.
Table 60: Evaluated 2024 HEA Gross Energy and Peak Demand Savings Measure Category HOT2000 Modelled Measures Wood Burning Equipment HPWHs Electrical Thermal Storage Energy Efficiency Measure Subtotal Solar PV Measures Total Number of Parti...
AI summary Table 60 presents evaluated 2024 Home Energy Assessment (HEA) gross energy and peak demand savings, including data on the number of participants, installed capacity, energy savings with and without adjustment ratios, and peak demand savings across various measures and technologies.
\ \ The number of participants who install measures modelled in HOT2000 and the number of prescriptive measures are not mutually exclusive. Number of participants for Solar PV measures corresponds to the number of participants who generate...
AI summary The text discusses GHG emission reductions calculated using Nova Scotia-specific factors applied to HEA net savings, noting that the number of participants in HOT2000 and prescriptive measures are not mutually exclusive. It also mentions variations in unitary savings for wood burning equipment and HPWHs based on equipment type and baseline.
Table 62: 2024 HEA Free-ridership Levels Measure Average Free-ridership Level Sample Size Population Size Margin of Error Energy Efficiency Measures 17% 77 3,995 4.20% Solar PV Measures 26% 29 1,520 6.50% 61 At the time of writing, 2023 da...
AI summary Table 62 presents free-ridership levels for energy efficiency and solar PV measures in 2024 HEA. The data shows 17% free-ridership for energy efficiency measures and 26% for solar PV measures. The Nova Scotia-specific factor was derived from Nova Scotia Power's 2022 emissions and electricity generation data.
23.3.2 Participant Spillover For HEA, participant spillover occurs when participants implement additional measures recommended in their initial energy assessments after their participation in the program component, that is after having com...
AI summary Participant spillover in the Home Energy Assessment (HEA) program occurs when participants implement additional energy efficiency measures after completing their initial assessments, without receiving further support from the program. The 2023 spillover level was reused in the 2024 evaluation due to a lack of updated data collection.
Table 64: 2024 HEA NTGR Values Measure Free-ridership Participant Spillover NTGR Energy Efficiency Measures 17% 0.84 Solar PV Measures 26% 1% 0.75 23.3.4 Unconverted Assessment Spillover
AI summary Table 64 provides 2024 HEA NTGR values for Energy Efficiency Measures and Solar PV Measures, showing free-ridership and participant spillover rates. Section 23.3.4 discusses unconverted assessment spillover, which likely relates to the impact of these measures on broader energy efficiency outcomes.
The unconverted D assessment savings spillover effect corresponds to the savings associated with those measures implemented by electrical participants who did not complete an E assessment by the end of the allocated 12-month period (referr...
AI summary The analysis examines the unconverted D assessment savings spillover effect, focusing on expired participants who did not complete an E assessment within the allocated 12-month period. The Evaluator conducted surveys and site visits to reassess savings parameters, finding that 54% of expired participants implemented at least one upgrade. Average savings were calculated as 2,097 kWh using a new methodology, compared to a tracked value of 2,283 kWh.
23.3.5 Savings Deductions for Participation in Other Residential Programs Several measures are offered under both HEA and Green Heat. In addition, Efficient Product Installation (EPI) introduced air sealing measures in 2019, and Solar Home...
AI summary To avoid double-counting energy savings, net electrical savings from Green Heat or EPI are deducted from HEA savings for overlapping participants. E1 developed a tool to identify overlaps using customer information fields, which helps reduce duplication in energy savings claims.
Table 67: 2024 Savings Overlap to Deduct from HEA Overlap Net Energy Savings at Generator (GWh) Net Peak Demand Savings at Generator (MW) Overlap with Green Heat (0.013) (0.007) Overlap with EPI (0.051) (0.009) Total (0.064) (0.017) 23.3.6...
AI summary Table 67 shows the overlap of energy savings from various programs, including Green Heat and EPI, which are being deducted from the Home Energy Assessment (HEA). The net energy savings and peak demand savings are negative, indicating overlaps that need to be accounted for in the evaluation of net savings.
Table 68: Evaluated 2024 HEA Net Energy and Peak Demand Savings Energy Efficiency Measures Solar PV Measures Total Energy Savings Gross Energy Savings – at the Meter (GWh) 9.409 26.202 35.611 Unconverted D Assessment Spillover Energy Savin...
AI summary Table 68 outlines the evaluated 2024 HEA (Home Energy Assessment) net energy and peak demand savings, showing that HEA exceeded its energy and peak demand savings targets by 68% and 81%, respectively. The table includes metrics such as gross energy savings, net energy savings with deductions, and effective useful life of measures.
24 HEA Key Findings and Recommendations As mentioned previously, the main objectives of the 2024 HEA evaluation were as follows: › Calculate gross and net results, namely electrical first-year and lifetime energy savings, peak demand savin...
AI summary The 2024 HEA evaluation found that net electrical energy and demand savings exceeded targets, with participation reaching a historic high due to the CGH Grant. Solar PV measures contributed significantly to savings, but future participation may decline post-CGH Grant closure. Energy savings tracked by E1 were lower than evaluation results, prompting adjustments. A recommendation to remove wood/pellet fireplace inserts from HEA is proposed due to low savings.
25.1 MHEEP Description MHEEP provides energy efficiency upgrades to homes in Mi'kmaw communities at no cost to participants or communities. E1 works with community housing managers (HMs), two delivery agents (DAs), and Mi'kmawpreferred con...
AI summary The Mi'kmaw Home Energy Efficiency Project (MHEEP) delivers free energy efficiency upgrades to Mi'kmaw communities in Nova Scotia through E1, community housing managers, and delivery agents. It includes home assessments, building envelope upgrades, appliance replacements, and moisture management measures. Funding comes from Electricity ratepayer DSM funding and Province of Nova Scotia (PNS) funds, with goals of achieving 0.618 GWh in electrical savings and 0.167 MW in peak demand reduction by 2024.
26 MHEEP Evaluation Approach The 2024 MHEEP evaluation comprised a condensed impact evaluation. The main objectives of the 2024 MHEEP evaluation were as follows: › Calculate gross and net MHEEP results, namely electrical first-year and lif...
AI summary The 2024 MHEEP evaluation focused on calculating gross and net results, including energy savings, peak demand savings, and avoided GHG emissions. The evaluation objectives are outlined in a table and mapped to research questions and methods.
Table 70: 2024 MHEEP Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate gross results › Are the data in the tracking sheet complete, accurate, and consistent? › What are the savings for heating and building...
AI summary The document outlines the evaluation approach for the 2024 MHEEP (Mi'kmaw Home Energy Efficiency Project), focusing on calculating gross and net results through data audits, unitary savings reviews, effective useful life updates, and GHG emission reduction calculations.
27.2 Gross Savings MHEEP gross savings correspond to the change in energy consumption resulting from the measures implemented by participants regardless of why they participated.[64](#page-177-0) In 2024, MHEEP participants received buildi...
AI summary MHEEP gross savings are calculated based on energy consumption changes from implemented measures, including building envelope and heating upgrades. Non-modeled measures use unitary savings values. Methodologies are detailed in subsections, referencing NREL's Uniform Methods Project for net savings estimation.
Where: - › and correspond to the modelled energy consumption levels respectively obtained in HOT2000 during the pre-retrofit (D) and post-retrofit (E) assessments. When modelled energy consumption levels were not available, the participant...
AI summary The text outlines methods for calculating energy savings using HOT2000 and EnerGuide ratings, unitary savings values for HPWHs and DWHRs, adjustment ratios (ARs) derived from billing analyses, and prescriptive measure calculations from MHEEP. ARs vary by heating system scenarios and are based on 2024 HEA evaluations.
Table 71: 2024 MHEEP Adjustment Ratios Scenario Tracked Evaluated ORD Assessment ORE Assessment AR A participant who registered with a heat pump 0% (1.00) 0% (1.00) 1.24 A participant who registered without a heat pump and who did not inst...
AI summary Table 71 outlines adjustment ratios for the Mi'kmaw Home Energy Efficiency Project (MHEEP) in 2024, showing different scenarios based on heat pump registration and installation. Participants with non-electrical space heating can generate both electrical and non-electrical savings, with electrical savings calculated using total energy consumption and the proportion of electrical heating systems during the D assessment.
Non-modelled Measures Replaced appliances as well as programmable and smart thermostats are not modelled in HOT2000. Instead, resulting energy savings are calculated based on unitary energy savings values from the 2024-2025 DSM MA. That do...
AI summary Non-modelled measures such as replaced appliances and thermostats are not included in HOT2000. Energy savings for these measures are calculated using unitary values from the 2024-2025 DSM MA. For HPWHs and DWHRs, savings are adjusted using an AR before being added as prescriptive measures. This approach accounts for low installation rates and supports future savings tracking.
Table 72: Tracked and Evaluated 2024 MHEEP Unitary Energy Savings Measure Tracked Savings [kWh/year] Evaluated Savings [kWh/year] Smart Thermostats with Electric Resistance Baseline 348 312 Smart Thermostats with Heat Pump Baseline 514 564...
AI summary Table 72 presents tracked and evaluated energy savings for the Mi'kmaw Home Energy Efficiency Project (MHEEP) in 2024, comparing actual and estimated energy savings for various energy efficiency measures, including smart thermostats and appliance replacements.
27.2.2 Peak Demand Savings Peak demand savings correspond to the demand savings that coincide in time with the peak demand period of the electricity system. The projected electricity peak demand period in Nova Scotia is between 5 p.m. and...
AI summary Peak demand savings in Nova Scotia are calculated using a 0.283 MW/GWh ratio from Navigant's 2016-2018 DSM Plan, except for heat pumps, which use updated 2024 unitary values (0.148 W/(Btu/hr)). The Evaluator validated Navigant's method, while MHEEP's savings are tracked via appliance replacements and updated in the 2024-2025 DSM MA.
27.2.3 Interactive Effects In a home, interactive effects occur when the implementation of energy efficiency measures has an impact on the energy consumption of other elements such as heating and cooling. The interactive effects of the spa...
AI summary Interactive effects in energy efficiency measures, such as those modeled in HOT2000, are considered in savings calculations. However, for the 2024 evaluation, certain measures like programmable thermostats and drain water heat recovery systems, as per the 2024-2025 Measure Assessment, do not impact other elements' energy consumption.
27.2.4 Effective Useful Life As part of the 2024-2025 DSM MA activities, the Evaluator reviewed the EUL values used in the calculation of electrical energy savings that are expected to persist over time. The EUL values for building envelop...
AI summary The Evaluator reviewed Effective Useful Life (EUL) values for building envelope upgrades and space heating equipment as part of the 2024-2025 DSM MA update. EUL values were not revised for most measure categories, except for heat pump water heaters and modelled measures, as reflected in Table 74.
Table 74: Tracked and Evaluated 2024 MHEEP Equivalent EUL Values Measure Tracked Equivalent EUL [years] Evaluated Equivalent EUL [years] Heat Pump Water Heaters 10 15 Building Envelope (Modelled) 20.8 20.5 Space Heating Equipment (Modelled...
AI summary Table 74 presents the tracked and evaluated Equivalent Useful Life (EUL) values for various energy efficiency measures under the Mi'kmaw Home Energy Efficiency Project (MHEEP) in 2024, including Heat Pump Water Heaters and modeled building envelope and space heating equipment. The section also mentions 'Evaluated Gross Savings' in 27.2.5.
The modelled and non-modelled measure annual gross savings at the meter are presented in [Table](#page-181-1) 75 and [Table](#page-182-0) 76 below respectively. [Table](#page-183-0) 77 further below combines the savings of all MHEEP measur...
AI summary The text discusses the presentation of annual gross savings for modelled and non-modelled measures under the MHEEP program, with specific tables referenced for detailed data on energy and peak demand savings.
Number of Participants 192 Energy Savings Gross Energy Savings Without Adjustment Ratio (AR) – at the Meter (GWh) Gross Energy Savings with AR – at the Meter (GWh) 0.632 0.361 Effective Useful Life (years) 20.5 Gross Lifetime Energy Saving...
AI summary The document presents energy savings data from the MHEEP Non-modelled Measure for 2024, including gross energy and peak demand savings from appliance replacements and drain water heat recovery systems. The data includes metrics such as effective useful life, unitary energy savings, and gross lifetime energy savings.
Table 77: Evaluated 2024 MHEEP Gross Energy and Peak Demand Savings Measure Category Modelled Non-modelled Total Energy Savings Gross Energy Savings – at the Meter (GWh) 0.361 0.005 0.366 Line Loss Factor 1.0947 1.0947 - Gross Energy Savin...
AI summary Table 77 evaluates the 2024 MHEEP Gross Energy and Peak Demand Savings, showing modelled and non-modelled energy and peak demand savings at both the meter and generator levels. The table includes metrics such as Effective Useful Life and Line Loss Factor, with footnotes explaining the calculation of non-modelled measure lifetimes.
Table 78: Evaluated 2024 MHEEP Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 0.401 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annual GHG Emiss...
AI summary Table 78 evaluates the 2024 MHEEP Gross GHG Emission Reductions, showing 0.401 GWh of energy savings, a 472.2 tonnes of CO2 eq/GWh emissions factor, and 189 tonnes of CO2 eq annual emission reductions.
27.3.1 Evaluated Net Savings Net savings are defined as the energy savings specifically attributable to MHEEP. Since spillover and freeridership effects were considered nil, the net MHEEP impacts are equal to the gross savings generated by...
AI summary The MHEEP program achieved net energy savings of 0.401 GWh and peak demand savings of 0.481 MW, with no spillover or free-rider effects. It missed its energy target by 35% but exceeded peak demand savings by 189% as shown in Figure 55.
Gross Savings NTGR Net Savings Realization Rate Value Unit Value Unit Energy Savings Tracked Savings by E1 0.578 GWh 1.00 0.578 GWh Evaluation Results 0.401 GWh 1.00 0.401 GWh 69% Peak Demand Savings Tracked Savings by E1 0.420 MW 1.00 0.4...
AI summary This table compares tracked and evaluated energy and peak demand savings from the Mi'kmaw Home Energy Efficiency Project (MHEEP) in 2024. Tracked savings by E1 are compared to evaluation results, showing a realization rate of 69% for energy savings and 115% for peak demand savings.
28 MHEEP Key Findings and Recommendations As mentioned previously, the main objectives of the 2024 MHEEP evaluation were as follows: › Calculate gross and net MHEEP results, namely electrical first-year and lifetime energy savings, peak de...
AI summary The 2024 MHEEP evaluation found that net electrical energy savings fell short of targets (65% achieved vs. 95% in 2023), while peak demand savings exceeded targets. Higher participation (19% increase) was offset by a 41% drop in average savings per participant due to updated adjustment ratios. Evaluated savings were 31% lower and 15% higher than E1's initial tracking for energy and peak demand, respectively.
29.1 Description The Residential Behaviour program component, publicly branded as Efficiency Insights, is designed to help Nova Scotia Power (NS Power) residential customers reduce their electricity consumption. The component provides a su...
AI summary The Residential Behaviour program, branded as Efficiency Insights, helps NS Power customers reduce electricity use via personalized Home Energy Reports (HERs) and behavior tips. E1, using Bidgely's algorithms, integrates HERs into NS Power's MyEnergy Insights platform. Energy Solutions Advisors (ESAs) assist customers, and savings are evaluated annually through billing analysis. Funded under E1's 2023-2025 DSM Plan, the program launched in May 2024 with four reports issued in 2024.
Table 81: 2024 Residential Behaviour Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate net results › What are the evaluated first-year net electrical energy savings? › Are the participation levels in other...
AI summary Table 81 outlines the 2024 Residential Behaviour Evaluation Approach, focusing on calculating net results through billing analysis, participation analysis in other E1 programs, and GHG emission reduction calculations.
31.2 Net Savings For Residential Behaviour, savings correspond to the change in electricity consumption resulting from behaviours adopted by treatment group participants compared with the change in electricity consumption observed among co...
AI summary Net savings for residential behavior programs are calculated by comparing electricity consumption changes between treatment and control groups, ensuring savings directly attribute to the program. The Uniform Methods Project (UMP) defines net savings as the difference in energy consumption with and without the program, excluding control group changes. No additional freeridership adjustments are needed, but overlap with other ENS programs must be considered.
31.2.1 Treatment and Control Group Selection and Equivalency Check To yield accurate and unbiased results when calculating savings under a RCT approach, the treatment and control groups must be selected properly so that the two groups are...
AI summary The document discusses the selection and equivalency check of treatment and control groups in a randomized controlled trial (RCT) approach for residential behavior programs. The Evaluator ensured groups were randomly selected and statistically equivalent by analyzing energy consumption data and geographical locations before program launch.
31.2.3 Energy Savings The model used to calculate savings for Residential Behaviour is the difference-in-difference (DiD). The DiD serves to compare the average change in electricity consumption in the treatment group prior to and during p...
AI summary The Residential Behaviour program uses a difference-in-difference (DiD) model to calculate energy savings, comparing treatment and control groups across preprogram (May 2023–April 2024) and post-program (May–December 2024) periods. Monthly savings trends are analyzed, but cumulative savings are reported officially due to statistical insignificance in some monthly results.
Cumulative Savings The DiD model serves to compare the difference in the average daily consumption between the treatment group and the control group before and after program participation. The cumulative approach uses the average daily con...
AI summary The document explains the use of a Difference-in-difference (DiD) model to evaluate cumulative savings by comparing average daily consumption between treatment and control groups. It also outlines the cumulative approach equation for calculating total savings across the entire period, with monthly savings details in Appendix XXXVI.
Where: - › _ℎ = The control group's average daily consumption over the given post-program year - › _ℎ = The treatment group's average daily consumption over the given post-program year - › _ℎ = The control group's average daily consumption...
AI summary The document discusses adjustments made to the cumulative savings approach for calculating annual electrical savings, taking into account varying numbers of participating households with AMI data. Table 84 presents the 2024 electrical savings values established using this method.
31.2.5 Interactive Effects Interactive effects occur when the implementation of energy efficiency measures has an impact on the energy consumption of other elements such as heating and cooling. For Residential Behaviour, interactive effect...
AI summary Interactive effects occur when energy efficiency measures impact other energy-consuming systems like heating and cooling. For residential behavior, these effects are already factored into savings calculations through whole-house energy consumption data analysis.
31.2.7 Savings Deductions for Participation in Other Residential Programs As mentioned in Subsection [29.1](#page-186-1) above, a secondary aim of Residential Behaviour is to encourage customers to engage with other ENS programs tailored t...
AI summary The Residential Behaviour program aims to encourage participation in other ENS programs. Savings deductions are calculated if treatment groups show higher participation in EPI and Green Heat programs. Statistically significant differences were found in participation levels for high and medium users in Green Heat and EPI, requiring savings deductions for those waves.
Table 85: Other 2024 Program Participation Levels Program Treatment Participation Level Control Participation Level Difference (%) Is the Difference Statistically Significant? Wave 1 – High users HEA 1.6% 1.7% -0.1% No Green Heat 0.4% 0.3%...
AI summary Table 85 shows participation levels for various energy efficiency programs in 2024, comparing treatment and control groups across different user categories. The data indicates that some programs show statistically significant differences in participation, while others do not.
2024 Residential Behaviour-Finding: Residential Behaviour fell short of its net electrical energy savings targets. Residential Behaviour achieved 6.270 GWh in net electrical energy savings in 2024, thus falling short of the planned net ele...
AI summary Residential Behaviour program underperformed in 2024, achieving 6.270 GWh vs target 8.000 GWh, but shows potential as it scales. Control and treatment groups were similar, and treatment group had higher participation in other programs.
CONCLUSION Table 87 presents the participation levels, net-to-gross ratios (NTGRs), evaluated gross and net savings at the generator, annual greenhouse gas (GHG) emission reductions, as well effective useful life (EUL) values for each prog...
AI summary Table 87 outlines participation levels, net-to-gross ratios, evaluated savings, annual GHG emission reductions, and effective useful life values for various program components and the Existing Residential category.
Table 87: Overall 2024 Existing Residential Participation and Evaluated Savings Particip ation Level Gross Savings NTGR Net S Savings Value Unit Value Unit Value Value Unit AMH • Energy Savings 83 Projects 1.159 GWh 1.00 1.159 GWh Lifetime...
AI summary Table 87 presents data on residential participation and evaluated savings for 2024, including energy savings, GHG emission reductions, and EUL for various programs like AMH, ASFH, EPI, Green Heat, HEA, MHEEP, and Residential Behaviour. The table also includes net savings ratios (NTGR) for each program component.
Home Energy Assessment Appendix XXVI: HEA Past Participant Survey Questionnaire Appendix XXVII: HEA Past Participant Survey Results Appendix XXVIII: HEA Expired Participant Survey Questionnaire Appendix XXIX: HEA Expired Participant Survey...
AI summary The document outlines appendices related to the Home Energy Assessment (HEA) program, including past and expired participant surveys, audit tracking sheets, billing analysis methodologies, reporting requirements, and 2024 recommendations. These appendices focus on program evaluation, performance monitoring, and participant engagement metrics.
EfficiencyOne
AI summary The document text consists solely of the heading 'EfficiencyOne' from a Nova Scotia regulatory proceeding, with no further content or context provided in the chunk.
2024 DSM EVALUATION March 25, 2025 In Collaboration with:
AI summary The 2024 Demand-Side Management (DSM) evaluation by Nova Scotia Power outlines program performance and outcomes, with collaboration noted in the document. Key focus areas include energy efficiency initiatives, program effectiveness, and regulatory compliance.
Table 1: 2024 AMH Corrected Tracked Savings Value Tracked by E1 Corrected Tracked Value Relative Difference Program Component Results Value Unit Value Unit Value AMH Gross Electrical Energy Savings at the Generator 1.132 GWh 1.158 GWh 2.30...
AI summary Table 1 shows the 2024 AMH Corrected Tracked Savings, highlighting differences between tracked and corrected values due to an incorrect line loss factor used by E1 for residential participants. The relative difference in gross electrical energy savings is 2.30%, while peak demand savings remain unchanged.
APPENDIX II AMH Energy Auditor Interview Guide
AI summary This document is an interview guide for energy auditors in the Affordable Multifamily Housing (AMH) program, part of a Nova Scotia regulatory proceeding. It outlines procedures for assessing energy efficiency in multifamily housing, aligning with broader demand-side management (DSM) and energy efficiency initiatives.
C. Participants' Questions - C1. What concerns about the program, if any, do participants typically have at the time of scheduling the energy audit with you? [OPEN END] - C2. What concerns about the program, if any, do participants typical...
AI summary The document outlines participant concerns during energy audits, focusing on questions about recommended technologies like heat pumps, insulation, and hybrid systems. It seeks insights into common participant queries and barriers to program engagement.
E. Satisfaction - E1. On a scale of 0 to 10, where 0 is "Not at all satisfied" and 10 is "Completely satisfied," how satisfied are you with each of the following ten aspects of the Affordable Multifamily Housing program? [DO NOT RANDOMIZE]...
AI summary The text outlines a satisfaction survey for the Affordable Multifamily Housing program, evaluating aspects like information provision, audit processes, software tools, and communication with Efficiency Nova Scotia, including open-ended feedback opportunities.
Table 1: Overview of Data Collection Activity Descriptor This Instrument Instrument Type Telephone interviews Estimated Time to Complete 15-20 minutes Target Audience Dropped-out and non-participants Expected Number of Completions n=6 drop...
AI summary The document outlines a data collection plan involving telephone interviews targeting dropped-out and non-participants in a program. It aims to understand motivations, barriers, and perceptions of the affordability covenant. The research will be conducted by Narrative Research, with results to be adapted by Econoler.
Introduction Could I speak with ? - 1. Yes [CONTINUE] - 2. No [SAY "PERHAPS YOU CAN HELP ME ANYWAY." CONTINUE] Hello, my name is ____________________ and I'm calling from Narrative Research, a Halifax based market research company, on beha...
AI summary Narrative Research, on behalf of Efficiency Nova Scotia, conducts a survey to evaluate energy efficiency services, targeting participants who dropped out or didn't join the Affordable Multifamily Housing Program. The call aims to understand reasons for non-participation and improve service quality.
C7. [ASK IF CODE 2 AT C5 OR C6] What would be an acceptable term length in your opinion? [SINGLE RESPONSE.] PRESCRIPTIVE PATH ACCEPTABLE TERM: years COMPREHENSIVE PATH ACCEPTABLE TERM: years 98. 99. (Don't know) (Refusal) D. Alternatives f...
AI summary The text presents a series of questions related to energy efficiency programs, including acceptable term lengths for programs, participation in other energy efficiency initiatives, and energy efficiency upgrades implemented in the past year. The questions are part of a survey or data collection process.
E. Suggested Improvements - E1. What could Efficiency Nova Scotia do to improve the Affordable Multifamily Housing Program? [OPEN END] - E2. How helpful would the following tools or support be to the program? [READ AND RANDOMIZE. ASK FOR E...
AI summary Efficiency Nova Scotia seeks input on improving the Affordable Multifamily Housing Program, including tools like case studies, contractor assistance, and low-interest financing, as well as preferred communication methods for rebate information.
Table 1: Protocol Used for Project Reviews Project ID Facility Address Project Contact Name Project Contact Phone Number Project Contact Email Measure Count 1 2 Total Measure Description Energy Savings Methodology Used for Calculating Savi...
AI summary The document outlines a protocol for project reviews, focusing on verifying energy savings calculations, ensuring proper modeling and calibration of buildings, and assessing discrepancies between claimed savings and documentation. It also includes a section on recommendations for Affordable Multifamily Housing (AMH) in 2024.
A1. How did you become aware of Efficiency Nova Scotia's HomeWarming program? Anything else? Overall Measure Category % Modelled% Heat Pump% Sample Size (#) 52 22 30 Word of mouth/friends/family 37% 36% 37% Online – general 31% 23% 37% Soc...
AI summary The text discusses how participants became aware of Efficiency Nova Scotia's HomeWarming program through various channels such as word of mouth, online sources, and social media. It also outlines the main reasons participants were interested in the program, primarily to save on energy costs.
- a. [IF MEASURE CATEGORY = MODELLED] I learned about my home's energy usage during the initial Home Energy assessment Overall Measure Category % Modelled% Heat Pump% Sample Size (#) 22 22 0 10 - Completely agree 36% 36% 0% 9 9% 9% 0% 8 27...
AI summary The text presents survey results regarding customer satisfaction with home energy assessments. Respondents rated their agreement with learning about their home's energy usage during the initial assessment, with mean scores of 7.5 for the overall category and 8.5 for the Modelled category. No responses were recorded for the Heat Pump category.
- a. My home is more comfortable because of the energy efficient upgrades I received Overall Measure Category % Modelled% Heat Pump% Sample Size (#) 52 22 30 10 - Completely agree 31% 32% 30% 9 2% 0% 3% 8 6% 0% 10% 7 2% 5% 0% 6 8% 5% 10% 5...
AI summary The text presents survey results on customer satisfaction with energy-efficient upgrades, showing varying levels of agreement across different categories, with heat pumps receiving higher satisfaction ratings compared to other measures.
D1. [IF MEASURE CATEGORY = MODELLED] What questions, if any, do you have about the different upgrades installed through the Home Warming program? Overall Measure Category % Modelled% Heat Pump% Sample Size (#) 22 22 0 Other efficiency upgr...
AI summary The document presents survey results from participants in the Home Warming program, highlighting areas for improvement such as communication, information availability, and program awareness. Most respondents indicated satisfaction, but some requested more details about the program and how to operate heat pumps.
Aspects of the Program Score 0 = Not at all satisfied 10 = Completely Satisfied Reason If 7 or less, please share the reason(s) for your score. a. The overall program /10 What could be improved? b. The selection of heat pumps eligible for...
AI summary The table outlines various aspects of a program related to heat pumps and Efficiency Nova Scotia, with each aspect rated on a scale from 0 to 10. It invites feedback on what could be improved, particularly in areas such as program effectiveness, product quality, communication, and data reporting.
- E1. What additional support, tools, or training could Efficiency Nova Scotia provide to help make your job easier? - E2. [IF SUPPORT MENTIONED AT E1] How would you like Efficiency Nova Scotia to deliver this support to you? [PROBE: webin...
AI summary The text presents a series of questions aimed at gathering feedback on how Efficiency Nova Scotia can better support its employees and improve the HomeWarming Program, particularly in relation to heat pump technology and participant education.
- e. What could be improved? Steps (a) Problems Faced by DAs (b) Working Well for DAs (c) Problems Faced by Participants (d) Working Well for Participants (e) What could be improved? ASK IF NOT COVERED 1 The delivery agent (DA) receives in...
AI summary The document outlines a process involving delivery agents (DAs) and Efficiency Nova Scotia in conducting energy assessments and installing upgrades. It highlights areas for improvement in the process, including communication, approval of upgrades, and participant engagement.
APPENDIX XI ASFH Tracking Sheet Audit This appendix presents the main results of the tracking sheet audit performed by the Evaluator, which was aimed at: - › Verifying that all data fields required for the evaluation were included and fill...
AI summary This appendix outlines the results of a tracking sheet audit conducted by the Evaluator to verify the completeness and accuracy of data submitted by E1. The audit ensured that all required fields were included and that calculations for program results were consistent with previous evaluations.
Table 1: 2024 ASFH Corrected Tracked Savings Program Component Result Value Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Value Modelled Measures Gross Energy Savings at the Generator 4.758 GWh 4.635 GWh -...
AI summary Table 1 presents corrected tracked savings for the 2024 Affordable Single-family Homes (ASFH) program, showing a decrease in both modelled and non-modelled measures due to adjustments in calculation methods and overestimation corrections. The differences between tracked and corrected values are attributed to changes in the calculation approach by EfficiencyOne (E1), particularly for non-modelled heat pumps.
C. Satisfaction C1. Using a scale from 1 to 10 where 1 is "not at all satisfied" and 10 is "completely satisfied," how satisfied are you with the Efficient Product Installation Service overall? [DO NOT ACCEPT A RANGE] 1-10 SCALE WITH END P...
AI summary The section evaluates customer satisfaction with the Efficient Product Installation Service (EPI) through 1-10 and 1-4 scales, exploring reasons for satisfaction or dissatisfaction, focusing on energy bill savings, service quality, and product effectiveness.
AND/OR "NO" IN [A1](#page-101-0)[96.99.M](#page-101-2) (SMART THERMOSTAT) AND "YES" IN EITHER [A1](#page-101-0)[96.99.C](#page-101-3) (PIPE INSULATION), [A1](#page-101-0)[96.99.D](#page-101-4) (HOT WATER TANK WRAP), [A1](#page-101-0)[96.99...
AI summary The text outlines conditional eligibility criteria for energy efficiency measures, requiring a 'NO' response for smart thermostats and 'YES' for other domestic hot water (DHW) measures like pipe insulation or low-flow showerheads. It directs to specific sections for further evaluation.
[ASK [E4,](#page-106-1) [E5,](#page-107-0) [E6](#page-107-1) SEQUENCE IN ORDER/DO NOT RANDOMIZE; REPEAT SCALE IF NECESSARY] - E4. Without the Efficient Product Installation Service, how likely would you have been to take the initiative to...
AI summary The text presents survey questions assessing the impact of the Efficient Product Installation Service (EPI) on consumer behavior regarding LED bulb adoption. Respondents are asked about likelihood of purchasing, delaying replacement, and quantity purchased without EPI, evaluating its role in promoting energy efficiency.
[VOLUNTEERED] - 98. Don't know - 99. Refused - E14. [IF [E13=](#page-109-1)YES] Just to confirm: Have I understood correctly that you had already made the decision to purchase and install in your home before you learned about the Efficient...
AI summary The text contains survey questions assessing customer decision-making regarding home energy efficiency measures, including willingness to pay for specific installations (e.g., pipe insulation, hot water tank wrap) with and without the Efficient Product Installation Service (EPI). It explores pre-existing decisions and hypothetical scenarios without EPI incentives.
[VOLUNTEERED] - 98. Don't know - 99. Refused - F3. [IF [F1=](#page-112-0)1] Do you agree or disagree that because of your previous participation in an Efficiency Nova Scotia program or service and what you learned by participating in the s...
AI summary A survey question asks participants if their prior engagement with Efficiency Nova Scotia programs influenced them to request free energy-efficient product installations. The question assesses program impact on customer behavior and adoption of energy-saving measures.
B3. Were there any other reasons? 2018 2021 2024 Reasons for Participating Most Important Motivation Other Important Motivations Most Important Motivation Other Important Motivations Most Important Motivation Other Important Motivations Sa...
AI summary The table presents survey results showing the motivations for participating in energy efficiency programs in 2018, 2021, and 2024. The primary motivation shifted from saving on energy costs in 2018 to environmental protection in 2024, with a notable increase in participants citing no other reasons over time.
B4. Were you present when these energy efficient products were installed? \ Was Present During Installation 2018 2021 2024 Sample Size 100 100 100 Yes 92% 91% 95% No 8% 8% 4% Refused - 1% 1% Wording change in 2021 B5. Did you receive infor...
AI summary The data shows a high percentage of respondents were present during the installation of energy-efficient products in 2018, 2021, and 2024. There was an increase in the percentage of respondents who received information from installers over the years, with a significant drop in those who did not receive any information.
B6. Would you have liked to receive information about energy efficient products from the installer? \ Interested in Receiving Information 2018 2021 (#) 2024 (#) Sample Size 34 15 11 Yes 68% 7 5 No 28% 6 6 Don't know 4% 2 - Base: Respondent...
AI summary The text presents survey data on customer satisfaction with the Efficient Product Installation (EPI) Service. It shows a slight decline in satisfaction from 2018 to 2021, followed by a slight increase in 2024. Customers also provided feedback on reasons for dissatisfaction, such as expectations not being met and product preferences.
2018 2021 2024 Satisfaction with Aspects of EPI Sample Size Mean Sample Size Mean Sample Size Mean The time required to complete work 92 9.5 91 9.4 93 9.3 The quality of the work completed 100 9.5 100 9.3 98 9.3 The information you receive...
AI summary The table presents customer satisfaction survey results for the Efficient Product Installation (EPI) program across three years (2018, 2021, and 2024). It shows metrics related to the time required to complete work, quality of work, and information provided about energy-efficient products. Satisfaction levels remained relatively consistent over the years.
D1. When you initially thought about participating in the Efficiency product Installation Service, what were your concerns, if any? \ Concerns about the Service 2018 2021 2024 Sample Size 100 100 100 Would save money - 9% 8% Would save ene...
AI summary The text presents survey data on concerns related to the Efficiency Product Installation Service (EPI) across three years (2018, 2021, 2024). It shows a decrease in concerns over time, with the most common concerns being related to product efficiency, program requirements, and scheduling. A majority of respondents had no concerns, and a significant portion had already decided to install LED bulbs through EPI before learning about the service.
To Confirm: Already Decided to Purchase and Install 2021 (#) 2024 (#) Before Learning About EPI Sample Size Yes No Don't know Sample Size Yes No Don't know Pipe insulation - - - - 3 2 1 - Hot water tank wrap - - - - 2 2 - - Low-flow shower...
AI summary The table presents data on respondents who had already decided to purchase and install specific energy efficiency measures through EPI before learning about the service. It shows the sample size and responses for different measures in 2021 and 2024.
E15. Without the Efficient Product Installation Service, what is the likelihood you would have paid for the knowing that the cost is about… If No EPI, Likelihood of Paying For The 2024 (# or %) 2024 (# or %) MEASURE> Knowing The Cost is Ab...
AI summary This table explores the likelihood that respondents would have paid for specific domestic hot water (DHW) measures without the Efficient Product Installation (EPI) service, based on cost and sample size. The data shows varying responses depending on the measure and its associated cost.
E16. Without the Efficient Product Installation Service, how likely would you have been to take the initiative to purchase at a store and install them in your home … If No EPI, Likelihood of Taking Initiative to 2024 (# or %) Purchase and...
AI summary This question explores the likelihood of customers taking initiative to purchase and install specific domestic hot water (DHW) measures without the Efficient Product Installation (EPI) service. The data shows varying responses across different measures, with some showing higher likelihoods of purchase and installation, while others show lower probabilities.
E17. Without the Efficient Product Installation Service, what is the likelihood you would have postponed replacing your by at least one year? If no EPI, Likelihood of Postponing 2024 (# or %) Replacement of by at Least One Year Sample Size...
AI summary This question explores the likelihood that respondents would have postponed replacing specific domestic hot water (DHW) measures by at least one year without the Efficient Product Installation (EPI) service. The data shows varying responses across different measures, with low-flow showerheads having the highest percentage of respondents who would have postponed the replacement.
E18. Without the Efficient Product Installation Service, which of the following scenarios would have most likely occurred? You would have purchased and installed… If No EPI, Likelihood of Purchasing and 2024 (# or %) Installing Same, Less...
AI summary This question explores the impact of the Efficient Product Installation (EPI) service on customer behavior. It asks what would have happened if EPI was not available, focusing on the likelihood of customers purchasing and installing energy-efficient products themselves.
E19. How influential were the following two factors in your decision to have energy-efficient products installed in your home? 2024 Influence of Factors in Decision to Have Energy-Efficient Products Installed in Home Sample Size Very/Somew...
AI summary The survey explores the influence of free installation and service staff advice on the decision to install energy-efficient products in homes. It also examines prior participation in Efficiency Nova Scotia (ENS) programs before joining the Efficient Product Installation (EPI) service.
\ Scale change in 2024 F2. Do you agree or disagree that your previous participation in an Efficiency Nova Scotia program or service was a major factor in your decision to have energy-efficient products installed in your home? \
AI summary The text asks whether previous participation in an Efficiency Nova Scotia program or service was a major factor in the decision to install energy-efficient products in a home.
Previous Participation in an ENS Program or Service Was a Major Factor in Decision to Have Energy Efficient Products Installed in Home 2021 2024 Sample Size 34 44 Agree 79% 95% Disagree 21% 5% Base: In 2021, respondents who had LED bulbs a...
AI summary A survey indicates that previous participation in an ENS program or service significantly influenced the decision to install energy-efficient products in homes, with 79% of respondents in 2021 and 95% in 2024 agreeing with this statement.
\ Wording change in 2024 \ Wording change in 2024 F3. Do you agree or disagree that because of your previous participation in an Efficiency Nova Scotia program or service and what you learned by participating in the service, you requested...
AI summary The text asks if the participant agrees or disagrees that their previous involvement in an Efficiency Nova Scotia program led them to request the installation of energy-efficient products at no cost in their home.
Requested Installation of Energy-Efficient Products Because of Previous ENS Program or Service Participation 2021 2024 Sample Size 34 44 Agree 94% 98% Disagree 6% 2% Base: In 2021, respondents who had LED bulbs and/or low flow showerheads...
AI summary The data shows a high level of agreement (94% in 2021 and 98% in 2024) among respondents who had energy-efficient products installed through EPI and had previously participated in ENS programs or services. The sample sizes were 34 in 2021 and 44 in 2024.
F4. Do you agree or disagree that because of your previous participation in another Efficiency Nova Scotia program or service and what you learned by participating, you took into account the savings on your energy bill when evaluating diff...
AI summary The question asks whether participants in an Efficiency Nova Scotia program considered energy bill savings when evaluating energy-efficient products for their home, based on their previous participation and knowledge gained.
Took Into Account the Savings on Energy Bill When Evaluating Different Energy Efficient Products Because of Previous ENS Program or Service Participation 2021 2024 Sample Size 34 44 Agree 82% 95% Disagree 18% 2% Don't know - 2% Base: In 20...
AI summary The data shows a significant increase in agreement (from 82% in 2021 to 95% in 2024) regarding considering energy bill savings when evaluating energy-efficient products due to previous participation in ENS programs or services. The sample size also increased, and the percentage of respondents who disagreed or were unsure decreased.
Seen ENS Advertisement or Information Discussing Benefits of Energy Efficiency Prior to Participating in EPI 2021 2024 Sample Size 98 97 Yes 78% 73% No 20% 25% Don't know 2% 2% Base: In 2021, respondents who had LED bulbs and/or low flow s...
AI summary The data shows a decrease in the percentage of EPI participants who saw ENS advertisements or information about energy efficiency benefits before participating, from 78% in 2021 to 73% in 2024. The sample size also slightly decreased from 98 to 97 respondents.
F6. Do you agree or disagree that the promotion of energy efficiency by Efficiency Nova Scotia was a major factor in your decision to have energy-efficient products installed in your home? \ Promotion of Energy Efficiency Carried Out by EN...
AI summary A survey indicates that 79% of respondents in 2021 and 94% in 2024 agreed that Efficiency Nova Scotia's promotion of energy efficiency was a major factor in their decision to install energy-efficient products in their homes. The sample size decreased slightly from 76 to 71 respondents between 2021 and 2024.
F7. Do you agree or disagree that the promotion of energy efficiency by Efficiency Nova Scotia prompted you to ask for the installation of energy-efficient products at no cost in your home? \ Promotion of Energy Efficiency Carried Out by E...
AI summary A survey shows that 96% of respondents in both 2021 and 2024 agreed that Efficiency Nova Scotia's promotion of energy efficiency prompted them to install energy-efficient products at no cost in their homes. The sample included individuals who had installed various energy-efficient products through EPI and had previously seen ENS advertisements or information about energy efficiency.
\ Wording change in 2024 F8. Do you agree or disagree that you took into account the savings on your energy bill when evaluating different energy-efficient products for your home due to the promotion of energy efficiency by Efficiency Nova...
AI summary The question asks whether the respondent considered energy bill savings when evaluating energy-efficient products for their home, influenced by Efficiency Nova Scotia's promotion of energy efficiency.
Promotion of Energy Efficiency Carried Out by ENS Prompted Taking Into Account the Savings on Energy Bill When Evaluating Different Energy-Efficient Products for Home 2021 2024 Sample Size 76 71 Agree 88% 97% Disagree 11% 1% Don't know - 1...
AI summary A survey conducted in 2021 and 2024 shows that a majority of respondents (88% in 2021 and 97% in 2024) agreed that the promotion of energy efficiency by ENS influenced their consideration of energy bill savings when evaluating energy-efficient home products. The sample size was 76 in 2021 and 71 in 2024.
G1. Since participating in the Efficient Product Installation Service, have you installed any additional efficient products in your home? Installed Additional Efficient Products Since Participating in EPI 2021 2024 Sample Size 100 100 Yes...
AI summary The text presents data on the installation of energy-efficient products by participants in the Efficient Product Installation Service (EPI) in 2021 and 2024. The percentage of participants who installed additional efficient products decreased slightly, and there is a shift in the types of products installed over time.
G3. How many did you purchase and install? 2021 2024 Number of Energy Efficient Products Installed Since Participating in EPI Sample Size Mean Sample Size Mean LED bulbs 9 8.9 5 9.4 LED fixtures 1 3.0 2 5.5 Dehumidifiers 1 1.0 1 1.0 Faucet...
AI summary The table details the number of energy-efficient products installed by participants in the Efficient Product Installation (EPI) program in 2021 and 2024, including LED bulbs, fixtures, dehumidifiers, and others. The data includes sample sizes and mean values per respondent.
G4. Did you receive an instant rebate at the cashier for the [energy efficient product] you purchased? Received Instant Rebate at Cashier for Energy Efficient 2021 (#) 2024 (#) Products Installed Since Participating in EPI Sample Size Yes...
AI summary The text discusses customer experiences with receiving instant rebates at the cashier for energy-efficient products purchased through the Efficient Product Installation (EPI) program. It includes survey data from 2021 and 2024 on product types, sample sizes, and customer feedback on the program's influence and potential improvements.
Table 1: Free-Ridership - LEDs Previous Algorithm n 2024 AI gorithm E4 If there was no Efficient Product Installation Service, how likely would you have been to take the initiative to purchase LED bulbs at a store and\ninstall them yoursel...
AI summary The table presents a comparison of responses to questions about free-ridership related to LED bulb adoption, focusing on the likelihood of customers purchasing and installing LED bulbs without the Efficient Product Installation Service. It includes scoring metrics and response distributions.
APPENDIX XVIII EPI Algorithm for Participant Spillover Calculation Participant spillover was measured using a participant survey. Participants were asked, pursuant to participating in EPI, whether they implemented any additional energy eff...
AI summary This appendix describes the EPI Algorithm for calculating participant spillover, which measures the impact of energy efficiency programs on participants' additional energy efficiency measures. Surveys were used to determine the influence of program components on participants' decisions, and spillover was calculated by dividing additional savings by total savings achieved through program participation.
Table 1: Spillover (for Electrical Savings) 2021 Algorithm 2024 Algorithm Question Answer Score Score Question Answer Score 0 1) Yes CONTINUE Since participating in the 1) Yes CONTINUE G1 Since participating in the Efficient Product Instal...
AI summary Table 1 presents a survey related to the Efficient Product Installation Service, asking participants about additional energy-efficient products installed in their homes and the associated energy savings. The table outlines a structured algorithm for data collection and scoring.
Table 1: Jurisdictional Scan Findings Jurisdiction Program Entity Offering the Program Energy Efficiency Measures Source Canadian Direct-install Programs British Columbia Energy Conservation Assistance Program (ECAP) Fortis BC LED light bu...
AI summary Table 1 presents findings from a jurisdictional scan of energy efficiency programs in Canada, focusing on direct-install programs in British Columbia and Manitoba. It lists various energy efficiency measures offered by entities such as Fortis BC, BC Hydro, and Efficiency Manitoba.
B. Verification of Actions Taken The following questions concern "the energy efficiency upgrades" "the installation project" that you completed through your participation in in for the house located at - B1. "Were your energy efficiency up...
AI summary This document outlines a verification survey for energy efficiency upgrades and heat pump installations under Nova Scotia programs. It asks participants about renovations involving added floor area, heating previously unheated rooms, fireplace/wood stove usage changes, and heat pump installations, ensuring compliance with program requirements.
APPENDIX XXII Green Heat Past Participant Survey Results TABLE B1: Was your Green Heat installed as part of a renovation project that involved adding floor area to your home? By adding floor area, we mean that you added an extension to you...
AI summary This section presents survey results from past participants of the Green Heat program, focusing on whether their Green Heat installations were part of renovation projects involving the addition of floor area to their homes.
OVERALL % SAMPLE SIZE (#) 240 Yes, the renovation project involved heating rooms that were previously not heated/were minimally heated 16% No, the renovation project did not involve heating rooms that were previously not heated/were minima...
AI summary The text presents survey data on heat pump installations and their impact on fireplace and wood stove usage, as well as the presence of air conditioners. The majority of respondents did not heat previously unheated rooms, and most did not have fireplaces or wood stoves. Usage of these heating methods decreased for some after energy efficiency upgrades.
APPENDIX XXIV Green Heat Detailed Methodology and Billing Analysis
AI summary Appendix XXIV outlines the methodology and billing analysis for the Green Heat initiative, focusing on energy efficiency programs, appliance retirement, and heat pump adoption in Nova Scotia. It includes technical details on cost recovery, program evaluation, and regulatory considerations for residential and commercial energy efficiency measures.
Background After inconclusive results in 2023, a billing analysis was again conducted for Green Heat as part of the 2024 DSM evaluation to obtain measured electrical energy savings generated through the installation of mini-split heat pump...
AI summary A 2024 billing analysis for Green Heat evaluated energy savings from mini-split heat pumps (MSHPs) and wood/pellet stoves, updating prior results and using AMI data for improved accuracy. MSHPs are the primary measure, with stove installations analyzed for the first time via billing rather than modeling.
Methodology The billing analysis consisted of calculating the change in electrical energy consumption by comparing levels before and after participation in Green Heat for a group of recent participants (treatment group). To account for var...
AI summary The methodology uses a difference-in-differences approach to measure Green Heat program savings by comparing treatment and control groups, normalizing energy data for weather, and calculating unitary savings for MSHPs and wood/pellet stoves. This isolates program impacts from external factors like the pandemic.
Selection of the Treatment and Control Groups The initial treatment group included 1,211 Green Heat participants (1,014 for MSHP measures and 197 for wood/pellet stoves/fireplace inserts) who were selected based on the following criteria:...
AI summary The treatment group included 1,211 Green Heat participants with specific installation dates and heating criteria, while the control group had 2,810 past participants selected to match treatment characteristics. AMI data availability varied between groups, and the Evaluator ensured similarity using UMP guidelines.
Table 1: Details on the Point System Used for the Selection of Control Participants Parameters Points Average daily consumption of treatment and control candidates after their Add a maximum of 2 points based on a function of the relative d...
AI summary Table 1 outlines a point system for selecting control participants based on average daily consumption differences between treatment and control groups. Points are awarded based on the relative difference, with up to 2 points for a 10% difference and 0 points for a 50% or greater difference. Each participant had different pre and post-program periods, and control participants were matched to treatment participants for billing analysis.
Weather Normalization The Evaluator normalized the consumption values obtained from AMI data using normal weather data to obtain annual consumption values that are aligned with a typical meteorological year. A regression was used to determ...
AI summary The Evaluator normalized AMI data using regression analysis and heating/cooling degree days from 2008-2023 for five weather stations (Debert, Greenwood, Halifax, Sydney, Yarmouth) to align consumption with a typical meteorological year. Multiple iterations were conducted to select optimal balance temperatures for accurate normalization.
MSHP Measures Table 2 presents the results of the billing analysis for the Green Heat MSHP measure. Treatment participants who mentioned adding heated floor area as part of their Green Heat renovation project were excluded from the analysi...
AI summary Table 2 provides the results of the billing analysis for the Green Heat MSHP measure, excluding participants who added heated floor area. Previous results from the 2017 evaluation are included for comparison.
Table 2: MSHP Billing Analysis Results Scenario Number of Treatment Participants Average Heating Capacity (Btu/h) Average Variation in Energy Consumption of Treatment (Tpre-Tpost, kWh) Average Variation in Energy Consumption of Control (Cp...
AI summary Table 2 presents the results of a billing analysis for MSHP (Mini-split heat pump) participants, comparing energy consumption variations between treatment and control groups. The fully electrical scenario shows significant energy savings, while the mainly electrical scenario shows a slight increase in energy consumption. The analysis includes average savings and margin of error for each scenario.
Wood or Pellet Stoves or Fireplace Inserts Measures Wood or pellet stoves or fireplace inserts were analyzed as a single measure. As a starting point, the Evaluator separated the results according to the baseline heating system: ASHP or el...
AI summary The analysis of wood or pellet stoves and fireplace inserts as energy efficiency measures excluded participants who previously used such systems and found that fireplace inserts significantly affect energy savings results. Excluding fireplace inserts increased energy consumption variation and reduced average savings.
Table 3: Wood and Pellet Stove Billing Analysis Results After Removing Fireplace Inserts Scenario Number of Treatment Participants Average Variation in Energy Consumption of Treatment (Tpre-Tpost, kWh) Average Variation in Energy Consumpti...
AI summary Table 3 presents energy savings results after removing fireplace inserts from wood and pellet stoves. The savings are statistically significant, and the Evaluator recommends removing fireplace inserts from Green Heat offerings due to their limited savings.
Literature review To put the results of the billing analysis into perspective, the Evaluator conducted a literature review of recent billing analyses and metering studies performed in other jurisdictions for similar energy conservation mea...
AI summary The Evaluator reviewed literature on billing analyses and metering studies for energy conservation measures, finding no relevant studies on woodburning appliances. However, one billing analysis and two metering studies on MSHPs were identified as methodologically comparable to the current evaluation.
Table 4: Econoler and Energy Trust savings results Scenario Number of Participants Average Savings (kWh) Sample Description Sample N Average Evaluated Savings (kWh) Econoler Green Heat Results Energy Trust Results Fully electric 99 1,514 W...
AI summary Table 4 presents savings results from the Econoler and Energy Trust programs, showing average kWh savings for fully electric and partially electric participants. The overall results include data from 2020-2022, with the note that supplemental heating information was only available for 2022 participants.
Table 5: Econoler and Guidehouse Savings Results Scenario Number of Participants Average Savings (kWh/tone) Displacement Type Sample Electrical Savings (kWh/tonne) Econoler Green Heat Results Guidehouse Results Fully electric 99 1,026 n/a...
AI summary Table 5 presents savings results from Econoler and Guidehouse, showing average electrical savings from green heat initiatives. The fully electric scenario had 99 participants with an average savings of 1,026 kWh/tonne, while the part-electric scenario had 24 participants with a negative saving of -15 kWh/tonne. The overall sample size was 123 participants, with an average savings of 799 kWh/tonne for PD displacement type.
2017 Vermont Metering Study This metering study[5](#page-182-0) was conducted in 2017 and covers cold climate ductless mini-split heat pumps (ccHP) installed in Vermont. The study measured in situ performance and consumption of 77 ccHPs fo...
AI summary The 2017 Vermont Metering Study evaluated the performance of cold climate ductless mini-split heat pumps (ccHPs) installed in Vermont. It measured the in situ performance of 77 ccHPs across 65 service accounts from November 2015 through the 2017 heating season. The study used on-site data collection without a control group and estimated heating savings by assuming ccHPs offset alternate heating systems.
Figure 2: Retrofit Savings per Cold Climate Heat Pump Installed (Cadmus, 2017) Percent of MMBtu Provided by Existing Heating System Heating System Efficiency Assumptions Fuel Heat Content Assumptions Savings Units 7% COP of electric resist...
AI summary Figure 2 presents retrofit savings per cold climate heat pump installed, based on a 2017 Cadmus study. The Evaluator noted discrepancies in interpreting the savings data and consulted the study's author, who recommended using the ccHP consumption and heating capacity results instead for more accurate estimates.
Since Green Heat is offered to homes fully or mainly electrically heated, Econoler estimated savings from the Cadmus study for an electric resistance baseline. Cadmus' average ccHP results are 2,085 kWh consumed and 21.4 MMBtu of heat ener...
AI summary The document discusses energy savings estimates for Green Heat, which is offered to homes primarily heated by electricity. Econoler calculated savings based on the Cadmus study, estimating 4,261 kWh in annual savings, including both heating and cooling, and normalized these savings per Btu/h of installed capacity.
Table 6: Econoler and Cadmus Savings Results Scenario Sample Average Savings per Capacity (kWh/Btu/h) Baseline Heating System Sample Electrical Savings (kWh/Btu/h) Econoler Green Heat Results Cadmus Results Fully electric 99 0.0855 Electri...
AI summary Table 6 presents the savings results from Econoler and Cadmus for different heating scenarios. The data includes average savings per capacity and electrical savings, with notes indicating that some baseline heating systems were not electric resistance and that savings were estimated rather than directly measured.
Summary of Literature Review Findings The Evaluator reviewed the aforementioned three studies to compare and put into perspective the savings results of the 2024 Green Heat billing analysis. - › The 2024 billing analysis conducted in Orego...
AI summary The Evaluator compared the 2024 Green Heat billing analysis with studies from Oregon, Massachusetts/Connecticut, and Vermont. Results showed similar savings (1,032–1,075 kWh) except for Vermont’s higher savings (3x), attributed to different methodologies, higher-efficiency heat pumps, and early adopter behavior. Recent studies reinforce confidence in Green Heat’s findings.
APPENDIX XXVII HEA Past Participant Survey Results Table B1: Were your energy efficiency upgrades installed as part of a renovation project that involved adding floor area to your home? By adding floor area, we mean that you added an exten...
AI summary This section presents survey results from past participants of the Home Energy Assessment (HEA) program, focusing on whether energy efficiency upgrades were installed as part of a renovation project involving the addition of floor area to their homes.
OVERALL % SAMPLE SIZE (#) 483 Yes 2% No 98% TABLE B2: Were your energy efficiency upgrades installed as part of a renovation project that involved heating rooms that were previously not heated or were only minimally heated (for example, at...
AI summary The tables present survey data on energy efficiency upgrades, including the percentage of participants who installed upgrades during renovation projects involving heating previously unheated rooms, the presence of fireplaces or wood stoves, changes in their usage after upgrades, and the installation of heat pumps. The survey data is part of the Home Energy Assessment program.
A. Verification and Recall - A1. Just to confirm, do you recall having an Energy Advisor from a delivery partner of the Home Energy Assessment program come to your home located at to complete a home energy assessment in ? - 1. Yes [CONTINU...
AI summary This section verifies whether respondents had a Home Energy Assessment conducted by a delivery partner's Energy Advisor, received recommendations, completed upgrades, and booked follow-up visits for rebate qualification. It also confirms current residence at the addressed location.
B. Upgrades Implemented and Influence B1. Which of the following upgrades, if any, did you implement after you received your home energy assessment report? [DO NOT ROTATE - CODE ONE ONLY PER STATEMENT] [1 = YES, IMPLEMENTED, 2 = NO, NOT IM...
AI summary The document outlines a survey assessing homeowner upgrades post-home energy assessment, including heat pumps, insulation, and smart thermostats, and evaluates the assessment's influence on implementation decisions. It also inquires about rebate applications for heat pump installations.
C. Reasons for Not Conducting an E Assessment - C1. Which one of the following best describes the reason why you chose not to have the follow-up visit by an Energy Advisor? [DO NOT READ, ACCEPT ONE RESPONSE] - 1. Follow-up visit was too di...
AI summary The document presents survey questions to identify reasons participants did not pursue follow-up energy assessments, including scheduling difficulties, cost concerns, perceived lack of utility, and completion of energy-saving measures. Options highlight barriers to program participation and evaluation.
D. Verification of Interest for a Visit - D1. Would you be interested in having an Energy Advisor again come to your home, for free, to perform an energy assessment of your house? - 1. Yes - 2. No - 98. (Don't know) - 99. (Refused) END: Th...
AI summary The text presents a survey question asking if respondents would be interested in a free home energy assessment by an Energy Advisor. It includes response options and concludes the interview. The focus is on verifying interest in residential energy efficiency programs.
APPENDIX XXIX HEA Expired Participant Survey Results TABLE A1: Just to confirm, do you recall having an Energy Advisor from a delivery partner of the Home Energy Assessment program come to your home located at to complete a home energy ass...
AI summary This section presents survey results from participants whose Home Energy Assessment (HEA) expired, confirming whether they recall an Energy Advisor from a delivery partner visiting their home to complete the assessment.
TABLE A2: [POSE ONLY IF 'YES' TO A1] And do you recall receiving a Home Energy Assessment report that identified renovations or upgrades that could improve your home's energy efficiency? OVERALL % SAMPLE SIZE (#) 338 Yes 97% No 2% Don't kn...
AI summary The table presents survey results showing that a high percentage of respondents received Home Energy Assessment reports and identified renovations or upgrades to improve home energy efficiency. However, implementation rates vary significantly across different questions and sample sizes.
Which of the following upgrades, if any, did you implement after you received your home energy assessment report? OVERALL % SAMPLE SIZE (#) 76 None 5% 1 of 9 33% 2 of 9 34% 3 of 9 17% 4 of 9 9% 5 of 9 0% 6 of 9 0% 7 of 9 1% 8 of 9 0% 9 of...
AI summary The text presents survey data on home energy upgrades and rebate applications following home energy assessments. It includes statistics on the number of upgrades implemented, rebate applications for heat pumps, and reasons for not proceeding with follow-up visits by Energy Advisors.
TABLE C1/C2: TOTAL MENTIONS: Which one of the following best describes the reason why you chose not to have the follow-up visit by an Energy Advisor? Were there other reasons as well? OVERALL % SAMPLE SIZE (#) 76 Follow-up visit was too di...
AI summary The table presents reasons why participants did not have follow-up visits by Energy Advisors, with the most common reason being lack of time. Another table asks if participants would be interested in a future free energy assessment. The appendix mentions a HEA Tracking Sheet Audit but provides no details.
› For the differences in gross energy savings: - › Correction of unitary savings for some biomass measures - › Correction of the logic used to determine the unitary savings for HPWH (heat pump or electric baseboard baseline heating system)
AI summary The text outlines two corrections related to energy savings calculations: adjusting unitary savings for biomass measures and revising the logic for determining unitary savings for HPWH (Heat Pump Water Heater) under different baseline heating systems.
› For the differences in net energy savings: - › Correction of NTGR and/or line loss factors for some participants that had hardcoded values using outdated parameters instead of formulas - › A deduction of additional participants for uncon...
AI summary The text outlines corrections needed for net energy savings calculations: adjusting NTGR/line loss factors using outdated parameters, addressing unconverted D assessment spillover reversals, and fixing Green Heat savings deductions that incorrectly used gross meter savings instead of net generator savings in EfficiencyOne's tracking sheet.
› For the differences in demand savings: - › The same explanations as for energy savings - › Correction of formula for biomass measures, which rounded the savings at the kW instead of the W for each participant - › Correction of some heat...
AI summary The text outlines three corrections related to demand savings: reusing energy savings explanations, fixing a biomass measure formula rounding error from kW to W, and updating heat pump specs via NEEP cross-reference. These adjustments aim to improve accuracy in demand-side management calculations.
Methodology To assess the electrical energy savings obtained from HEA energy efficiency upgrades, the billing analysis consisted of calculating the change in electrical energy consumption before (pre) and after (post) participation in HEA...
AI summary The methodology assesses electrical energy savings from HEA upgrades by comparing treatment and control groups, normalizing AMI data against HOT2000 modelled savings, and calculating adjustment ratios (ARs) to isolate program-specific impacts from external factors like the pandemic.
Energy Savings Calculation Figure 1 below illustrates how energy savings were obtained by calculating the difference in the treatment group normalized annual consumption of each participant for the year before and after program participati...
AI summary Energy savings are calculated by comparing normalized annual consumption of treatment and control groups before and after program participation, then adjusting using HOT2000 modelled savings. Exclusions include wood burning equipment, solar PV systems, and HPWHs, which are handled via prescriptive savings methods.
Detailed Results Once the main steps of the billing analysis were completed, the Evaluator conducted several analyses to interpret the data. The three scenarios used to establish ORs, associated with the presence of a heat pump or not, rem...
AI summary The Evaluator conducted analyses after completing the billing analysis, focusing on scenarios with and without heat pumps. Survey results showed that participants who added heating or floor area had lower savings, indicating the need to account for such changes. Econoler recommended using average consumption values from the entire control group for more accurate results.
Table 2: Detailed Results from the Analysis by Heat Pump Scenario Scenario Sample Size Pre-consumption (kWh/year) Post-consumption (kWh/year) Difference (kWh/year) A participant who registered with a heat pump Treatment Group 49 20,245 17,...
AI summary Table 2 presents detailed results from an analysis of energy consumption before and after heat pump installation across different participant groups. The results show significant energy savings, although margins of error are high due to variability and limited sample size. The Evaluator still considers the adjustment ratios (ARs) reliable based on consistent consumption trends.
Table 3: Evaluated Adjustment Ratios by Heat Pump Scenario Scenario AR Margin of Error A participant who registered with a heat pump 1.24 57.7% A participant who registered without a heat pump and who did not have one installed 0.58 13.2%...
AI summary Table 3 evaluates adjustment ratios (AR) for different heat pump scenarios, showing significant variations in margin of error. The highest margin of error (93.0%) is for participants who registered without a heat pump and later had one installed, suggesting uncertainty in savings estimates for this scenario.
Impacts of Billing Analysis Results on Modelled Measure Savings To get a sense of how the new adjustment ratios and calculation approach impact energy savings for modelled measures in HEA, Table 4 below compares gross electrical energy sav...
AI summary The document compares the impact of new adjustment ratios and calculation approaches on modelled measure savings in HEA, showing that the new methods are slightly more penalizing than previous ones. This comparison is based on gross electrical energy savings at the meter for 2024.
Table 1: Reporting Requirements for Different Energy Savings Scenarios[8](#page-13-0) Scenarios 1 2 3 4 Change in Overall Electrical Energy Consumption Increase Increase Decrease Decrease Change in Overall Non-electrical Energy Consumption...
AI summary Table 1 outlines the reporting requirements for different energy savings scenarios, including changes in electrical and non-electrical energy consumption, reporting types, and equations used to calculate DSM and government-funded savings. The rationale explains how savings are accounted for in each scenario to avoid double counting.
This appendix summarizes all the recommendations made by the Evaluator as part of the 2024 HEA evaluation. Section Recommendations Executive Summary Recommendation #1: In light of their very low savings and considering their low uptake, co...
AI summary This appendix summarizes recommendations from the 2024 HEA evaluation, including the suggestion to remove wood and pellet fireplace inserts from the HEA offer due to low savings and uptake.
Table 1: 2024 MHEEP Corrected Tracked Savings Value Tracked by E1 Corrected Tracked Value Relative Difference Program Component Results Value Unit Value Unit Value MHEEP (Excluding Appliance Replacements) Gross Energy Savings at the Genera...
AI summary This table presents the corrected tracked savings for the 2024 MHEEP program, showing minor differences between the original tracked values and the corrected values. The adjustments were made due to a change in methodology to better account for electrical space heating percentages and the use of outdated unitary savings for certain appliance replacements.
Where: - › = A number between 1 and 12 to identify the given month - › _ℎ, = The control group's average daily consumption in a given month of the post-program period - › _ℎ, = The treatment group's average daily consumption in a given mon...
AI summary The document outlines the methodology for calculating monthly electricity savings in 2024 for high, medium, and low users, noting discrepancies in active treatment participants due to inactivity or solar transitions between group selection and program launch.
EfficiencyOne
AI summary The document text consists solely of the heading 'EfficiencyOne' from a Nova Scotia regulatory proceeding, with no further content or context provided in the chunk.
DEFINITIONS Accuracy Reflects the proximity of measurements to the true value. Equivalent CO2 A unit of measurement indicating the amount of carbon dioxide to which various kinds of emitted greenhouse gases are equivalent in terms of warmi...
AI summary The document defines key terms such as 'Accuracy' and 'Equivalent CO2', providing detailed explanations for each. These definitions are important for understanding measurement reliability and greenhouse gas equivalency in the context of energy efficiency and environmental impact assessments.
Evaluation Approach The 2024 evaluation was aimed at calculating program component gross and net results, namely electrical first-year and lifetime energy savings, peak demand savings, as well as avoided greenhouse gas (GHG) emissions. [Ta...
AI summary The 2024 evaluation focused on calculating program component gross and net results, including electrical first-year and lifetime energy savings, peak demand savings, and avoided greenhouse gas emissions. Table 1 summarizes the types of evaluation conducted and the corresponding methodology.
Table 2: Overall 2024 Efficient Product Rebates Participation and Evaluated Savings Participation Level Gross Gross Savings Net Savings Value Unit Value Unit Value Value Unit Application Rebates Energy Savings 262 Projects 15.526 GWh 0.74...
AI summary Table 2 presents the 2024 participation levels and evaluated savings from efficient product rebates, including energy savings, peak demand savings, GHG emission reductions, and effective useful life. The data is categorized into Application Rebates and Instant Rebates, with overall totals and net-to-gross ratios (NTGR) provided for each category.
BER Findings and Recommendations This subsection presents the key findings and recommendations from the 2024 BER evaluation. 2024 BER-Finding: BER net electrical energy savings almost reached the target of 39.747 GWh, falling short by less...
AI summary The 2024 BER evaluation found energy savings nearly met targets, with Instant Rebates participation dropping 26% due to LED market saturation, while Application Rebates grew by 18%. Satisfaction with Instant Rebates remained high, free-ridership decreased, and LED fixtures now dominate the market with near-total adoption.
BER Application Rebates In 2024, 15,644 units were rebated through 262 projects that were implemented by 199 unique participant[s](#page-39-2) 2 under Application Rebates. [Figure](#page-40-0) 2 below illustrates how Application Rebates pa...
AI summary In 2024, 15,644 units were rebated through 262 projects under BER Application Rebates, with 18% more businesses participating than 2023. Lighting and motors accounted for 82% of energy savings, driven by a large project yielding 2.998 GWh. Energy savings per participant rose 16%.
2 BER Evaluation Approach The 2024 BER-AR evaluation included a condensed impact evaluation, while the BER-IR evaluation included a comprehensive impact evaluation as well as a process evaluation and market evaluation. The main objectives...
AI summary The 2024 BER evaluation aimed to collect participant and distributor perspectives, calculate gross and net BER results, and analyze the evolution of the BNI lighting market. It included both condensed and comprehensive impact evaluations, as well as process and market evaluations.
Efficient Product Rebates Program 8 Evaluation Objectives Research Questions Methodology Analyze the evolution of the BNI lighting market › How has the BNI lighting market evolved in Nova Scotia since 2021? › To what extent are LED product...
AI summary This section evaluates the evolution of the BNI lighting market in Nova Scotia since 2021, focusing on the availability of LED products compared to non-LED products and the implications of an updated baseline for E1's BNI lighting programs. The research methodology includes surveys, distributor interviews, and market characterization studies.
Effective Useful Life Update As part of the 2024-2025 DSM MA update activities, the Evaluator also reviewed the effective useful life (EUL) values for all measure categories and recalculated the EUL values of lighting measures for which ba...
AI summary As part of the 2024-2025 DSM MA update, the Evaluator reviewed and recalculated effective useful life (EUL) values for lighting measures, considering anticipated baseline changes during their lifetimes.
Calculations Using Evaluation Results Building on all the above methods and collected data, the Evaluator calculated first-year and lifetime energy savings as well as peak demand savings as per the calculation methodologies presented in Se...
AI summary The Evaluator calculated first-year and lifetime energy savings, as well as peak demand savings, using methodologies outlined in Sections 4 and 5 of the document. These calculations build on prior data collection and evaluation methods.
3.1 Participant Awareness and Decision to Purchase
AI summary This section discusses participant awareness and the decision-making process related to purchasing energy efficiency measures or programs. It likely addresses factors influencing consumer choices, program accessibility, and barriers to participation in initiatives like DSM or BER.
Instant Rebates Participants Of all IR survey participants (n=50), six in 10 said they purchased energy efficient products (that were available for IR) for their own organization (60%), while nearly four in 10 (38%) either said they purcha...
AI summary A survey of 50 Instant Rebates participants revealed that 60% purchased energy-efficient products for their own organizations, while 38% did so for customers or as contractors. Contractors primarily rely on organizational decision-making for purchases, with energy efficiency as the top reason (43%) for choosing efficient products. Distributors are the primary rebate awareness source (74%), and 81% of participants had not considered alternatives to the purchased products.
3.3 Distributor Satisfaction with Instant Rebates Distributors (n=10) were asked to express their level of satisfaction with various aspects of Instant Rebates using a 10-point scale where 1 means "Not at all satisfied" and 10 means "Very...
AI summary Distributors expressed high satisfaction with Instant Rebates, with an average score of 8.3 out of 10. Satisfaction with service support and communications was even higher at 9.3. However, some dissatisfaction arose due to the maturity of LED technology and time-intensive administrative tasks.
3.4 Service Influence on Distributors Similar to 2022, distributors of LED linear fixtures, LED linear lamps, and LED outdoor fixtures were questioned about the different strategies employed to sell each of these product categories in 2024...
AI summary Distributors in 2024 promoted LED products through strategies such as Instant Rebates, discounts, and training workshops, particularly for LED fixtures. These efforts were more common for LED fixtures than for LED lamps. Distributors noted limited availability of non-LED alternatives, which influenced their strategies.
2024 BER Participant and Distributor Perspective Highlights - › The majority of Instant Rebate survey participants purchased energy efficient products for their own organization, while fewer purchased the products for a customer/project ou...
AI summary Participants in the 2024 BER Instant Rebate program primarily purchased energy-efficient products for their own organizations, driven by energy efficiency and cost savings. Satisfaction with the service was high (9.1), though distributors suggested expanding eligibility and improving rebate processes. Distributors used E1 rebates to promote LEDs but faced challenges with administrative burdens and product adoption perceptions.
4.2 Gross Savings Gross savings refer to changes in energy consumption resulting from actions taken by participants regardless of their reasons for participating.[6](#page-52-5) For each Application Rebates project, E1 tracks annual gross...
AI summary Gross savings are defined as energy consumption changes from participant actions, measured annually by E1 using the BER CIRx Screening Tool (version 1.6) for Application Rebates projects. The tool incorporates project-specific savings methodologies and equipment parameters.
4.2.1 Adjustment Ratios The Evaluator applied adjustment ratios to the tracked gross savings to determine evaluated gross savings. These ratios were established using 2022 project review results, with the exception of the lighting measure...
AI summary Adjustment ratios were applied to tracked gross savings using 2022 project reviews, except for lighting measures using 2021 data. Solar PV projects had specific ratios (0.942 for RETScreen, 1.101 for PVWatts) not used by E1 in 2024, with a recommendation to adopt them for accuracy.
4.2.2 Interactive Effects Interactive effects occur when the implementation of energy efficiency measures has an impact on the energy consumption of other elements such as heating and cooling; these are considered in the gross savings stan...
AI summary Interactive effects in energy efficiency programs, particularly for indoor lighting under BER, are evaluated using the BER CIRx Screening Tool. Adjustments are made based on site observations and 2024 DSM MA factors, with evaluators ensuring accuracy. Lighting adjustments are reflected in the 2024 adjustment ratio.
Table 9: Updated BER AR EUL Values Measure Tracked EUL Evaluated EUL LED Linear Fixtures 1 x 4 Luminaires 11.6 11.9 2 x 2 Luminaires and Retrofit Kits 11.6 11.9 2 x 4 Luminaires and Retrofit Kits 11.6 11.9 Linear Ambient and Low-bay Lumina...
AI summary Table 9 presents updated Business Energy Rebates (BER) Annualized Energy Usage Life (EUL) values for various energy efficiency measures. The table shows both tracked and evaluated EUL values for different lighting and HVAC measures, with the weighted average EUL for gross and net savings calculated as 18.9 years.
Table 11: Evaluated 2024 Application Rebates Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 15.526 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross A...
AI summary Table 11 presents the gross GHG emission reductions from the evaluated 2024 rebate applications, showing 7,331 tonnes of CO2 eq reduction based on energy savings and a specific emissions factor for Nova Scotia.
Table 14: Evaluated 2024 Application Rebates Net Energy and Peak Demand Savings Measure Category Agriculture Commercial Kitchen HVAC Lighting Motors Pumping Energy Savings Gross Energy Savings – at the Meter (GWh) 0.082 0.017 1.818 7.955 3...
AI summary Table 14 presents the evaluated 2024 application rebates net energy and peak demand savings across various measure categories, including agriculture, commercial kitchen, HVAC, lighting, motors, pumping, refrigeration, and solar PV. The table includes gross and net energy savings, line loss factors, effective useful life, and peak demand savings at both the meter and generator levels.
Gross Savings NTGR Net Savings Realization Rate Value Unit Value Unit Energy Savings Tracked Savings by E1 15.526 GWh 0.74 11.489 GWh Evaluation Results 15.526 GWh 0.74 11.489 GWh 100% Peak Demand Savings Tracked Savings by E1 1.721 MW 0.7...
AI summary The table presents energy and peak demand savings tracked by E1, with NTGR values showing the ratio of net savings to gross savings for Application Rebates. The evaluation results show 100% realization for both energy and peak demand savings.
5.2 Gross Savings For Instant Rebates, gross savings refer to changes in energy consumption resulting from actions taken by participants regardless of their reasons for participating.[10](#page-59-5) Since the identification of eligible me...
AI summary The text defines gross savings for Instant Rebates as energy consumption changes from participant actions, using assumptions for measure types. Calculations involve parameters like baseline wattages, ballast factors, and peak coincidence factors. The 2024-2025 DSM Measure Assessment details these methods, with equations and EUL values reviewed during the DSM MA update.
Table 16: Instant Rebates Tracked and Evaluated HOU Values Measure Tracked Annual HOU (hours/year) Evaluated Annual HOU (hours/year) LED Linear Fixtures 1 x 4 Luminaires 4,300 4,209 2 x 2 Luminaires and Retrofit Kits 4,300 4,209 2 x 4 Lumi...
AI summary The text presents tables tracking and evaluating HOU values for instant rebates related to LED lighting fixtures and occupancy/motion sensors. The data shows tracked and evaluated annual HOU values and unitary energy savings for different lighting measures and sensor types.
Parameter Type of Occupancy Sensor Tracked Value [W] Updated Value [W] Unitary Peak Demand Interior Remote Ceiling or Wall-mounted 37.6 26.3 Savings (W) Fixture Mounted or Wall Switch 21.9 Exterior 31.1 35.3 5.2.4 Interactive Effects
AI summary The table presents the impact of occupancy sensors on unitary peak demand and energy savings, with data showing reductions in tracked values and updates for different sensor types. The section '5.2.4 Interactive Effects' likely discusses the combined effects of these sensors on energy efficiency and demand management.
Table 19: Instant Rebates Tracked and Evaluated EUL Values Measure Tracked EUL (years) Evaluated EUL (years) LED Linear Fixtures 1 x 4 Luminaires 11.6 11.9 2 x 2 Luminaires and Retrofit Kits 11.6 11.9 2 x 4 Luminaires and Retrofit Kits 11....
AI summary Table 19 presents the tracked and evaluated Equivalent Energy Usage Life (EUL) values for various LED lighting measures under the Instant Rebates program. The evaluated EUL values are used to calculate gross and net lifetime electrical energy savings, resulting in a gross weighted average EUL of 14.1 years.
Table 20: Evaluated 2024 Instant Rebates Gross Energy and Peak Demand Savings Measure Category LED Linear Fixtures LED Linear Lamps LED Outdoor Fixtures LED Directional and Architectural Fixtures Outdoor Motion Sensors Indoor Occupancy/ Mo...
AI summary Table 20 presents the evaluated 2024 instant rebates gross energy and peak demand savings for various measures, including LED fixtures, motion sensors, and circulator pumps, providing data on energy savings, demand savings, and associated factors like adjustment ratios and interactive effects.
[Figure](#page-65-0) 9 below compares the tracked and evaluated gross energy savings, and [Figure](#page-65-1) 10 further below compares the tracked and evaluated gross peak demand savings. The slight differences between evaluated gross el...
AI summary The text compares tracked and evaluated gross energy and peak demand savings from the 2024 Instant Rebates program. Differences in energy savings are attributed to updated HOU for LED measures and occupancy/motion sensors. GHG emission reductions are calculated using a Nova Scotia-specific factor applied to gross savings.
Table 21: Evaluated 2024 Instant Rebates Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 31.327 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annua...
AI summary Table 21 presents evaluated 2024 instant rebates gross GHG emission reductions, including energy savings, emissions factor, and annual emission reductions. Section 5.3 discusses net savings, though details are not provided in the chunk.
Table 23: 2024 Instant Rebates NTGRs Measure Free-ridership NTGR LED Linear Fixtures 8% 0.92 LED Linear Lamps 15% 0.85 LED Outdoor Fixtures 15% 0.85 Other Measures 0% 1.00 5.3.3 Evaluated Net Savings
AI summary Table 23 presents the 2024 Instant Rebates NTGRs for various energy efficiency measures, including free-ridership percentages and NTGR values. Section 5.3.3 discusses the evaluated net savings related to these rebates.
Table 24: Evaluated 2024 Instant Rebates Net Energy and Peak Demand Savings Measure Category LED Linear Fixtures LED Linear Lamps LED Outdoor Fixtures LED Directional and Architectural Fixtures Outdoor Motion Sensors Indoor Occupancy /Moti...
AI summary Table 24 evaluates the 2024 Instant Rebates program, detailing net energy and peak demand savings across various measure categories such as LED fixtures, motion sensors, and circulator pumps. It provides data on gross and net energy savings, line loss factors, and net lifetime energy savings, as well as peak demand savings at both the meter and generator levels.
Gross Savings NTGR Net Savings Realization Value Unit Value Unit Rate Energy Savings Tracked Savings by E1 32.251 GWh 0.84 27.068 GWh Evaluation Results 31.327 GWh 0.90 28.040 GWh 104% Peak Demand Savings Tracked Savings by E1 5.031 MW 0.8...
AI summary The evaluated net electrical energy and peak demand savings were 4% and 6% higher than the values tracked by E1. Increases in savings from occupancy/motion sensors and updated NTGRs for LED fixtures led to higher evaluated savings than tracked values.
6 Overall BER Results As outlined in [Figure](#page-71-2) 11, BER nearly reached the planned net electrical energy savings, falling short by less than 1%, and exceeded the peak demand savings target by 13% Figure 11: 2024 BER Targets and E...
AI summary The 2024 Business Energy Rebates (BER) program nearly met its planned net electrical energy savings target, falling short by less than 1%, and exceeded the peak demand savings target by 13%. Table 26 compares savings tracked by E1 to evaluated savings and realization rates.
7.2.1 DesignLights Consortium (DLC) Certified Fixtures Distributors were asked about the breakdown of the LED fixtures between DLC Standard Certified, DLC Premium, and non-certified products. Of the six distributors that were asked those q...
AI summary The text discusses distributor reports on the distribution of DLC-certified LED fixtures (Standard, Premium) versus non-certified products, noting that most distributors carry DLC Premium (80%+), with some non-certified stock. Distributors believe DLC certification remains stable even without rebates, citing performance and industry standards. Rebates make DLC-certified prices competitive with non-certified products.
Table 28: 2024 Analysis of Key Factors in Market Evolution Factor Results Market share of LED fixtures for BNI sector The fixtures market is fully transformed to LED; distributors report that all or nearly all of their fixture stock is LED...
AI summary The LED lighting market in the BNI sector is largely transformed, with LED fixtures dominating and lamps nearing full adoption. Distributors report stable pricing and quality differences among LED products. No more efficient substitute to LEDs has emerged, and both markets are evolving toward multi-mode models.
8 BER Key Findings and Recommendations The main objectives of the 2024 BER evaluation were as follows: - › Collect information on participant and distributor perspectives - › Calculate gross and net BER results (for both AR and IR), namely...
AI summary The 2024 BER evaluation found BER nearly met its net electrical energy savings target (39.529 GWh vs. 39.747 GWh), exceeded peak demand savings by 13% (5.746 MW vs. 5.107 MW), and saw a 26% drop in Instant Rebates participation but 18% growth in Application Rebates. Satisfaction with Instant Rebates remained high despite lower participation.
CONCLUSION Table 29 presents the participation levels, net-to-gross ratios (NTGRs), evaluated gross and net savings at the generator, annual GHG emission reductions, as well effective useful life (EUL) values for each service and Efficient...
AI summary Table 29 summarizes participation levels, net-to-gross ratios, evaluated gross and net savings, annual GHG emission reductions, and effective useful life values for each service and Efficient Product Rebates as a whole.
Table 29: Overall 2024 Efficient Product Rebates Participation and Evaluated Savings Participa tion Level Gross s Savings NTGR Net S avings Value Unit Value Unit Value Value Unit Application Rebates Energy Savings 262 Projects 15.526 GWh 0...
AI summary Table 29 presents data on the participation and evaluated savings from efficient product rebates in 2024, including energy savings, GHG emission reductions, and EUL for both Application Rebates and Instant Rebates. The table highlights the effectiveness of these programs in reducing energy consumption and emissions.
C. Participation and Decision to Purchase - C1. [ASK IF CONTRACTOR [A3=](#page-90-0)2] Who usually makes the decision to buy rather than standard ? Is it… [READ CODE 1-2 AND 96. SINGLE RESPONSE] . - 1. You or someone else in your organizat...
AI summary The document outlines a series of questions aimed at understanding decision-making processes related to purchasing energy-efficient products, such as LED lighting, and the factors influencing these decisions. It explores who makes the purchase decisions, whether customers seek advice, and the importance of various factors like energy efficiency, cost savings, and incentives.
D12. How influential were the following four factors in your decision to purchase ? [RANDOMIZE] Factor (READ AND RANDOMIZE) Responses a. [ASK IF D1=1 OR D2=2] The program rebate 1. Very influential 2. Somewhat influential 3. Not very influ...
AI summary The text presents a survey question (D12) asking respondents about the influence of four factors in their decision to purchase an efficient product. The factors include program rebates, information from Efficiency Nova Scotia representatives, information from distributors, and the prevalence of LED products. The survey includes response options ranging from 'Very influential' to 'Not at all influential' and includes options for 'Don't know' and 'Refused'.
ASK ALL - READ AND ROTATE (E1 + E2-E4) AND (E5 + E6-E8) SEQUENCES - E1. Before participating in the Business Energy Rebates program in , had your company/organization at any time in the past already participated in the Business Energy Reba...
AI summary The text outlines a series of questions for participants in the Business Energy Rebates program, inquiring about prior participation in Efficiency Nova Scotia programs and the influence of past experiences on current decisions regarding energy efficiency. It includes branching logic based on responses.
[READ IF [E5=](#page-99-0)1] For the following statements, please indicate whether you agree or disagree. E6. [IF E5=1] Do you agree or disagree that Efficiency Nova Scotia promotional materials or communications were a major factor in the...
AI summary The text contains survey questions related to the impact of Efficiency Nova Scotia promotional materials on purchasing decisions for efficient products, specifically LED lighting. It also asks about the proportion of lighting projects involving rebate recipients.
A3. Did you purchase these products for your own organization, or are you a company purchasing products for a customer or project outside of your organization? Purchase for Contractor or End User 2018 2019 2020 2021 2022 2024 Technology/Sc...
AI summary The text presents data on the purchase of energy-efficient products by contractors and end users across various sectors from 2018 to 2024. It includes statistics on the percentage of purchases made for different sectors, the number of contractors seeking purchase decision advice, and the consideration of alternatives to LED lighting.
C8. What was the SECOND most important reason you purchased rather than standard ? Motivations for 2018 2019 2020 2021 2022 2024 Buying Efficient Products Most Important Reason Other Reasons Most Important Reason Other Reasons Most Importa...
AI summary The table presents data on the motivations for purchasing efficient products over standard products from 2018 to 2024, highlighting energy efficiency, cost savings, and program incentives as key factors influencing the decision.
C9. Did your distributor recommend to you? Distributor Recommended Product 2018 2019 2020 2021 2022 2024 Sample Size 49 60 51 50 50 50 Yes 51% 62% 71% 60% 62% 52% No 43% 33% 29% 40% 38% 40% Don't know 6% 5% - - - 8% C10. For what type of p...
AI summary The text presents survey data on distributor recommendations for efficient products, the types of projects for which these products were purchased, and the condition of existing fixtures or lamps when the products were acquired. The data spans multiple years and includes percentages of responses for each category.
D2. Have I understood correctly that you were not aware that a rebate would be given on the product's total cost when you purchased these items? \ Aware of Product Rebate Prior to Purchase 2018 2019 2020 2021 2022 2024 Sample Size 50 60 51...
AI summary The text presents survey data on customer awareness of rebates from Efficiency Nova Scotia's Business Energy Rebates Program. It shows that awareness of rebates and their source has varied over the years, with a significant portion of respondents becoming aware through their distributor.
D5. Had you already decided to purchase these before talking to a distributor? Already Made Decision to Purchase Product Before Talking to a Distributor 2022 2024 Sample Size 50 50 Yes 86% 72% No 14% 26% Don't know - 2% Already Made Decisi...
AI summary The data shows a decrease in the percentage of respondents who decided to purchase efficient products before talking to a distributor, from 86% in 2022 to 72% in 2024. Additionally, awareness of rebates influenced purchasing decisions, with a decline in the percentage of respondents who would have purchased the exact same model of premium lighting products if rebates were not offered.
D12. How influential were the following four factors in your decision to purchase ? \ 2024 Influence of Factors in Decision to Purchase Efficient Product Sample Size Vey/Somewhat influential Not very/Not at all influential The program reba...
AI summary This table assesses the influence of four factors on customers' decisions to purchase efficient products in 2024. The program rebate had the highest influence (89% very/somewhat influential), followed by the prevalence of LED products, information from distributors, and information from Efficiency Nova Scotia program representatives.
Previous Participation in Another ENS Program Component 2018 2019 2020 2021 2022 2024 Sample Size 50 60 51 50 50 50 Yes Yes, in Business Energy Rebates 58% 62% 69% 22% 26% 26% (Total) Yes, in another program(s) 2% - 1% Yes, in both Busines...
AI summary The table shows participation rates in Efficiency Nova Scotia (ENS) programs from 2018 to 2024. Participation in Business Energy Rebates increased from 58% in 2018 to 69% in 2020 but dropped to 26% in 2024. There was also a change in wording and scale in 2021 and 2024.
\ \ Respondents aware of rebate \ \ \ Respondents aware that rebate was offered by Efficiency Nova Scotia
AI summary The text indicates that respondents were aware of a rebate offered by Efficiency Nova Scotia, highlighting their knowledge of the rebate program.
E2. Do you agree or disagree that your company/organization's previous participation in an Efficiency Nova Scotia program was a major factor in the decision to purchase ? \ Previous Participation in BER and/or Another ENS Program Was a Maj...
AI summary The text asks respondents whether their previous participation in an Efficiency Nova Scotia (ENS) program was a major factor in purchasing an efficient product. The table shows a high percentage of respondents agreeing across multiple years, indicating a strong influence of ENS programs on purchasing decisions.
\ Wording change in 2024 E3. Do you agree or disagree that because of your company/organization's previous participation in an Efficiency Nova Scotia program and what was learned by participating in that program, a company representative a...
AI summary The text asks whether a company or organization, due to prior participation in an Efficiency Nova Scotia program, had a representative consult a contractor or technical staff member to examine energy efficiency options for their facility.
Previous BER and/or ENS Program Participation Led to Ask About Energy Efficiency Options 2018 2019 2020 2021 2022 2024 Sample Size 29 37 35 29 34 15 (#) Agree 69% 78% 74% 72% 85% 9 Disagree 24% 22% 20% 17% 15% 6 Don't know/Refused 6% - 6%...
AI summary The table shows the percentage of respondents who agreed, disagreed, or were unsure about energy efficiency options based on their participation in the BER or ENS programs from 2018 to 2024. Agreement rates increased over time, peaking at 85% in 2022.
E4. Do you agree or disagree that because of your company's previous participation in an Efficiency Nova Scotia program and what was learned by participating in that program, a company representative took into account the cost-effectivenes...
AI summary The question asks whether a company representative considered the cost-effectiveness of energy-efficient measures, based on previous participation in an Efficiency Nova Scotia program, when evaluating options for the company's facility.
Previous BER and/or ENS Program Participation Led to Assess Cost-Effectiveness of Different Energy-Efficient Options 2018 2019 2020 2021 2022 2024 Sample Size 29 37 35 29 34 28 Agree 86% 89% 94% 86% 88% 93% Disagree 7% 11% 6% 14% 12% 7% Do...
AI summary The table shows the percentage of respondents who agreed, disagreed, or were unsure about the cost-effectiveness of energy-efficient options based on their participation in the BER or ENS programs from 2018 to 2024. Agreement levels are generally high, with the highest at 94% in 2020.
Previously Seen Energy Efficiency Promotional Materials Distributed by ENS 2018 2019 2020 2021 2022 2024 Sample Size 50 60 51 50 50 50 Yes 96% 87% 88% 88% 86% 84% No 2% 13% 12% 10% 14% 12% Don't know 2% - - 2% - 4% E6. Efficiency Nova Scot...
AI summary The table shows the distribution of promotional materials by Efficiency Nova Scotia (ENS) and their impact on purchase decisions. A majority of respondents agreed that ENS materials were a major factor in their decisions, with percentages ranging from 57% to 69% across the years.
E7. Do you agree or disagree that Efficiency Nova Scotia promotional materials or communications prompted a company representative to ask a contractor or a distributor about efficient lighting
AI summary The text asks whether Efficiency Nova Scotia's promotional materials or communications prompted a company representative to inquire about efficient lighting from a contractor or distributor.
options for your organization? \ ENS Energy Efficiency Promotional Materials Led to Ask About Products 2018 2019 2020 2021 2022 2024 Sample Size 48 52 45 44 43 23 Agree 63% 62% 69% 61% 65% 39% Disagree 35% 37% 31% 36% 30% 43% Don't know 2%...
AI summary A table shows survey results from 2018 to 2024 on how respondents who saw ENS energy-efficiency promotional materials perceived their impact. Agreement with the effectiveness of these materials declined from 63% in 2018 to 39% in 2024, while disagreement and uncertainty increased.
\ Slight wording change in 2022 and 2024 E8. Do you agree or disagree that Efficiency Nova Scotia promotional materials or communications prompted a company representative to take into account the cost-effectiveness of when evaluating diff...
AI summary The text asks whether Efficiency Nova Scotia's promotional materials or communications influenced a company representative to consider the cost-effectiveness of an efficient product when evaluating options for a facility.
ENS Energy Efficiency Promotional Materials Led to Assess Product Cost-Effectiveness 2018 2019 2020 2021 2022 2024 Sample Size 48 52 45 44 43 42 Agree 81% 77% 71% 66% 63% 76% Disagree 19% 23% 29% 32% 37% 21% Don't know - - - 2% - 2% Base:...
AI summary The table shows the percentage of respondents who agreed, disagreed, or were unsure about the cost-effectiveness of ENS energy-efficiency promotional materials from 2018 to 2024. Agreement rates decreased slightly over time but increased again in 2024.
F1. Over the last year, have you made other lighting purchases for customers that received Efficiency Nova Scotia rebates at the distributor? 2024 Sample Size 19 (#) Yes 17 No 2 Base: Contractors F2. Thinking about all the lighting project...
AI summary The question asks whether lighting purchases were made for customers who received Efficiency Nova Scotia rebates at the distributor over the past year. The response indicates that out of a sample size of 19, 17 customers had other lighting purchases made for them.
F3. And, of those lighting projects that were for replacement of existing lamps or fixtures, what proportion of the existing lamps or fixtures were: Working but at the end of their useful life: 41.4% Working and not close to the end of the...
AI summary The text discusses the proportion of lighting projects that involved replacing existing lamps or fixtures that were either at the end of their useful life or not close to the end. 41.4% were working but at the end of their useful life, and 28.8% were working and not close to the end of their useful life.
G2B. Why were you not more satisfied with the rebate amounts? Most Important Reason for Not Being More Satisfied with Rebate Amounts 2019 2020 2021 2022 2024 Sample Size 12 (#) 17 (#) 10 (#) 8 (#) 6 (#) Rebate is too small/Expected higher...
AI summary Respondents expressed dissatisfaction with rebate amounts, citing reasons such as rebates being too small, inconsistency in rebate amounts, and lack of information. Some respondents also suggested additional efficient equipment or services for which rebates could be provided.
G4. What was the most important reason you were not more satisfied with the program overall? Any other reasons? Most Important Reason Not More Satisfied with BER Overall 2019 2020 2021 2022 2024 Sample Size 7 (#) 12 (#) 5 (#) 7 (#) 2 (#) D...
AI summary The document presents survey results from participants in the Business Energy Retrofit (BER) program, highlighting reasons for dissatisfaction and suggestions for improvement. Key issues include rebate size, program consistency, paperwork, and communication, while suggestions focus on increasing rebates, simplifying processes, and improving marketing.
C8. [ASK IF A3=1, C1=1 OR C3=1; DO NOT ASK IF 98 OR 99 IN C4] What was the SECOND most important reason you purchased rather than standard PRODUCT>? [DO NOT READ. SINGLE RESPONSE.] 1. Availability of other alternatives 2. Energy efficie...
AI summary The text presents a series of survey questions related to customer purchasing decisions regarding efficient products, including reasons for purchase, distributor recommendations, and project types. It also includes conditional questions based on prior responses.
[ASK [D8](#page-96-0) TO [D11](#page-97-0) IF AWARE OF REBATE [(D1=](#page-95-0)1 or [D2=](#page-95-1)2), RANDOMIZE [D8](#page-96-0) TO [D11]](#page-97-0) - D8. Without the BER rebate, what is the likelihood that you would have purchased t...
AI summary The text presents a series of questions related to the impact of a rebate program on the purchase of efficient lighting products. It asks respondents about their likelihood of purchasing the same products, keeping existing fixtures, purchasing quantities, and postponing purchases without the rebate.
F. Market – LED Lighting The next series of questions are about how the market for LED lighting is evolving in Nova Scotia - F1. [ASK IF [A3](#page-90-0) = 2] Over the last year, have you made other lighting purchases for customers that re...
AI summary The section discusses the market for LED lighting in Nova Scotia, focusing on purchases made for customers who received Efficiency Nova Scotia rebates. It includes questions about the proportion of lighting projects for rebate recipients.
New construction% Replacement of existing fixtures or lamps% [TOTAL MUST EQUAL 100%] F3. [ASK IF Response to F2 Replacement of existing fixtures or lamps ≠ 0] And, of those lighting projects that were for replacement of existing lamps or f...
AI summary The text presents a series of questions related to the replacement of existing lighting fixtures and the adoption of LED lighting. It seeks information on the proportion of existing lamps or fixtures that are working but nearing the end of their life, broken, or still functional, as well as reasons for slower adoption of LED lighting and building types with the most potential for LED adoption.
Table 1: 2024 Application Rebates Corrected Tracked Savings Service Result Value Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Value BER Application Rebates Gross Energy Savings at the Generator 15.582 GWh...
AI summary Table 1 presents corrected tracked savings for the 2024 BER Application Rebates, showing no differences between the original and corrected values for energy and peak demand savings at the generator level. Appendix V discusses an audit of the BER Instant Rebates Tracking Sheet.
Table 1: 2024 Instant Rebates Corrected Tracked Savings - Lighting Service Results Value Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Value Instant Rebates - Lighting Gross Energy Savings at the Generator...
AI summary Table 1 presents corrected tracked savings for 2024 Instant Rebates in lighting, showing minor differences between original and corrected values. The discrepancies were attributed to inconsistent unitary energy savings from occupancy sensor entries and interactive effects factors for energy savings and wattage baselines.
Table 2: 2024 Instant Rebates Corrected Tracked Savings - Pumping Program Component Results Value Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Value Instant Rebates - Pumping Gross Energy Savings at the G...
AI summary Table 2 shows the 2024 Instant Rebates Corrected Tracked Savings for Pumping. The data indicates that both gross and net energy and peak demand savings at the generator remained unchanged after correction, with a negligible difference of -0.09%.
Table 1: Instant Rebates Distributor Influence Level Algorithm 2022 Algorithm 2024 Algorithm Question Answer Score Question Answer Score Influence 1 [ASK IF B1=1-6 OR 96 OR B2=2] I'd like to learn more about what influenced your organizati...
AI summary Table 1 outlines an algorithm used to assess the influence level of distributors in the context of instant rebates for efficient products. It includes questions and scoring mechanisms to evaluate factors affecting decision-making related to the sale of efficient products in 2022 and 2024.
Table 2: Instant Rebates Participant and Overall Free-ridership Algorithm 2022 Algorithm 2024 J Algorithm Question Answer Score Question Answer Score INTE NTION Cost Efficiency Nova Scotia offered a rebate for 1) Answer: (scale 0-10) Answe...
AI summary Table 2 outlines the Instant Rebates Participant and Overall Free-ridership Algorithm, comparing the 2022 and 2024 algorithms. It includes questions related to rebate participation, such as the likelihood of participating in a rebate program for purchasing efficient products, with scores based on responses.
To further supplement the market evaluation findings, the Evaluator conducted a jurisdictional scan to investigate similar programs to BER-IR. The Evaluator found very few instant discount programs targeted at the BNI sector. BC Hydro, Eff...
AI summary The Evaluator conducted a jurisdictional scan and found very few instant discount programs targeted at the BNI sector, with only the IESO program identified as similar to BER-IR, which requires replacing inefficient lighting.
Jurisdiction - Program Measures Baseline Information Notes Massachusetts – MassSave Instant Lighting Incentives Lamps are not incented. Controlled lighting products only – fixtures and troffer retrofit kits with controls. Past studies indi...
AI summary The text discusses lighting incentive programs in Massachusetts, Wisconsin, and Ontario, highlighting differences in eligibility criteria, baseline assumptions, and implementation rules. Massachusetts and Ontario have specific rules for controlled lighting products and retrofit kits, while Wisconsin excludes lighting from its instant discount program. Ontario's program excludes new construction and has unclear enforcement mechanisms.
This appendix summarizes all the recommendations made by the Evaluator as part of the 2024 BER evaluation. Section Recommendations Executive Summary Recommendation #1: Undertake additional research to further validate the market evaluation...
AI summary The Evaluator recommends additional research to validate market evaluation results for LED baseline effectiveness in BER-IR, reviewing eligibility criteria for LED lighting in new construction, maintaining the non-LED baseline for BER-IR, and planning for a shift in product offerings from BER-IR to BER-AR. The recommendations also focus on improving tracking of multi-wattage products and increasing interest in controlled lighting products.
DEFINITIONS Accuracy Reflects the proximity of measurements to the true value. Baseline To determine gross savings, a baseline (or base case) is established, providing detailed information about the reference (e.g. pre-existing or standard...
AI summary The text defines key terms such as accuracy, baseline, bias, billing calibration, and confidence interval, providing detailed explanations for each. These definitions are relevant to energy efficiency and measurement processes.
Table 1: Summary of 2024 Custom Incentives Program Evaluation Program Evaluation Type Methodology Component Impact Process Market Custom Comprehensive New Construction › Participant builder and non-participant modeller phone interviews (Ne...
AI summary The 2024 Custom Incentives Program Evaluation includes comprehensive assessments of the Custom and SEM programs. The evaluation methodology involves interviews, project reviews, and analysis of program participation and effectiveness. In 2023, SEM and EMIS were merged into a single program component.
Table 2: Overall 2024 Custom Incentives Participation and Savings Particip ation Level Gross s Savings NTGR Net Savings Value Unit Value Unit Value Unit Value Custom • Energy Savings 49.825 GWh 0.80 39.951 GWh Lifetime Energy Savings 628.9...
AI summary Table 2 shows the participation and savings from the 2024 Custom Incentives program, which exceeded its targets for net electrical energy and peak demand savings. The program achieved 44.429 GWh in net energy savings and 5.793 MW in net peak demand savings, with Custom being the largest contributor.
amiliar with New Construction service, including those that work on non-MURB projects. 2024 New Construction-Finding: Decarbonization is a motivator for participating in New Construction service. 2024 New Construction-Finding: Financial fa...
AI summary Barriers to energy-efficient new construction include financial costs, builder awareness gaps, and insufficient energy modeller participation. Recommendations include increasing modelling incentives, recruiting more modellers through outreach, and collaborating with educational institutions. Builders must adapt to NECB 2020 requirements, which demand higher upfront costs and efficiency technologies.
SEM Findings and Recommendations This subsection provides the key findings and recommendations from the SEM evaluation. The recommendations are also outlined in Appendix XVIII. 2024 SEM-Finding: SEM exceeded its net electrical energy and p...
AI summary SEM exceeded 2024 energy and peak demand savings targets by 6% and 14% respectively, maintained stable participation levels over five years, and improved M&V accuracy. Seven of 12 participants achieved savings, with peak demand estimates showing significant methodological improvements.
Program Tracked and Evaluated Savings [Table](#page-171-1) 3 below compares E1 tracked energy and peak demand savings to evaluated savings at the generator. It also includes the realization rate, representing the ratio of evaluated net sav...
AI summary The table compares E1's tracked energy and peak demand savings to evaluated savings at the generator, including realization rates and NTGR values, which are rounded averages obtained by dividing net savings by gross savings.
EfficiencyOne (E1), an independent, non-profit organization, is responsible for helping Nova Scotians improve the energy efficiency of their homes and workplaces by designing, marketing, and delivering demand-side management (DSM) for Nova...
AI summary EfficiencyOne (E1) is a non-profit organization that provides energy efficiency and demand response services in Nova Scotia through the Efficiency Nova Scotia (ENS) franchise. E1's 2024 DSM program portfolio includes the Custom Incentives program, which was evaluated by Econoler. The evaluation focuses on baseline definitions, savings calculation methodologies, parameter values, and net-to-gross ratios.
Retrofit - Technical and financial support to help organizations conduct scoping and feasibility studies. - Technical and financial support for the implementation of energy efficiency projects using a customized and flexible approach.\ - •...
AI summary The Retrofit initiative provides technical and financial support for energy efficiency projects, targeting organizations with annual electricity consumption of 350,000 kWh or higher. Eligibility requires projects to be unstarted, with a customized approach for implementation.
New Construction - Technical and financial support to achieve electrical energy savings in new buildings and for major renovations in existing buildings, excluding savings from lighting systems. - •Participation begins at the preliminary d...
AI summary The program provides technical and financial support for energy efficiency in new buildings and major renovations, requiring facilities of at least 15,000 sq ft to achieve 25% energy consumption reductions and 100,000 kWh electricity savings. Participation begins at the preliminary design stage.
Building Optimization (BOpt) - Technical and financial support to help organizations conduct an investigation study with the objective of improving building operational efficiency. - Technical and financial support for the implementation o...
AI summary Building Optimization (BOpt) provides technical and financial support for investigations and low-cost energy efficiency measures in eligible facilities. Eligibility requires facilities to have a building automation system, annual consumption of 350,000 kWh or more, and not have been commissioned in the past two years.
Pay-for-Performance (P4P) - Financial support for reductions in electricity consumption achieved through a variety of capital and behavioural energy efficiency upgrades. - •Incentives are based on verified facility energy performance. - Or...
AI summary Pay-for-Performance (P4P) provides financial incentives for verified energy efficiency savings, targeting large electricity consumers. EfficiencyOne (E1) tracks multi-year savings for custom projects, with partial or final claims based on project completion. Combined programs aim for 27.036 GWh of energy savings and 4.101 MW peak demand reduction in 2024.
Retrofit In 2024, energy and/or demand savings were generated by a total of 88 Retrofit projects, including - › 75 projects completed in 2024 - › 61 single-year projects - › 14 multiyear projects - › 13 projects that claimed partial saving...
AI summary In 2024, 88 Retrofit projects generated energy and demand savings, with 75 completed projects achieving 17% higher average savings per project compared to 2023. Despite a 19% decrease in completed projects from 2023, overall gross energy savings increased by 24%, and peak demand savings rose by 35%. Compressed air leak audits, motor upgrades, and solar PV measures were the top contributors to savings.
New Construction In 2024, 28 projects claimed savings under New Construction: 27 complete projects and 1 project, a new industrial facility, that was partially completed and for which savings were claimed because the building was commissio...
AI summary In 2024, 28 New Construction projects achieved energy savings, including 27 completed projects and one partially completed industrial facility commissioned in 2024. Savings reached record highs, with 21.495 GWh and 4.004 MW in gross energy and peak demand savings. The number of completed projects increased after a decline between 2021–2023.
Building Optimization A total of three Building Optimization projects reported savings in 2024: two single-year projects and one project that claimed partial savings since it began in 2024 but was not completed. One of the completed projec...
AI summary Three Building Optimization projects reported 2024 savings, with energy savings per project up 53% despite fewer projects. Total savings increased by 219% and 48% for energy and peak demand, respectively, due to a partial savings claim from an uncompleted project.
2 Custom Evaluation Approach The 2024 Custom evaluation comprised a comprehensive impact evaluation for Retrofit, Building Optimization, and New Construction. For Building Optimization, given its smaller contribution to Custom savings, NTG...
AI summary The 2024 Custom evaluation assessed Retrofit, Building Optimization, and New Construction programs, focusing on energy savings, GHG reductions, and participation analysis. NTGR 2021 data was applied for Building Optimization due to 2024 project inactivity. Objectives included calculating savings, analyzing sub-sector/region participation, and reviewing logic models.
Table 6: 2024 Custom Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate gross results › Are the data in the tracking sheet complete, accurate, and consistent? › Are the gross savings calculated for a sample...
AI summary Table 6 outlines the 2024 Custom Evaluation Approach, focusing on calculating gross and net results, exploring opportunities to expand program presence, and updating program service logic. It includes research questions, methodologies, and evaluation objectives for various projects and programs.
Modeller Interviews To collect information on program awareness, motivations, barriers, and views on NECB 2020 and electrification, the Evaluator conducted phone interviews with three non-participant energy modellers and two newly particip...
AI summary The Evaluator conducted phone interviews with five energy modellers (three non-participants and two new participants) between November 2024 and January 2025 to assess program awareness, motivations, barriers, and views on NECB 2020 and electrification. The interview guide is detailed in Appendix IX.
Calculations Using Evaluation Results Building on all the above methods and collected data, the Evaluator calculated the first-year and lifetime energy and peak demand savings as per the calculation methodology presented in Sections [3,](#...
AI summary The Evaluator calculated first-year and lifetime energy and peak demand savings using methodologies outlined in Sections 3, 5, and 6. These calculations build on prior data collection and evaluation methods to quantify program impacts.
Table 8: Impact Evaluation Approach per Retrofit Project Category Retrofit Project Number of Projects Gross Savings Methodology Net Savings Category Completed in 2024 Methodology Regular Retrofit 44 Adjustment ratio determined from a full...
AI summary Table 8 outlines the impact evaluation approach for different retrofit project categories, detailing the number of projects, gross savings methodology, and net savings evaluation. The methodology varies by project type, with adjustments based on prior evaluations from 2021 to 2023.
3.2 Gross Savings Gross savings correspond to the changes in energy consumption resulting from actions taken by Retrofit participants regardless of why they participated.[8](#page-185-4) E1 tracks the annual gross savings of each project....
AI summary Gross savings are calculated based on energy consumption changes from Retrofit participants' actions. E1 tracks annual gross savings using participant data, supplemented by engineering assumptions and professional judgments, following best measurement and verification practices for commercial/industrial energy efficiency projects.
3.2.1 Savings Verification For compressed air leak audit and solar PV projects, the Evaluator verified savings by validating that the correct input parameters were used to estimate savings and applying a previously established adjustment r...
AI summary The Evaluator verified savings for compressed air leak audits and solar PV projects by validating input parameters and applying adjustment ratios. Energy and demand savings for air leak audits used 2021 Retrofit ratios, while solar PV projects used 2023 adjustment ratios.
3.2.3 Project Review Findings The Evaluator reviewed the project sample to ensure the best measurement and verification practices were applied for commercial and industrial energy efficiency projects and adjusted the tracked savings accord...
AI summary The Evaluator reviewed energy efficiency projects to ensure best measurement and verification (M&V) practices were applied, adjusting tracked savings accordingly for commercial and industrial programs.
Compressed Air Leak Audit Project Review The Evaluator also conducted an in-depth review of one of two large compressed air leak audit projects completed by the same participant at two different facilities. These projects were conducted us...
AI summary The Evaluator reviewed a compressed air leak audit project using an innovative all-in-one platform, finding the process sound and reliable. Documentation and savings calculations were accurate, leading to an adjustment ratio of 1.0. Technical expertise from the OEM and participant staff ensured project quality, with no adjustments made to energy savings estimates.
3.2.4 Interactive Effects Since interactive effects vary significantly from one Retrofit project to another, they are taken into account in the project engineering calculations used to obtain initial gross savings. Any adjustments required...
AI summary Interactive effects in retrofit projects vary significantly and are incorporated into engineering calculations for initial gross savings. Adjustments for these effects are addressed during project reviews to ensure accuracy in savings estimates.
Table 9: 2024 Retrofit Adjustment Ratios per Project Category Retrofit Project Category Adjustment Ratio on Energy Savings (Margin of Error) Adjustment Ratio on Demand Savings (Margin of Error) Regular Retrofit 1.021 (±4.9%) 1.001 (±0.2%)...
AI summary Table 9 presents 2024 Retrofit Adjustment Ratios for various project categories, including Regular Retrofit, Solar PV systems using different modeling tools, and Compressed Air Leak Audits. The table highlights the adjustment ratios for energy and demand savings, along with associated margins of error.
Table 10: Example of a 2024 True-up Adjustment 2023 2024 Total Tracked Savings (kWh) 469,584 108,249 577,833 Year-specific Adjustment Ratio 1.017 1.021 Revised Savings Prior to True-up (kWh) 477,567 110,522 588,089 Total Project Revised Sa...
AI summary Table 10 provides an example of a 2024 True-up Adjustment, showing tracked savings, adjustment ratios, and revised savings for energy efficiency projects. Table 11 outlines overall evaluated gross savings for Retrofit, incorporating adjustment ratios and true-up adjustments to account for multiyear project completions in 2024.
Table 11: Evaluated 2024 Retrofit Gross Energy and Peak Demand Savings Partial Savings Claimed Final Savings Claimed for Single Year Projects Final Savings Claimed for Multiyear Projects Total Number of Projects 13 61 14 88 Energy Savings...
AI summary Table 11 presents the evaluated 2024 Retrofit Gross Energy and Peak Demand Savings, including metrics such as energy savings in GWh, adjustment ratios, line loss factors, and effective useful life. The table breaks down data by project type and includes calculated values for gross energy and peak demand savings at both the meter and generator levels.
3.4 Realization Rate [Table](#page-194-0) 17 below compares the total 2024 tracked and evaluated savings for Retrofit. It also includes the realization rate, representing the ratio of evaluated net savings to tracked net savings, for both...
AI summary The section discusses the realization rate for Retrofit in 2024, comparing total tracked and evaluated savings, and explains line loss factors and effective useful life (EUL) values used for calculating energy and peak demand savings.
Table 17: Comparison of 2024 Retrofit Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Unit Value Energy Savings Tracked Savings by E1 26.115 GWh 0.79 20.719 GWh 109% Eva...
AI summary Table 17 compares the 2024 retrofit tracked and evaluated savings at the generator, including energy and peak demand savings. Tracked savings by E1 and evaluation results are presented with NTGR values and realization rates, highlighting differences due to true-up adjustments and varying NTGRs applied to project categories.
ty requirements and municipal building rules limit these opportunities to some degree, this information indicates that there may be some opportunity for the service to widen its reach outside the HRM. While insufficient modelling support c...
AI summary The text highlights opportunities to expand energy efficiency programs beyond the HRM, noting barriers like limited modeling support and lower program awareness in rural areas. Energy modellers recommend tailored outreach, in-person engagement, and targeted messaging to address rural builders' needs, such as familiarity with oil-based systems over heat pumps. Growth rates inside HRM (24% annually) outpace those outside (15% annually).
4.2 Awareness and Motivations This section presents the findings from interviews with two newly participating modellers and three nonparticipant modellers to understand their awareness of the program, and perspectives on the motivation of...
AI summary Interviews with modellers reveal varying awareness of the Custom New Construction program, with non-participants showing limited familiarity. Builders are motivated by cost reduction, sustainability goals, and incentives. Modellers note clients prioritize long-term value, operational cost savings, and compliance with energy codes. Some builders aim to meet market demand for green buildings or government mandates.
4.4.1 Challenges Encountered Only two participants reported that their company had experienced challenges with Custom New Construction in the past year. One of them said there was a delay in guidance from E1 on the eligibility of a measure...
AI summary Two participants reported challenges with Custom New Construction programs: one cited delayed guidance from E1 on measure eligibility, causing design delays, while another criticized inadequate incentives for 'hyper'-efficient buildings.
4.5 Modeller and Participant Suggestions for Improvements Participants shared a number of suggestions for improving Custom New Construction, including conducting outreach to developers and builders to inform them of available incentives; f...
AI summary Participants and modellers suggested improving the Custom New Construction program through targeted outreach to developers, tiered incentives for complex buildings, simplified processes, increased awareness via platforms like LinkedIn, and reduced barriers to entry. Modellers emphasized training, government engagement, and adjusting incentive levels to boost participation.
4.6.2 Decarbonization and Electrification Program participants and non-participating and new energy modellers were also asked about the importance of reducing GHG emissions and the electrification in building design. Six of the eight parti...
AI summary Participants emphasized the importance of GHG emission reduction and electrification in building design, citing financial incentives from E1. Builders expressed concerns about upfront costs, grid reliability, and regulatory complexity. Electrification challenges include long lead times for specific equipment and grid reliability risks for critical facilities.
NECB 2015. A direct comparison to other jurisdictions is difficult because of the differences in baseline code (Efficiency Manitoba) or in the unit of comparison (BC Hydro has a GHG savings minimum). E1 requires buildings to be larger than...
AI summary The text compares E1's building size requirements and incentive structures with other jurisdictions like BC Hydro, Hydro Québec, and Massachusetts. It highlights differences in size thresholds, maximum modelling incentives, and implementation incentive caps, noting E1's alignment with some regions but disparities in others.
Table 18: Comparison program of building codes, eligibility, and incentives Jurisdiction Equivalent Baseline Code Minimum Eligibility (% Better Than Code) Building Size Requirement Modelling Incentive Implemen tation Incentive Structure Ma...
AI summary Table 18 compares building code requirements, eligibility criteria, and incentive structures across various jurisdictions, including Efficiency Nova Scotia, BC Hydro, New Brunswick Power, Efficiency Manitoba, Hydro-Québec, and National Grid Massachusetts. The table highlights differences in baseline codes, minimum eligibility, building size requirements, and incentive amounts.
4.8.2 Barriers Based on interviews with program staff, participating builders, and non-participant and new energy modellers, the evaluator found that high measure costs, modelling costs, and limited developer awareness are the primary barr...
AI summary The evaluator identifies high measure and modelling costs, limited developer awareness, and insufficient modeller capacity as key barriers to achieving energy efficiency service objectives. E1 staff note rising energy modelling costs and high upfront efficiency measure costs deter builder participation, while modellers report inadequate capacity to meet project demands.
4.8.3 Alignment of Program Logic With Barriers The service addresses the high costs barrier through financial inputs in the form of modelling and implementation incentives, which result in financial benefits to developers that encourage th...
AI summary The service addresses high costs through financial incentives for energy modeling and implementation. However, 30% of projects hit the 50% cost cap, and E1's incentives are lower than some jurisdictions. The shift to NECB 2020 may require adjusting incentive tiers to align with new code standards.
4.8.4 Logic Model Summary To summarize, the evaluator identified four important barriers that the service is working to overcome. These barriers are addressed by and aligned with the program logic model and theory of change to varying degr...
AI summary The evaluator identified four barriers to the program's success: high energy modelling costs, high upfront costs, limited developer awareness, and insufficient modeller participation. While some barriers are addressed in the logic model, others are not. Updates to the model are recommended to align activities with all barriers, including adding high modelling costs and awareness gaps.
2024 Custom NC Process Highlights - › There is a relatively high level of participant satisfaction with Custom New Construction overall. - › The service has been more successful in reaching MURBs than non-MURBs inside the HRM. - › There ar...
AI summary The 2024 Custom NC Process shows high participant satisfaction but faces challenges in reaching non-MURBs due to eligibility rules and municipal codes. Builders cite financial risks and upfront costs as major barriers to decarbonization, with concerns about NECB 2020 compliance timelines. Key barriers include high modelling costs, limited modeller participation, and low developer awareness, though the service addresses some issues outside its logic model.
5 New Construction Impact Evaluation The objective of the 2024 New Construction impact evaluation was to determine gross and net electrical energy and peak demand savings. In 2024, two types of savings were claimed: (1) partial savings (pr...
AI summary The 2024 New Construction impact evaluation aimed to assess gross and net electrical energy and peak demand savings, distinguishing between partial savings (future projects) and final savings (2024 single-year projects).
5.2 Gross Savings This subsection describes the methodology used by the Evaluator to review the gross savings of New Construction projects. For New Construction, gross savings for each participating building are calculated using energy mod...
AI summary The Evaluator calculates gross savings for new construction using energy models comparing baseline (NECB Part 8, E1 guidelines) and proposed designs with efficiency measures. Savings are derived from differences in modelled electricity consumption between these cases.
5.2.1 Sampling Methodology For the energy model review, the evaluator selected 12 of the 27 completed projects. The selected sample of 12 projects represented 68% of total tracked energy savings for projects completed in 2024. Only complet...
AI summary The evaluator sampled 12 of 27 completed projects, representing 68% of 2024 energy savings, excluding one incomplete industrial project. Gross savings were extrapolated using a weighted average adjustment ratio. The excluded project will be reviewed in 2025.
Energy Savings Positive or negative adjustments were made to the tracked gross energy savings of all 12 projects reviewed by the Evaluator for 2024. The energy model reviews resulted in an average adjustment ratio of 1.028 for gross energy...
AI summary Adjustments to energy savings for 12 projects in 2024 revealed discrepancies between modeled and actual installations, including HVAC system mismatches and incorrect ERV installations. An average adjustment ratio of 1.028 was applied, with improvements in as-built model accuracy due to E1's enhanced document control.
Table 19: Evaluated 2024 New Construction Gross Energy and Peak Demand Savings Partial Savings Claimed Final Savings for Projects Fully Claimed in 2024 Total Number of Projects 1 27 28 Energy Savings Tracked Gross Energy Savings – at the M...
AI summary Table 19 evaluates the 2024 new construction gross energy and peak demand savings, providing data on tracked and adjusted energy and peak demand savings at the meter and generator levels. It also includes the effective useful life and lifetime energy savings, as well as line loss factors.
6.2 Gross Savings Gross savings correspond to changes in energy consumption resulting from actions taken by Building Optimization participants regardless of why they participated. This subsection describes the review methodology used for a...
AI summary Gross savings in Building Optimization projects are calculated based on energy consumption changes, using data from participants and E1, supplemented by engineering assumptions. The Evaluator applied best measurement and verification practices for commercial and industrial energy efficiency projects.
6.2.1 Project Review Findings The Evaluator reviewed both completed Building Optimization projects. Following the review, the Evaluator revised the energy savings of one project, and the demand savings of both projects. - › One project inv...
AI summary The Evaluator reviewed two completed Building Optimization projects, adjusting energy savings upward for one and demand savings downward for both due to miscalculations in original assessments. No average adjustment ratio was established, with total savings calculated by summing individual project evaluations. Partial savings claims will require future reviews.
6.2.2 Interactive Effects Since interactive effects vary significantly from one Building Optimization project to another, they are either accounted for in the project engineering calculations used to establish gross savings or included whe...
AI summary Interactive effects in Building Optimization projects are addressed through engineering calculations or whole-building data. For six reviewed projects, no interactive effects were identified, so gross savings remained unadjusted.
6.2.4 Evaluated Gross Savings [Table](#page-18-0) 24 below presents the overall evaluated gross savings for Building Optimization, which were obtained by applying project-specific adjustments to energy and peak demand savings as a result o...
AI summary The section discusses the evaluation of gross savings for Building Optimization projects, including adjustments for energy and peak demand savings based on project reviews. Line loss factors from the 2014 Cost of Service Study Progress Update were used to calculate savings at the generator level for each project.
Table 24: Evaluated 2024 Building Optimization Gross Energy and Peak Demand Savings Partial Savings Claimed Final Savings Claimed for Single Year Projects Total Number of Projects 2 2 4 Energy Savings Tracked Gross Energy Savings – at the...
AI summary Table 24 presents the evaluated 2024 Building Optimization Gross Energy and Peak Demand Savings, including metrics such as tracked energy savings, adjustment ratios, line loss factors, and lifetime energy savings. The table provides a breakdown of energy and peak demand savings at both the meter and generator levels.
Table 25: Evaluated 2024 Building Optimization Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 1.975 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross...
AI summary Table 25 presents the evaluated 2024 Building Optimization Gross GHG Emission Reductions, showing 933 tonnes of CO2 eq reductions annually from energy savings. This data is part of a broader analysis of energy efficiency initiatives and their environmental impact.
Table 27: Evaluated 2024 Building Optimization Net Energy and Peak Demand Savings Partial Savings Claimed Final Savings Claimed for Single Year Projects Total Number of Projects 2 2 4 Gross Energy Savings – at the Meter (GWh) 1.540 0.318 1...
AI summary Table 27 presents evaluated energy and peak demand savings from the 2024 Building Optimization program. It shows gross and net energy savings at the meter and generator, along with peak demand savings, effective useful life, and line loss factors for single-year projects and partial savings claimed.
Table 28: Comparison of 2024 Building Optimization Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Unit Value Energy Savings Tracked Savings by E1 1.954 GWh 0.91 1.778 G...
AI summary Table 28 compares the tracked and evaluated energy savings from the 2024 Building Optimization program. It shows gross and net savings in gigawatt-hours and megawatts, along with realization rates, indicating the effectiveness of the program's energy-saving measures.
Table 29: Comparison of 2024 Custom Tracked and Evaluated Savings at the Generator Gross Savings NTGR Net Savings Realization Rate Value Unit Value Value Value Unit Energy Savings Tracked Savings by E1 26.115 GWh 0.79 20.719 GWh Evaluation...
AI summary Table 29 compares tracked and evaluated energy and peak demand savings from 2024 custom programs. It highlights differences between gross and net savings, along with realization rates, showing that evaluation results often exceed tracked savings, with realization rates ranging from 90% to 109%.
8 Custom Key Findings and Recommendations The main objectives of the 2024 Custom evaluation were as follows: - › Calculate gross and net results, namely electrical first-year and lifetime energy savings, peak demand savings, as well as avo...
AI summary The 2024 Custom evaluation aimed to calculate energy savings, GHG emissions, and collect perspectives on New Construction participation motivations and barriers. Findings and recommendations are provided, with general and service-specific insights outlined in Appendix XIV.
General Custom Key Findings and Recommendations 2024 Custom - Finding: Custom net electrical energy and peak demand savings surpassed targets in 2024. Custom achieved 39.951 GWh in net electrical energy savings and 5.225 MW in net peak dem...
AI summary Custom program exceeded 2024 energy and peak demand savings targets by 48% and 28%, respectively. Participation decreased in Retrofit and Building Optimization but increased in New Construction. Evaluator adjustments led to varying ARs across services. Free-ridership dropped for Retrofit and New Construction. Evaluated savings were 8-5% higher than E1's tracking.
shift to NECB 2020 in Nova Scotia. Builders will need to adjust designs, plan for higher efficiency technologies and higher upfront costs, and work closely with energy modellers under the new code. Nova Scotia will phase in Tiers 1, 2, and...
AI summary Nova Scotia will phase in NECB 2020 tiers from 2025–2029, requiring builders to adopt higher efficiency technologies and upfront costs. Recommendations include enhancing outreach to builders, updating program guidelines to align with NECB 2020, and aligning incentives with code tiers. The logic model is deemed outdated and needs revision to reflect current program activities and barriers.
Figure 10: 2024 SEM Participation Process Summary Eligibility Check, Memorandum of Understanding (MOU), and Kick-off Meeting - Once approved, eligible participants must first sign a MOU that outlines the project scope, participant requirem...
AI summary The 2024 SEM Participation Process involves eligibility checks, MOUs, energy team formation, policy development, energy improvement events, and savings verification. Participants receive performance-based incentives ($0.04-$0.06/kWh) to achieve energy savings targets of 4.222 GWh and 0.470 MW. The process includes M&V, weekly calls, and energy management planning.
Table 30: Implementation Status of Past Recommendations for SEM # Recommendations Status Comments 2023- SEM-R1 Consider including plant-level key performance indicators (KPIs) and tracking their progression since program component inceptio...
AI summary Table 30 outlines the implementation status of past recommendations for Strategic Energy Management (SEM). Three recommendations are discussed, with two in progress and one marked as complete. The recommendations focus on tracking performance indicators, project implementation, and communication of energy management benefits.
10 SEM Evaluation Approach The 2024 SEM evaluation comprised a comprehensive impact evaluation. The main objectives of the SEM evaluation were as follows: › Calculate SEM gross and net results, namely electrical first-year and lifetime ene...
AI summary The 2024 SEM evaluation aimed to calculate gross and net results, including energy savings, peak demand savings, and avoided GHG emissions. The Evaluator identified key research questions and outlined methods and sample sizes in Table 31.
Table 31: 2024 SEM Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate gross results › Are the data in the tracking sheet complete, accurate, and consistent? › Are the gross savings for each project accuratel...
AI summary Table 31 outlines the 2024 SEM Evaluation Approach, focusing on calculating gross and net results from energy management initiatives. It includes evaluation objectives, research questions, and methodologies such as tracking sheet audits, project file reviews, and calculation of energy savings and GHG emissions.
Calculations Using Evaluation Results Building on all the above methods and collected data, the Evaluator calculated the first-year and lifetime gross energy and peak demand savings as per the calculation methodology presented in Section [...
AI summary The Evaluator calculated first-year and lifetime gross energy and peak demand savings using a methodology outlined in Section 11, building on prior data collection and analysis methods.
11.2.1 Project Review Findings The Evaluator reviewed the calculation methodologies for the seven projects based on project documentation and information from interviews with participants and the Service Provider. All but two projects used...
AI summary The Evaluator reviewed seven projects' savings calculation methodologies, noting most used a bottom-up M&V approach consistent with Custom Retrofit standards. A top-down approach was deemed appropriate for whole-facility measures where component-level monitoring was impractical. The Service Provider's methodology selection aligned with approved M&V procedures.
Strategic Energy Management 67 40 The 2024-2025 DSM MA is a reference document that provides an in-depth review of all parameters necessary to calculate the annual and lifetime gross energy and peak demand savings of most prescriptive meas...
AI summary The 2024-2025 DSM MA serves as a reference document for evaluating energy and peak demand savings from EfficiencyOne's DSM program portfolio. It includes effective useful life values for all measures offered and is referenced for evaluations during the 2023-2025 DSM cycle. A reference is made to a 2014 Cost of Service Study Progress Update by the Nova Scotia Utility and Review Board.
Table 33: Evaluated 2024 SEM Gross GHG Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 4.478 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annual GHG Emissio...
AI summary Table 33 presents evaluated 2024 SEM gross GHG emission reductions, including gross energy savings, the Nova Scotia-specific GHG emissions factor for electricity production, and the resulting gross annual GHG emission reductions in tonnes of CO2 equivalent.
11.3.1 Evaluated Net Savings Since spillover and free-ridership effects were considered nil, net SEM impacts are equal to the gross savings generated by the program component. The 2024 SEM net electrical energy and peak demand savings were...
AI summary The 2024 SEM program achieved 4.478 GWh of net electrical energy savings and 0.538 MW of peak demand reductions, exceeding targets by 6% and 14% respectively. These savings corresponded to 2,114 tonnes of annual CO2 eq GHG reductions, with no spillover or free-ridership effects considered.
11.4 Realization Rate A comparison of the electrical energy and peak demand savings established through this evaluation and those tracked by E1 is presented in [Table](#page-40-0) 34 below. It also includes the realization rate, representi...
AI summary This section compares electrical energy and peak demand savings evaluated in this proceeding with those tracked by E1, including the realization rate, which is the ratio of evaluated net savings to tracked net savings. References include a 2024 report and Emera Inc.'s 2023 Annual Report.
12 SEM Key Findings and Recommendations As mentioned previously, the main objectives of the 2024 SEM evaluation were as follows: › Calculate SEM gross and net results, namely electrical first-year and lifetime energy savings, peak demand s...
AI summary The 2024 SEM evaluation found that SEM exceeded its net electrical energy and peak demand savings targets by 6% and 14%, respectively. Participation remained stable with 12 participants, and M&V methodologies showed improved accuracy, particularly for peak demand savings. The Evaluator noted no recommendations for the program.
Table 35: Overall 2024 Custom Incentives Participation and Evaluated Savings Participa ation Level Gross Gross Savings Net S Savings Value Unit Value Unit Value Unit Value Custom ' ' • Energy Savings 49.825 GWh 0.80 39.951 GWh Lifetime Ene...
AI summary Table 35 summarizes the participation and evaluated savings from the 2024 Custom Incentives program. The program exceeded its targets for net electrical energy and peak demand savings. The data includes energy savings, lifetime energy savings, peak demand savings, GHG emission reductions, and energy use life (EUL).
EfficiencyOne
AI summary The document text consists solely of the heading 'EfficiencyOne' from a Nova Scotia regulatory proceeding, with no further content or context provided in the chunk.
B. Awareness and Participation B1. Without commenting on your participation in the Custom Retrofit program for now, why did your organization decide to implement the energy efficiency upgrades we are discussing today? [DO NOT READ] Specify...
AI summary The section explores organizational motivations for energy efficiency upgrades and awareness of the Custom Retrofit program, focusing on reasons for participation and initial exposure to the program.
Factor [READ AND RANDOMIZE] Responses a. The program financial incentive for the [Investigation or Feasibility Study]. Response 98 Don't Know Refused b. The program financial incentive for the implementation of the energy efficiency measur...
AI summary The text presents a series of questions related to a program's financial incentives, energy efficiency measures, and technical and non-technical support provided by Efficiency Nova Scotia staff. Most responses are 'Don't Know' or 'Refused', indicating a lack of information or unwillingness to provide details.
[READ AND ROTATE (D1 + D2 TO D3) AND (D4 + D5 TO D7) SEQUENCES] - D1. Before participating in the Custom Retrofit program for this project, had your organization already participated in this program or in other Efficiency Nova Scotia progr...
AI summary The document outlines survey questions assessing prior participation in Efficiency Nova Scotia programs and the influence of promotional materials on energy efficiency project decisions. It evaluates whether past involvement or exposure to promotional content prompted technical evaluations and cost-effectiveness considerations.
E. Spillover - E1. Since taking part in the Custom Retrofit program, have you implemented any additional energy efficiency measures outside of the program? - 1. Yes - 2. No [THANK AND TERMINATE] - 98. Don't know [THANK AND TERMINATE] - 99....
AI summary The survey explores whether participants in the Custom Retrofit program implemented additional energy efficiency measures outside the program, their financing sources, and the influence of the program on these decisions. It also requests details on measures and reasons for not using Efficiency Nova Scotia programs.
APPENDIX II Retrofit Algorithm for Free-Ridership Calculation Question Answer Score 98/99) Don't know/Refused EMPTY C5 [ASK IF $ ≥0] As part of its Custom Retrofit program, Efficiency Nova Scotia gave your organization a $ incentive for th...
AI summary This section of the document outlines a retrofit algorithm for free-ridership calculation, focusing on the Custom Retrofit program by Efficiency Nova Scotia and the use of study incentives for energy efficiency projects. It includes a series of questions and scoring mechanisms to assess the impact of these incentives.
Cross-Influence Question Answer Score Cross-Influence D1 Before participating in the Custom Retrofit program for this project, had your organization already participated in this program or in another Efficiency Nova Scotia program? 1) Yes,...
AI summary This section of the document contains a survey question regarding participation in Efficiency Nova Scotia programs and the impact of prior participation on decision-making processes related to energy efficiency projects.
APPENDIX IV Retrofit and Building Optimization Tracking Sheet Audit This appendix presents the main results of the tracking sheet audit performed by the Evaluator, which was aimed at: - › Verifying that all data fields required for the eva...
AI summary This appendix details the results of a tracking sheet audit conducted by the Evaluator to verify the accuracy and completeness of data submitted by EfficiencyOne (E1) for the Retrofit and Building Optimization programs. The audit ensured consistency in calculation methods and parameters used to determine energy and peak demand savings.
Table 1: 2024 Retrofit Corrected Tracked Savings Program Component Result Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Gross Energy Savings – at the Generator 26.198 GWh 26.115 GWh -0.32% Gross Demand Sav...
AI summary The tables present 2024 corrected tracked savings for energy and demand from retrofit and building optimization programs. There were no substantial differences between tracked and corrected values, with minor changes attributed to adjustments in line loss factors.
ECONOLER Efficency Nova Scotia On-Site Visit Protocol - 2024 1. General Information Virtual Visit Date: Team: Contact Name: Contact Title: Role on the projet: Company Name: Facility Name: Address: Consultant: Administer FR/SO? Alternate FR...
AI summary This document outlines an on-site visit protocol for Efficiency Nova Scotia in 2024, focusing on the collection of facility and project information, as well as M&V (Measurement and Verification) plans and documentation. It includes sections for general information, facility description, project description, and M&V documentation.
Efficency Nova Scotia Measure Review Protocol - 2024
AI summary The document presents the Efficency Nova Scotia Measure Review Protocol for 2024, outlining procedures for reviewing energy efficiency measures. It is part of a regulatory proceeding related to energy efficiency programs and their evaluation.
Operating Schedule Include notes on schedule and seasonal variations. The operating schedule corresponds to the typical one (non-COVID). - 6. Is the M&V period appropriate? (Y/N) - a. Do both the baseline and reporting periods cover all ra...
AI summary The Operating Schedule section includes questions about the appropriateness of the M&V period, focusing on whether it covers all operational ranges, occurs near the implementation of an energy efficiency project, and captures seasonal effects.
Savings calculation approach - Projects with M&V 5. Are the M&V boundaries capturing all the energy consumption that's impacted by the project? (Y/N) 7. Are M&V results measured in a short period extrapolated to annual results appropriatel...
AI summary The document discusses the evaluation of M&V (Measurement and Verification) boundaries, extrapolation methods, regression validity, and the impact of COVID on energy savings calculations. It includes questions to assess the accuracy of savings calculations and the consideration of seasonal load profiles and peak demand savings.
Tracked Savings Calculation For this project, an E1 project engineer created an Excel spreadsheet to calculate electrical energy consumption for all four tanks for both the base cases and efficient cases, using the refrigeration unit perfo...
AI summary An E1 project engineer developed an Excel spreadsheet to calculate electrical energy consumption and peak demand savings for refrigeration units, using manufacturer data, weather conditions, seawater temperatures, and on-site measurements to validate heat exchange efficiency during winter peak demand periods (December-February, 5-7 pm).
Revised Savings Calculation The Evaluator found that the assumptions and the analysis performed by E1 were generally sound. Moreover, after reviewing the savings calculations, the Evaluator found mistakes in some of the Excel formulas used...
AI summary The Evaluator found E1's analysis generally sound but identified errors in refrigeration load formulas using incorrect target temperatures, leading to downward adjustments in consumption and demand savings. The Effective Useful Life (EUL) was also revised from 15 to 11 years due to varying unit lifespans from mixed refrigerant upgrades.
Introduction – Telephone IDI I am with Narrative, and we are conducting an evaluation of the Efficiency Nova Scotia Custom New Construction program. This interview should take about 15-20 minutes. Is this still a good time for you? The pur...
AI summary Narrative is conducting an evaluation of Efficiency Nova Scotia's Custom New Construction program through telephone interviews. The purpose is to understand motivations for building energy-efficient structures exceeding code requirements, with confidentiality assured and no impact on incentive amounts.
Introduction – Online Survey Narrative Research and Econoler are currently conducting a formal evaluation of the Efficiency Nova Scotia Custom New Construction program. Your organization recently entered into an agreement in [CPA ACCEPTED...
AI summary Narrative Research and Econoler are evaluating Efficiency Nova Scotia's Custom New Construction program. The survey seeks to understand participants' decisions in building energy-efficient 'better-than-code' buildings, including material and equipment choices exceeding code requirements.
A. Identifying Key Decision-makers - A1. [SINGLE RESPONSE] Did you play a key role in your organization's decision to build an energy efficient, or better-than-code, building. - 1. Yes - 2. No - 98. I am unsure - A2. [IF [A1=](#page-71-0)Y...
AI summary This section includes survey questions aimed at identifying key decision-makers involved in building energy-efficient or better-than-code buildings. Respondents are asked about their role in the decision-making process, whether others in their organization were involved, and to provide contact information for key individuals.
ciency Nova Scotia? - 1. Very confident - 2. Somewhat confident - 3. Not very confident - 4. Not at all confident - 98. I am unsure - 99. I prefer not to say - C4. [SINGLE RESPONSE] Which one of the following best represents the impact of...
AI summary The text presents survey questions assessing stakeholders' confidence in Efficiency Nova Scotia and the financial impact of its incentives on building projects. Respondents are asked about budget adherence, project viability, and likelihood of hiring energy consultants without incentives.
CAPTURE VERBATIM - 98. I am unsure - 99. I prefer not to say - C10. [SINGLE RESPONSE PER STATEMENT; DO NOT RANDOMIZE] Rate the influence of the following factors in your decision to build a better-than-code building. - a. The program finan...
AI summary A survey question asks respondents to rate the influence of factors like financial incentives, energy modeling insights, and technical assistance from Efficiency Nova Scotia staff on their decision to build better-than-code buildings, using a 0-10 scale.
A. Identifying Key Decision-makers - A1. We hope to interview the person who played a key role in the decision to build a better-than-code building. Were you a key decision-maker? - 1. Yes - 2. No - 98. Don't know - 99. Refused - A2. [IF A...
AI summary This section outlines a survey methodology to identify key decision-makers involved in constructing buildings exceeding code standards. It asks respondents about their role in the decision-making process and requests contact information for other stakeholders if applicable.
- B10. [IF B7 = 2] Without the incentive from Efficiency Nova Scotia or the expertise provided by the energy modeler, what is the likelihood that you would have designed a building with as many efficiency measures as you included ? - 1. De...
AI summary The questions assess the impact of Efficiency Nova Scotia's incentives and technical support on the inclusion of energy efficiency measures in new buildings, focusing on free-ridership by evaluating whether participants would have implemented similar measures without program support.
D. Barriers and Motivations - D1. What were your primary concerns when you were considering building a high-efficiency building? [DO NOT READ. MULTIPE RESPONSE] - 1. (Cost of energy efficient technologies) - 1. (Cost of energy modeling) -...
AI summary The section explores barriers to high-efficiency building practices, including concerns about technology costs, profitability, construction speed, expertise gaps, and performance risks. It also inquires about uninstalled efficiency technologies and their specifics, aiming to identify motivations and obstacles in energy-efficient construction.
- b. If less than 8, please explain the reason(s) for your score. Aspects of the program [READ AND RANDOMIZE] Score Reason 1. The overall program Response 98 DK99 Ref _97 N/A 2. The responsiveness of Efficiency Nova Scotia employees to you...
AI summary The text includes a survey assessing the Efficiency Nova Scotia program, covering aspects such as program responsiveness, approval speed, and value. It also explores challenges faced and suggestions for improvement. Additionally, it addresses the importance of reducing GHG emissions and the influence of electrification on participation in construction programs.
G. Building codes - G1. In April 2025, Nova Scotia will adopt the National Energy Code of Canada for Buildings 2020 (NECB2020). Would you say that the adoption of NECB2020 increases, decreases, or has no impact on your likelihood to partic...
AI summary Nova Scotia plans to adopt NECB2020 in 2025, prompting a survey on its impact on New Construction program participation. Respondents are asked whether the code adoption would increase, decrease, or have no effect on their likelihood to participate, with options for qualitative justification.
B. Barriers to Participation and Motivations - B1. In your experience, why are some builders NOT completing an energy model for their building? [DO NOT READ. MULTIPE RESPONSE] - 1. (Cost energy efficiency upgrades are too expensive) - 2. (...
AI summary The text explores barriers preventing builders from completing energy models, including cost concerns, lack of expertise, and insufficient awareness, alongside motivations such as cost reduction, compliance, and financial incentives. It highlights conflicting priorities between minimum code requirements and energy efficiency goals.
C. GHG Emissions & Electrification - C1. Have you had discussions with your builder clients about reducing GHG emissions or about electrification? - 1. Yes, reducing GHG emissions - 2. Yes, electrification - 3. No - 98. Don't know - 99. Re...
AI summary The section includes survey questions targeting builders and industry professionals about discussions with clients on reducing GHG emissions and electrification. It explores clients' concerns and how these issues influence their decisions regarding building energy performance, including fuel choice between electric and gas heating.
E. Program Awareness and Participation - E1. Have you ever heard of the New Construction program from Efficiency Nova Scotia? - 1. Yes - 2. No - 98. Don't know - 99. Refused
AI summary This section of the document asks respondents whether they are aware of the New Construction program from Efficiency Nova Scotia, with response options including 'Yes', 'No', 'Don't know', and 'Refused'.
Table 7: Overview of Data Collection Activity Descriptor This Instrument Instrument Type Semi-directed in-depth interview Estimated Time to Complete 45 min for Program Manager, 45 min for BDM Target Audience E1 program staff: › Commercial...
AI summary This document outlines data collection activities for a program evaluation, focusing on interviews with program staff to explore opportunities for expanding participation and updating service logic. Research questions address participation trends, barriers, and relationships with modelers.
C. Program logic model C1. [PROGRAM MANAGER ONLY] Can you walk through the program logic model, starting with what you see as the main market barriers to efficient new buildings and how the program addresses those barriers?.
AI summary The Program Manager is asked to explain the program logic model, focusing on market barriers to efficient new buildings and the program's strategies to address these barriers. The response is not provided in the text.
Efficiency Nova Scotia Simulation Model Review Protocol Custom New Construction 1. General Information Review Date: Contact Name: Project ID: Contact Title: Project Type: Contact Phone: Project Status: Email: Project Name: Address: Project...
AI summary This document outlines a protocol for reviewing the simulation model used by Efficiency Nova Scotia for custom new construction projects. It includes sections for general information, facility operation schedules, and adjustments to the energy model based on specific measures.
1 Results General Overview - Check savings (in %) for each end use and identify where the major savings lie. Crosscheck with the energy efficiency measure list to validate if the savings claimed make sense. - Verify GJ/m2 and check benchma...
AI summary The text emphasizes verifying energy savings percentages against efficiency measures and checking energy intensity metrics (GJ/m2) with benchmarking data. It highlights the need to account for building-specific factors like underground parking to explain discrepancies in energy usage comparisons.
2 Envelope Review - Check envelope resistance value (wall/fenestration/roof/etc.) and validate with shop drawings and construction details. Make sure that effective R/RSI – U/USI values are used in the simulation. - Pay particular attentio...
AI summary The Envelope Review outlines procedures to verify building envelope performance, including checking insulation values against construction details, addressing curtain wall inefficiencies, validating fenestration-to-wall ratios, and ensuring compliance with code specifications in simulations.
Table 1: Participant Interview Questionnaire and Free-ridership Algorithm Question Answer Score A1 We hope to interview the key decision-makers that played a key role in the decision to build a better than-code building. Were you a key 1)...
AI summary This table outlines a participant interview questionnaire focused on identifying key decision-makers involved in building better-than-code buildings, with specific questions about their roles and other potential decision-makers.
Table 1: 2024 Custom Corrected Tracked Savings Program Component Result Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Gross Energy Savings – at the Generator 20.855 GWh 20.900 GWh 0.22% Gross Demand Saving...
AI summary The table presents 2024 custom corrected tracked savings for energy and demand, showing negligible differences between tracked and corrected values, attributed to adjustments in line loss factors.
This appendix summarizes all the recommendations made by the Evaluator as part of the Custom evaluation. Section Recommendations Executive Summary 2024 New Construction Recommendation #1: Review the demand savings script used for projects...
AI summary The appendix outlines recommendations for improving energy efficiency programs in Nova Scotia, including enhancing modelling accuracy, increasing M&V requirements, recruiting energy modellers, aligning with NECB 2020, and updating program guidelines to address barriers and improve participation.
Table 1: 2024 SEM Corrected Tracked Savings Program Component Result Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Gross Energy Savings at the Generator 4.474 GWh 4.480 GWh 0.12% Gross Peak Demand Savings...
AI summary The table shows minor changes in electrical energy and peak demand savings for the 2024 SEM Corrected Tracked Savings, attributed to adjustments in line loss factors. The differences are small, with energy savings increasing by 0.12% and peak demand savings by 0.18%.
- € Strategic Energy Management Efficiency Nova Scotia ECONOL≣R Project Review Protocol 1. General Information Interview/Site Visit Date: Project ID: NSPI Rate Code: Company Name: Address: Team: Contact Name: Contact Title: Phone: Email: L...
AI summary The document outlines the Strategic Energy Management (SEM) Efficiency Nova Scotia Project Review Protocol, focusing on energy consumption drivers, participation history, and measurement and verification (M&V) protocols. It includes sections for baseline and reporting periods, regression analysis, and energy savings calculations.
ABBREVIATIONS BER Business Energy Rebates BNI Business, non-profit and institutional CDI Commercial Direct Install DC direct current DIY Do-it-yourself DSM Demand-side management E1 EfficiencyOne EER energy efficiency ratio ENS Efficiency...
AI summary This section defines abbreviations used in the regulatory proceeding, including terms related to energy programs, organizations, and technical metrics. Key entities include Nova Scotia Power and Efficiency Nova Scotia, with topics covering energy rebates, demand-side management, and utility regulations.
Evaluation Approach The purpose of the 2024 evaluation was to calculate gross and net results of the program components, namely electrical first-year and lifetime energy savings, peak demand savings, as well as avoided greenhouse gas (GHG)...
AI summary The 2024 evaluation aimed to calculate gross and net results of program components, including electrical first-year and lifetime energy savings, peak demand savings, and avoided greenhouse gas emissions. Table 1 outlines the types of evaluations conducted and their corresponding methodologies.
Table 1: Summary of 2024 Direct Installation Program Evaluation Program Eva aluation Type Mothodology Component Impact Process Market Market Methodology Small Business Energy Solutions Condensed - - Tracking sheet audit Unitary savings rev...
AI summary The table summarizes the 2024 Direct Installation Program Evaluation, focusing on the Small Business Energy Solutions program. It outlines the evaluation methodology, including tracking sheet audits, savings reviews, and GHG emission reduction calculations.
Table 2: Overall 2024 Direct Installation Participation and Evaluated Savings 1 Participation Level Gross Savings NTGR Net Sa avings Value Unit Value Unit Value Value Unit Energy Savings 673 2 Units 13.459 GWh 0.81 10.854 GWh Lifetime Ener...
AI summary Table 2 presents the 2024 participation and evaluated savings from direct installation programs, including energy savings, lifetime energy savings, peak demand savings, and GHG emission reductions. The table also includes the net-to-gross ratio (NTGR) for these savings, with an indication that 741 of the rebated units were part of the CDI Pilot projects.
Table 3: Comparison of 2024 SBES Tracked and Evaluated Savings at the Generato[r](#page-129-1) 3 Gross Savings Net Savings Realization Value Unit NTGR Value Unit Rate Energy Savings Tracked Savings by E1 12.936 GWh 0.81 10.426 GWh 104% Eva...
AI summary Table 3 compares the tracked and evaluated energy and peak demand savings from the 2024 SBES and CDI Pilot programs. It shows gross and net savings, along with realization rates, indicating that evaluated savings slightly exceed tracked savings for both energy and peak demand.
INTRODUCTION EfficiencyOne (E1), an independent, non-profit organization, is responsible for helping Nova Scotians improve the energy efficiency of their homes and workplaces by designing, marketing, and delivering demand-side management (...
AI summary EfficiencyOne (E1) is an independent, non-profit organization responsible for delivering demand-side management (DSM) programs in Nova Scotia through the Efficiency Nova Scotia (ENS) franchise. E1's DSM activities are regulated by the Nova Scotia Utility and Review Board (NSUARB), and it receives funding from Nova Scotia Power (NS Power) ratepayers. The 2024 evaluation report focuses on the Direct Installation program, specifically the Small Business Energy Solutions (SBES) component, using parameters like net-to-gross ratios (NTGRs) from previous evaluations.
Table 4: Type of Evaluation Conducted for SBES, 2024 Program 2024 Program Component Process Market Impact Direct Installation SBES - - Condensed For each program, the Evaluator prepared a DSM evaluation report presenting key findings, elec...
AI summary Table 4 outlines the type of evaluation conducted for the Small Business Energy Solutions (SBES) program in 2024. The Evaluator prepared a DSM evaluation report highlighting first-year and lifetime energy savings, peak demand savings, and avoided GHG emissions.
1.1 SBES Description SBES offers incentives and resources to Nova Scotia small businesses to encourage them to make energy efficient upgrades in their facilities. To be eligible, businesses must annually consume less than 600,000 kW[h](#pa...
AI summary SBES provides energy efficiency incentives and on-bill financing for Nova Scotia small businesses with under 600,000 kWh annual consumption. It offers two participation paths: Audit (with no-cost energy audits) and DIY (self-directed upgrades). Rebates depend on technology factors, and the program aims for 10.592 GWh energy savings and 2.558 MW peak demand reduction in 2024. The Commercial Direct Install pilot remains in testing.
2 SBES Evaluation Approach The 2024 SBES evaluation consisted of a condensed impact evaluation, which also covered the Commercial Direct Install (CDI) pilot. The main objectives of the 2024 SBES evaluation were as follows: - › Calculate gr...
AI summary The 2024 SBES evaluation focused on calculating energy savings and GHG emissions reductions from the SBES and CDI pilot programs. The evaluation included objectives such as calculating gross and net results and spillover levels using non-participant surveys. Research questions and methods were outlined in a table.
Table 6: 2024 SBES Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate gross results › Are the data in the tracking sheet complete, accurate, and consistent? › What are the formulas and savings parameters for...
AI summary Table 6 outlines the 2024 SBES Evaluation Approach, detailing objectives, research questions, and methodologies for evaluating the Small Business Energy Solutions program. It includes calculating gross and net results, collecting non-participant perspectives, and conducting a tracking sheet audit.
3.3 Past Energy Efficiency Projects Among Small Businesses
AI summary This section reviews past energy efficiency initiatives targeting small businesses in Nova Scotia, highlighting programs like SBES (Small Business Energy Solutions) and BER (Business Energy Rebates) administered by ENS (Efficiency Nova Scotia). It discusses outcomes such as cost savings, GHG reductions, and challenges including participation rates and program evaluation complexities.
3.3.1 Energy Efficiency Project – History Non-participants are almost equally divided into those who had implemented energy efficiency projects without financial assistance from E1 (47%)[12](#page-139-4) and those who had not (50%). Of tho...
AI summary Non-participants in the Energy Efficiency Project are split between those who implemented projects without E1 financial assistance (47%) and those who did not (50%). Of 14 non-participants, projects were implemented in 2020-2024, with four prior to 2020. Figure 7 illustrates this distribution.
3.3.2 Energy Efficiency Project – Motivations Among the eight non-participants who had implemented energy efficiency projects between 2020 and 2024, five said their reason for installing energy efficiency upgrades was to replace equipment...
AI summary Of eight non-participants who implemented energy efficiency projects (2020-2024), five replaced end-of-life equipment with more efficient alternatives, two upgraded functional equipment prematurely, and one added supplementary equipment. This highlights equipment lifecycle management and efficiency improvements as primary motivations.
4.2 Gross Savings Gross savings correspond to the change in energy consumption resulting from actions taken by participants regardless of their reasons for participating.[13](#page-141-4) For each SBES Audit or DIY project, E1 calculates g...
AI summary Gross savings are calculated based on changes in energy consumption from participant actions using methods like the CIRx Screening Tool or custom calculations by auditors. The CDI pilot uses unitary algorithms.
4.2.1 Unitary Energy and Peak Demand Savings Savings for SBES Audit and DIY projects are established through calculations using data specific to each project. The 2024-2025 DSM MA provides a detailed description of inputs, references, and...
AI summary The 2024-2025 DSM MA outlines changes to unitary savings parameters for SBES measures, including updates to SEER, EER, and PCF values. The Evaluator validated these changes for top measures, with other parameters unchanged. The CIRx tool provides methodology details.
Table 7: 2024 SBES Equivalent EUL and Gross Lifetime Unitary Savings Values Product Tracked Equivalent EUL [years] Evaluated Equivalent EUL [years] Evaluated Gross Lifetime Unitary Savings [kWh] LED Lamps 2.0 1.0 211 LED Nightlights 22.8 1...
AI summary Table 7 provides equivalent energy use life (EUL) and gross lifetime unitary savings values for various energy efficiency products in 2024, including LED lamps, air-source heat pumps, and photovoltaic systems. These values are used to assess the effectiveness of these products in energy savings.
Table 8: Evaluated 2024 SBES Gross Energy and Peak Demand Savings – Audit Path Category of Measure Commercial Kitchen DHW HVAC Lighting Laundry Refrigeration Envelope Total for All Categories Energy Savings Gross Energy Savings Without Adj...
AI summary Table 8 presents evaluated 2024 SBES gross energy and peak demand savings based on an audit path. It breaks down energy savings by category, including adjustments, line loss factors, and lifetime energy savings at the generator level. Peak demand savings are also detailed, with adjustments and line loss factors applied.
Table 11: Evaluated 2024 SBES Gross Energy and Peak Demand Savings – All Paths Program Path Audit DIY CDI Pilot Total Energy Savings Gross Energy Savings – at the Meter (GWh) 0.388 12.077 0.124 12.589 Line Loss Factor 1.0746 1.0688 1.0897...
AI summary Table 11 evaluates the 2024 SBES gross energy and peak demand savings across different program paths, including audit, DIY, and CDI Pilot. The table shows energy and peak demand savings at the meter and generator levels, along with line loss factors and effective useful life. Evaluated gross savings are approximately 4% and 6% higher than tracked values, mainly due to corrected adjustment ratios and line loss factors.
Figure 9: 2024 SBES Tracked and Evaluated Gross Energy Savings at the Generator As presented in [Table](#page-148-3) 12 below, GHG emission reductions were calculated by applying the Nova Scotiaspecific factor[18](#page-147-2) for GHG emis...
AI summary The document discusses the calculation of GHG emission reductions based on energy savings from the Small Business Energy Solutions (SBES) program in 2024, using a Nova Scotia-specific factor derived from Nova Scotia Power's 2023 emissions data and total electricity generation.
Table 12: Evaluated 2024 SBES GHG Gross Emission Reductions Total Gross Energy Savings – at the Generator (GWh) 13.459 Nova Scotia-specific GHG Emissions Factor for Electricity Production (tonnes of CO2 eq/GWh) 472.2 Gross Annual GHG Emiss...
AI summary Table 12 presents evaluated 2024 SBES GHG gross emission reductions, showing 13.459 GWh of gross energy savings, a 472.2 tonnes of CO2 eq/GWh emissions factor, and 6,356 tonnes of CO2 eq annual emission reductions.
4.3.3 Non-Participant Spillover Using the approach described in Section 2, the Evaluator assessed non-participant spillover from a sample of 30 commercial customers. Respondents were asked if they had implemented energy efficiency projects...
AI summary The Evaluator assessed non-participant spillover by surveying 30 commercial customers, finding that 14 implemented energy efficiency measures without E1's assistance, with minimal influence from E1's actions. The non-participant spillover level was determined to be nil.
Net savings are defined as the energy use reductions that are specifically attributable to SBES. Program component net impacts were estimated by applying the above NTGRs to the revised gross savings by using the following equation: Net Sav...
AI summary The document defines net savings as energy use reductions attributable to the Small Business Energy Solutions (SBES) program and calculates net energy savings using the Net Total Gross Reduction (NTGR) equation. The results show 5,125 tonnes of CO2 eq in annual GHG emission reductions.
Table 15: Evaluated 2024 SBES Net Energy and Peak Demand Savings Measure Category Audit DIY CDI Pilot Total Energy Savings Gross Energy Savings – at the Meter (GWh) 0.388 12.077 0.124 12.589 NTGR 0.88 0.80 1.00 - Net Energy Savings – at th...
AI summary Table 15 evaluates the 2024 SBES program's net energy and peak demand savings. The program exceeded its energy savings target by 2% but fell short of its peak demand savings target by 16%. The data includes gross and net savings at both the meter and generator levels, as well as lifetime energy savings and peak demand savings metrics.
Table 16: Comparison of 2024 SBES Tracked and Evaluated Savings at the Generator[19](#page-151-3) Gross Savings NTGR Net Savings Realization Rate Value Unit Value Unit Energy Savings Tracked Savings by E1 12.936 GWh 0.81 10.426 GWh 104% Ev...
AI summary Table 16 compares the tracked and evaluated savings from the 2024 SBES program. Evaluated net energy savings were 4% higher and peak demand savings were 6% higher than tracked values, due to corrected adjustment ratios and line loss factors.
5 SBES Key Findings and Recommendations The main objectives of the 2024 SBES evaluation were as follows: - › Calculate gross and net SBES results, namely electrical first-year and lifetime energy savings, peak demand savings, as well as av...
AI summary The 2024 SBES evaluation found that the program met its net electrical energy savings target (10.854 GWh, 2% over target) but missed its peak demand savings target (2.155 MW, 16% short). Evaluated savings exceeded E1's tracked results by 4% and 6% respectively. Participation rose 53% year-over-year, with DIY Path dominating. Spillover surveys found no non-participant impact.
Table 17: Overall 2024 Direct Installation Participation and Evaluated Savings[20](#page-153-4) Participation Level Gross Savings Net Savings Value Unit Value Unit Value Value Unit SBES Energy Savings 61,673 Units 13.459 GWh 0.81 10.854 GW...
AI summary Table 17 presents the 2024 participation and evaluated savings from the Small Business Energy Solutions (SBES) program, including energy savings, peak demand savings, GHG emission reductions, and equivalent energy use life. The data includes gross and net savings, with net savings being approximately 80-81% of gross savings.
a) SBES Small Business Energy Solutions The program offers eligible small businesses in Nova Scotia access to energy assessments, energy efficiency contractors, rebates and financing for the installation of energy efficient upgrades. [Retr...
AI summary The Small Business Energy Solutions (SBES) program provides eligible small businesses in Nova Scotia with energy assessments, access to energy efficiency contractors, rebates, and financing for energy-efficient retrofits. Rebates cover up to 80% of project costs, and pre-approval is required for upgrades.
B. Non-Participant Spillover - B1. Have you implemented energy efficiency projects or installed more efficient equipment aimed at generating electricity savings in your establishment in the last five years without receiving financial assis...
AI summary The question asks whether respondents implemented energy efficiency projects without financial assistance from Efficiency Nova Scotia over the past five years, with options to confirm or skip to demographics. It focuses on non-participant actions in energy efficiency initiatives.
B3. Which energy efficiency upgrades did you install? [PUT CODES IN ALPHABETICAL ORDER. DO NOT READ. MULTIPLE RESPONSES] - a. Lighting - b. Thermal envelope: Insulation (wall, floor, or roof) - c. Thermal envelope: Doors/windows - d. Heati...
AI summary This section asks respondents to list energy efficiency upgrades installed, with options including lighting, insulation, heating systems, solar panels, and various efficient equipment. It allows for multiple responses and includes a field for specifying other upgrades.
B4. [IF B3 = A) Lighting] What type of lighting did you install? Please indicate how many of each category. [READ AS NEEDED, MULTIPLE RESPONSES – COLLECT QUANTITY IN NUMERIC BOX] a. Interior lighting – T5/T8 fluorescents b. Interior lighti...
AI summary The document includes a table and questions related to energy efficiency upgrades, focusing on lighting types, upgrade descriptions, and the reasons for implementing energy efficiency measures. It also asks about financial assistance received for these upgrades.
[ASK IF A1='No' OR 'Don't know'] I am going to read you a brief description of a rebate program offered by Efficiency Nova Scotia to small businesses in the province. Please indicate if you've heard of this program after hearing the descri...
AI summary The text describes a rebate program offered by Efficiency Nova Scotia for small businesses and asks if the respondent is familiar with it.
Have you implemented energy efficiency projects or installed more efficient equipment aimed at generating electricity savings in your establishment in the last five years without receiving financial assistance from Efficiency Nova Scotia?
AI summary The question asks whether energy efficiency projects or installations of more efficient equipment aimed at generating electricity savings have been implemented in the last five years without financial assistance from Efficiency Nova Scotia.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] When you installed the energy efficiency upgrades you mentioned just now, what was the estimated electricity energy savings associated with the project(s) you completed: Write the a...
AI summary The text asks the respondent to provide the estimated annual electricity energy savings in dollars from the energy efficiency upgrades they completed, specifically inquiring about the period from 2020 through 2024.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] When you installed the energy efficiency upgrades you mentioned just now, what was the estimated electricity energy savings associated with the project(s) you completed?
AI summary The question asks about the estimated electricity energy savings from energy efficiency upgrades installed between 2020 and 2024. It seeks clarification on whether the period '2020 thru 2024' is reflected in B8 and whether 'Don't know' is indicated in B9.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Which of the following situations best describes why you installed the energy efficiency upgrades you outlined just now? OVERALL FULL-TIME WORKERS RENT OWN OR BUSINESS' MAIN ACTIVIT...
AI summary The table provides data on the reasons for installing energy efficiency upgrades, categorizing responses into replacement of equipment at the end of useful life, early replacement of functional equipment, and other reasons. It includes sample sizes and distributions across various business categories.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Did you receive some form of financial assistance for these energy efficiency upgrades to your business? OVERALL FULL-TIME WORKERS RENT OWN OR BUSINESS' MAIN ACTIVITY # >5 5-19 20+...
AI summary This table provides data on the number of businesses that received financial assistance for energy efficiency upgrades between 2020 and 2024. It categorizes responses by business size, ownership type, and primary activity, with a total sample size of 8 businesses.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Thinking about when you decided to install energy efficiency upgrades in your business, please indicate how influential the following factors were using a response of very, somewhat...
AI summary The text asks respondents to evaluate the influence of various factors on their decision to install energy efficiency upgrades in their business, using a scale from very to not at all.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Thinking about when you decided to install energy efficiency upgrades in your business, please indicate how influential the following factors were using a response of very, somewhat...
AI summary The text presents a survey question asking respondents to evaluate the influence of various factors on their decision to install energy efficiency upgrades in their business, using a scale from 'very' to 'not at all'.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Thinking about when you decided to install energy efficiency upgrades in your business, please indicate how influential the following factors were using a response of very, somewhat...
AI summary The text asks respondents to evaluate the influence of various factors on their decision to install energy efficiency upgrades in their business, using a scale from 'very' to 'not at all'.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Thinking about when you decided to install energy efficiency upgrades in your business, please indicate how influential the following factors were using a response of very, somewhat...
AI summary The text asks respondents to evaluate the influence of various factors on their decision to install energy efficiency upgrades in their business between 2020 and 2024.
[ASK IF '2020 THRU 2024' IN B8 OR NOT 'Don't know' IN B9] Thinking about when you decided to install energy efficiency upgrades in your business, please indicate how influential the following factors were using a response of very, somewhat...
AI summary The text asks respondents to evaluate the influence of various factors on their decision to install energy efficiency upgrades in their business, using a scale from 'very' to 'not at all'.
Please indicate your business' annual electrical energy consumption. Please choose from the from the following options: OVERALL FULL-TIME WORKERS RENT OWN OR BUSINESS' MAIN ACTIVITY % >5 5-19 20+ O R L R S W M A O SAMPLE SIZE (#) 30 15 10...
AI summary The text presents a survey asking businesses to indicate their annual electrical energy consumption, with options based on kWh and monthly costs. It includes a table with sample sizes and percentages across different categories such as overall, full-time workers, and business activity.
Table 1: 2024 SBES Corrected Tracked Savings Program Component Results Value Tracked by E1 Corrected Tracked Value Relative Difference Value Unit Value Unit Value SBES – Audit & DIY Gross Energy Savings – at the Generator 12.790 GWh 12.791...
AI summary The table presents corrected tracked savings for the 2024 SBES, showing minimal differences between the values tracked by E1 and the corrected values. The SBES used the same net-to-gross ratios and line loss factors as E1, resulting in similar savings figures. However, without energy and peak demand unitary savings, accurate corrected tracked values are difficult to calculate.
INTRODUCTION EfficiencyOne (E1), an independent, non-profit organization, is responsible for helping Nova Scotians improve the energy efficiency of their homes and workplaces by designing, marketing, and delivering demand-side management (...
AI summary EfficiencyOne (E1) manages Nova Scotia's demand-side management (DSM) programs, including a demand response (DR) program evaluated in 2024. The DR program's available capacity is measured based on potential load reduction during winter events (Dec-Feb), excluding weekends/holidays, with capacity calculated per participant over two hours of DR events.
Table 8: 2024 Residential DR Evaluation Approach Evaluation Objectives Research Questions Methodology Calculate available DR capacity results › Are the data in the tracking sheet complete, accurate, and consistent? › What was the average p...
AI summary This section outlines the evaluation approach for the 2024 Residential Demand Response (DR) program. It includes objectives such as assessing data completeness and calculating available DR capacity, along with methodologies like tracking sheet audits and metering data analysis.
3.2.1 In-service Rates For the Eco Shift Pilot pathway, not all devices participated in each event since participants continued to be registered throughout the season and participants could opt out of any event. Additionally, connectivity...
AI summary The in-service rate for the Eco Shift Pilot pathway includes all enrolled devices, even those that opted out or had connectivity issues, which affects the average available DR capacity. This approach is necessary due to the continuous registration of participants and the use of whole-house data analysis.
Table 9: Eco Shift Pilot Mysa Thermostat In-service Rate per 2023-2024 Event Devices Enrolled per Event Event # Date Number of Enrolled Devices Number of Participating Devices In-service Rate 1 01-09-2024 934 919 98% 2 01-16-2024 947 928 9...
AI summary Table 9 presents the in-service rate of Mysa thermostats during the Eco Shift Pilot events from January to February 2024, showing a consistent participation rate above 96%. The table tracks the number of enrolled and participating devices, as well as the in-service rate per event.
3.2.3 Interactive Effects In a home, interactive effects occur when the implementation of energy efficiency products has an impact on the energy consumption of other elements such as heating and cooling. For the Eco Shift Pilot pathway, al...
AI summary Interactive effects occur when energy efficiency measures impact other home systems like heating/cooling. The Eco Shift Pilot evaluates these effects using whole-house metering data (AMI) over device-level data, capturing interactions with uncontrolled systems (e.g., heat pumps) and offsetting thermostat load reductions.
Table 15: 2024 BNI DR Evaluation Approach Evaluation Objectives Research Questions Methodology Establish available DR capacity results for the DR Aggregator pathway › Are the data in the tracking sheet complete, accurate, and consistent? ›...
AI summary This document outlines the evaluation approach for the 2024 BNI Demand Response (DR) program, focusing on assessing the completeness, accuracy, and consistency of data in the tracking sheet, as well as the application of measurement and verification (M&V) methodologies.
Form of the Regression After reviewing existing literature to identify the most appropriate baseline methodology for this evaluation, the Evaluator decided to use a regression model that considers the time of week and outdoor temperature t...
AI summary The Evaluator chose a regression model incorporating time-of-week and outdoor temperature to establish a baseline for evaluating a smart thermostat program. This approach accounts for temperature impacts on electricity consumption and leverages a large dataset, contrasting with methods using previous similar days. The model's preference stems from its common use in similar programs and ability to differentiate temperature impacts across varying times of the week.
Where: - › , is the calculated baseline load in kW on a specified day of week (D) and hour of day (H), for a given temperature. - › , is the time of the week where D is from 1 to 7 (Sunday to Saturday) and H is from 00 to 24 (midnight to 1...
AI summary The text outlines a methodology for calculating baseline load using heating degree days (HDD) and temperature data, with participants assigned to weather stations based on postal codes to align outdoor temperature with their location.
Consider Variability Account for variability in operations, weather conditions, and other factors that could affect energy usage.
AI summary The text emphasizes the importance of accounting for variability in operations, weather conditions, and other factors that may influence energy usage, highlighting the need for adaptable strategies in energy planning and management.
Presented below is the template used by the Evaluator to review projects to determine evaluated savings. PID Customer Name Agreed Curtailment (kW) Event 1 Event 2 Event 3 Event 4 Event 5 Event 6 Event 7 Event 8 Event 9 Event 10 Average Sav...
AI summary The document presents a template for evaluating energy savings from demand response (DR) projects under the BNI DR program. It includes fields for tracking customer names, curtailment agreements, savings calculations, and adjustments based on guidelines.
Table 1: Measure Assessment Change Log Change Type Section Description Date Update 1.1.1(7) Pipe Insulation Update EUL value 2023-03-09 New Measure 1.1.1(10) Smart Thermostats for Electrical Heating Systems Renamed from the smart thermosta...
AI summary This table outlines changes made to energy efficiency measures, including updates to existing measures and the addition of new ones, such as smart thermostats for electrical heating systems and solar fixtures, with modifications to energy use levels and savings values.
Development and Review Process Savings are established using one or more of the following approaches: Literature reviews of TRMs; metering studies and evaluation reports; engineering calculations; adjustments based on data collected throug...
AI summary The document outlines methods for establishing savings in the Measure Assessment (MA), including data collection approaches and parameter calculation guidelines. It details the use of three-year averages for most parameters, exceptions for rapidly changing data, and updates to specific parameters in the 2024 MA. New measures added in 2024 are also highlighted.
Electrical Energy Savings The following equation is used to calculate electrical energy savings. (ℎ) - = (ℎ) × (1 - + (%)) × " " " - − " (%) 1 The average retired appliance efficiency levels and sizes are likely to evolve overtime as the y...
AI summary The text provides an equation for calculating electrical energy savings, factoring in appliance efficiency and size changes over time. It references the 2024-2025 DSM Measure Assessment, noting that retired appliance efficiency levels evolve as manufacturing years become more recent.
Peak Demand Savings Peak demand savings correspond to the demand savings that coincide in time with the peak demand of the electricity system. The projected electricity peak demand period in Nova Scotia is between 5 p.m. and 7 p.m. from De...
AI summary Peak demand savings refer to electricity demand reductions during Nova Scotia's peak period (5-7 p.m., Dec-Feb non-holiday weekdays). The text outlines a calculation method for quantifying these savings, though the formula is partially obscured in the original document.
Lifetime Energy Savings Lifetime energy savings correspond to the savings that occur over the lifetime of the measures installed. The following equation is used to calculate lifetime energy savings. (ℎ) = (ℎ) × ()
AI summary Lifetime energy savings are calculated over the lifetime of installed measures using a formula (not fully visible in the text). The equation's structure is outlined, but specific variables or parameters are not detailed in the provided excerpt.
Table 2: Included Residential Measures Measure Program Component Lighting LED Lamps EPI Instant Savings LED Fixtures Instant Savings Dimmer Switches Instant Savings Motion Sensors Instant Savings LED Nightlights EPI Solar Fixtures Instant...
AI summary Table 2 lists various residential energy efficiency measures and their associated program components, including lighting, water heating, space heating, appliances, and demand reduction. Each measure is linked to specific programs such as EPI, Instant Savings, Green Heat, and others.
2.1.1 Interactive Effects In a home, the implementation of energy efficient lighting products interacts with the energy consumption of other elements such as heating and cooling. The interactive effects factors for residential lighting pro...
AI summary The text discusses the interactive effects of energy-efficient lighting products in residential homes, particularly how they interact with heating and cooling systems. It references a 1992 study by ADS Groupe-Conseil Inc. for Hydro-Québec and notes that climate data from Nova Scotia and Quebec are comparable, making the study applicable to EfficiencyOne (E1) lighting measures.
Interactive Effects on Heat Pump Heating Since the interactive effects factors for electrical heating are based on a heating system efficiency of 100%, some adjustments are necessary for homes that use a heat pump as a primary heating syst...
AI summary The interactive effects factor for heat pump heating is adjusted from -58.0% to -32.2% by dividing by 1.8 (the COP of a standard mini-split heat pump with HSPF2 Region V of 6.0). This reflects the superior efficiency of heat pumps over 100% electrical heating systems as defined by Federal Energy Efficiency Regulations.
Interactive Effects on Air Conditioning The Hydro-Québec study found that efficient lighting installed in homes with air-conditioning units results in an interactive effects factor for cooling of 3.6%. By analyzing the Hydro-Québec study,...
AI summary The Hydro-Québec study found that efficient lighting in homes with air conditioning creates a 3.6% interactive cooling effect. The Evaluator adjusted COP values from 2.5 to 2.9 (EER 10) due to improved AC efficiency, reducing the factor to 3.1%. The formula used considers 22% of energy savings during cooling and 40% conditioned home area.
Peak Demand The Hydro-Québec report assumes that 10% of the heat is released through exterior walls and ceilings and does not contribute to interactive effects. Since the peak demand period occurs during the heating period when lighting an...
AI summary The Hydro-Québec report assumes 10% heat loss through exterior walls/ceilings in electrically heated homes, leading to a -90% interactive effects factor for peak demand savings. This factor also applies to heat pumps, assuming 100% efficiency during peak cold conditions when heating and lighting systems are active.
Indoor Usage Lighting products cause interactive effects only if installed indoors. To account for this and obtain an overall interactive effects factor for all lighting products, the percentage of products installed indoors, listed in [Ta...
AI summary The document discusses how lighting products installed indoors cause interactive effects, and the method used to calculate an overall interactive effects factor for all lighting products by multiplying the percentage of indoor installations with the corresponding factor.
Table 4: Proportion of Lighting Products Used Indoors Type of Product Program Component % Indoor Source A-type LED Lamps 6 97% 2021, 2022 and 2023 EPI Tracking Sheets Reflector and Decorative LED Lamps 7 (Except PAR38) 100% 2024 EPI Evalua...
AI summary Table 4 outlines the proportion of various lighting products used indoors, based on data from EPI tracking sheets, evaluations, and assumptions. The table highlights that products like A-type LED lamps, reflector and decorative LED lamps (except PAR38), and dimmer switches are predominantly used indoors, while outdoor motion sensors and solar fixtures are not.
Combining the values presented in Table 3 and Table 4, Table 5 summarizes the interactive effects factor established for each lighting measure. & lt;sup>6 Including 9 W, 9.5 W, 10 W, 18 W, and 7 W black-out bulb LED lamps installed through...
AI summary The text discusses the calculation of interactive effects factors for various lighting measures, combining data from Table 3 and Table 4 into Table 5. It includes details on specific LED lamp installations and references a 2016 study on socket compatibility.
Table 5: Overall Interactive Effects Factors for Residential Lighting Measures Interactive Effects Factors Measure Type of Home Energy Savings Peak Demand Savings EPI LED A-type Lamps10 Heat Pump Heating and Air Conditioning -25.8% x 97% =...
AI summary Table 5 presents the overall interactive effects factors for residential lighting measures, including energy and peak demand savings for various lighting technologies and installation methods. The data shows significant energy savings from LED lamps and other efficiency measures across different home heating and cooling configurations.
Table 6: Peak Demand-to-energy Ratios for Residential Lighting Measures Measure Peak Demand-to energy Ratio (W/kWh) Source LED Lamps 0.162 Northeast Residential Lighting Hours-of-Use Study LED Fixtures LED Nightlights Dimmer Switches Solar...
AI summary Table 6 presents peak demand-to-energy ratios for various residential lighting measures, including LED lamps and motion sensors, with sources cited. The table highlights efficiency metrics for different lighting technologies and control systems.
Table 7: LED Lamp Measure Summary Parameter EPI Instant Savings Reference Measure Description and Identification Measure LED lamps (A-type, Reflector, and Decorative) with direct installation ENERGY STAR Certified LED non-A-type Lamps (R,...
AI summary Table 7 summarizes the LED lamp measure, including parameters such as installation rates, energy savings, and interactive effects. It compares different programs like EPI and Instant Savings, providing details on baseline lamps, energy savings in kWh/year, and peak demand-to-energy ratios.
The equation below determines the unitary savings values of LED lamps for each pairing of old and new wattages. Table 8 lists the parameters and corresponding values used in the equation and the resulting unitary savings values. $$Energy \...
AI summary The text provides an equation to calculate the annual energy savings of LED lamps based on the difference in wattage between old and new lamps, the number of hours a Homeowner Unit (HOU) is used per day, and a conversion factor to convert watts to kilowatts.
Table 8: Electrical Unitary Energy Savings Values for LED Lamps Old New Displaced Operating Unitary Type of LED Wattage Wattage Wattage Hours Savings Value (W) (W) (W) (hrs/day) (kWh/year) EPI 9 W Replacing 25 W 25 9 16 2.6 15.2 9 W Replac...
AI summary Table 8 presents electrical unitary energy savings values for LED lamps, comparing old and new wattages, displaced wattage, operating hours, and annual energy savings in kWh. The table includes various LED replacements, such as 9 W and 9.5 W lamps replacing higher wattage bulbs, as well as specific programs like EPI and Instant Savings. It also notes corrections from the 2024 DSM evaluation.
ation requirements as the baseline. This methodology is recommended in the principles of the Uniform Methods Project (UMP)[16](#page-95-0) to better represent the real baseline wattages for LED lamps. Since R, BR, and decorative lamps are...
AI summary The text discusses methodology for calculating baseline wattages for LED lamps, referencing the Uniform Methods Project (UMP). It notes assumptions about incandescent-to-LED replacements, regulatory wattage limits for ST19 and PAR lamps, and the continuation of E1 in Instant Savings despite incandescent lamp unavailability.
Hours of Operation The daily hours of operation value is based on the 2020 Residential Lighting Hours-of-Use Quick Hit Study (RLHOU)[19](#page-96-0) in which the data collected through the 2014 Northeast Residential Lighting Hours-of-Use (...
AI summary The document analyzes residential lighting hours-of-use (HOU) data from the 2020 RLHOU study and 2014 NERHOU study, noting differences in efficient bulb usage. Three theories (differential socket selection, shifting usage, snapback effect) explain higher HOU for efficient bulbs. Adjustments of 0.2 hours/day were added to avoid overestimating savings, with distinct HOU values applied to E1 and EPI programs.
Unitary Peak Demand Savings Unitary peak demand savings are calculated by multiplying the unitary savings value by the peak demandto-energy ratio. 21 The snapback effect is an increase in usage following the installation of an efficient pr...
AI summary Unitary peak demand savings are calculated by multiplying the unitary savings value by the peak demand-to-energy ratio. The text also mentions the snapback effect, which refers to increased usage after installing efficient products due to lower operating costs. Two studies on residential lighting hours-of-use are cited.
Table 9: Electrical Unitary Peak Demand Savings Values for LED Lamps Type of LED Unitary Energy Savings Value (kWh/year) Peak Demand-to energy Ratio (W/kWh) Unitary Peak Demand Savings Value (W/year) EPI 9 W Replacing 25 W 15.2 0.162 2.46...
AI summary Table 9 presents electrical unitary peak demand savings values for various LED lamps, including different wattage replacements and types. The table includes energy savings, peak demand-to-energy ratios, and unitary peak demand savings values for a range of LED lamps, such as EPI, PAR20, PAR30, PAR38, and GU10. These values are used to assess the impact of LED lamp installations on energy efficiency and demand reduction.
Table 10: EPI LED Lamp Installation Rate Installation Rate Margin of Error Reference 94% 3.0% 2024 EPI evaluation (on-site visits) For upstream programs like Instant Savings, the UMP makes the following recommendation:
AI summary Table 10 presents the EPI LED lamp installation rate at 94% with a 3.0% margin of error, based on the 2024 EPI evaluation. The UMP recommends considerations for upstream programs like Instant Savings.
Summary Table 11 presents a summary of the values used to calculate the savings for motion sensors. The detailed methodology follows.
AI summary Table 11 summarizes the values used to calculate the savings for motion sensors, with a detailed methodology provided in the following sections.
Table 11: LED Fixture Measure Summary Parameter Instant Savings Reference ENERGY STAR Certified LED Recessed Downlight Fixtures ENERGY STAR Certified LED Fixtures ENERGY STAR Certified LED Fixtures with Motion Sensors Measure Description a...
AI summary Table 11 summarizes the energy savings and performance metrics for different LED fixture measures, including energy star certified recessed downlight fixtures, standard-compliant new fixtures, and fixtures with motion sensors. Key parameters include installation rates, useful life, energy savings, and interactive effects factors.
The equation below determines the unitary savings values of LED fixtures. Table 12 lists the parameters and corresponding values used in the equation and the resulting unitary savings values. $$Energy Savings \left[\frac{kWh}{yr}\right] \\...
AI summary The text provides a formula for calculating annual energy savings from LED fixtures, using parameters such as average wattage and hours of use. Table 12 lists the parameters and resulting unitary savings values.
Table 12: Electrical Unitary Savings Values for LED Fixtures Type of LED Fixture Average Wattage (W) Average Equivalent Wattage (W) Displaced Wattage (W) Old Operating Hours (hrs/day) New Operating Hours (hrs/day) Unitary Savings Value (kW...
AI summary Table 12 presents electrical unitary savings values for different types of LED fixtures, including their average wattage, displaced wattage, and unitary savings in kWh/year. The data highlights the energy efficiency improvements from using LED fixtures compared to traditional lighting solutions.
Table 13: 2022 ENERGY STAR Certified Lamp Light Output Equivalency to Incandescent Lamp Wattage[22](#page-100-4) Old Incandescent Lamps (W) ENERGY STAR Certified Lamp Light Output (Lumens) 40 450 60 800 75 1,100 100 1,600 150 2,600 The Eva...
AI summary Table 13 provides equivalency between incandescent lamp wattage and ENERGY STAR certified lamp lumens. The Evaluator analyzed LED fixtures with motion sensors, finding that most replaced halogen lamps, with a small percentage replacing incandescent lamps. A citation to Natural Resources Canada's regulations on incandescent reflector lamps is also included.
Installation Rates The installation rate is assumed to be 100%. 2024-2025 DSM Measure Assessment 24 NMR Group Inc. and DNV GL, Residential Lighting Hours-of-Use Quick Hit Study , March 31, 2020, p. 22. 25 NMR Group Inc. and DNV GL, Northea...
AI summary The installation rate is assumed to be 100% for the 2024-2025 DSM Measure Assessment. Footnotes reference studies on residential lighting usage and an OPA document regarding prescriptive measures.
Table 14: Dimmer Switch Measure Summary Parameter Instant Savings EPI Reference Measure Description and lo dentification Measure Indoor dimmer switches r Savings) or with direct ins • - Baseline Existing indoor fixture without dimmer contr...
AI summary Table 14 summarizes the energy and demand savings associated with the installation of indoor dimmer switches. It includes parameters such as unitary energy savings, peak demand savings, and interactive effects factors, providing a detailed breakdown of the efficiency improvements and potential impacts on heating and cooling systems.
The unitary savings value for dimmer switches is based on the general lighting equation adapted as follows to consider the effect of dimming on energy consumption. $$Energy \, Savings \, \left[\frac{kWh}{yr}\right] = \frac{(Average \, Watt...
AI summary The unitary savings value for dimmer switches is calculated using a modified general lighting equation that incorporates the percentage of dimming, average wattage, and hours-of-use per day. This equation helps estimate annual energy savings in kilowatt-hours.
Table 15: Electrical Unitary Savings Values for Dimmer Switches Parameter Instant Savings EPI Reference Average Wattage [W] 2 x 21.6 W = 43.2 W 2 x 9 W = 18.0 W Assumed two controlled lamps per motion sensor Instant Savings: Weighted avera...
AI summary Table 15 presents electrical unitary savings values for dimmer switches, including average wattage, dimmed wattage, daily hours of operation, and unitary energy savings. The data is based on assumptions from various studies and references, including the United States Department of Energy and the Ontario Power Authority.
Table 16: Motion Sensor Measure Summary Parameter Instant Savings EPI Reference Indoor Motion Sensor Indoor Motion Sensor with Dimmer Switch Outdoor Motion Sensor Indoor Motion Sensor Outdoor Motion Sensor Measure Descrip tion and I dentif...
AI summary Table 16 presents a summary of motion sensor measures, including parameters such as installation rates, energy savings, and interactive effects factors for both indoor and outdoor sensors. The table compares different types of motion sensors and their associated energy and demand savings, providing details on their effective useful life and baseline conditions.
Indoor Motion Sensors The unitary savings value for indoor motion sensors is based on the general lighting equation adapted as follows to consider the effect of motion sensing on energy consumption. $$Energy\ Savings\ \left[\frac{kWh}{yr}\...
AI summary The document discusses the calculation of energy savings from indoor motion sensors using a modified general lighting equation, incorporating factors such as average wattage, hours of use, and percentage reduction in usage. The formula is used to determine unitary savings values, which are summarized in Table 17.
Table 17: Electrical Unitary Savings Values for Indoor Motion Sensors Parameter Instant Savings EPI Reference Average Wattage [W] 2 x 21.6 W = 43.2 W 2 x 9 W = 18.0 W Assumed two controlled lamps per motion sensor Instant Savings: Weighted...
AI summary Table 17 presents electrical unitary savings values for indoor motion sensors, including average wattage, daily hours of operation, and energy savings calculations. It references data from the United States Department of Energy, RLHOU, and the 2011 OPA Prescriptive Measures and Assumptions List.
The unitary savings value for indoor motion sensors is based on the general lighting equation adapted as follows to consider the effects of motion sensing and dimming on energy consumption. The annual energy savings corresponds to the diff...
AI summary The document outlines a method for calculating energy savings from indoor motion sensors and dimmer switches, using a modified lighting equation that accounts for motion sensing and dimming effects. It also references studies and reports related to residential lighting hours-of-use and energy efficiency measures.
Table 18: Unitary Savings Values for Indoor Motion Sensors with Dimmer Switch Parameter Value Reference Average Wattage [W] 2 x 21.6 W = 43.2 W Weighted average wattage per installed lamp of different lighting technologies observed in resi...
AI summary Table 18 presents unitary savings values for indoor motion sensors with dimmer switches, including parameters such as average wattage, dimmed wattage, daily hours of operation, and energy savings calculations. These values are based on references from the United States Department of Energy and the Ontario Power Authority.
The unitary savings value for outdoor motion sensors is based on the general lighting equation adapted as follows to consider the effect of motion sensing on energy consumption. $$Energy \, Savings \, \left[\frac{kWh}{yr}\right] = \frac{(A...
AI summary The unitary savings value for outdoor motion sensors is calculated using a modified general lighting equation that accounts for the impact of motion sensing on energy consumption. The formula incorporates average wattage, old and new hours-of-use (HOU), and results are summarized in Table 19.
Table 19: Unitary Savings Values for Outdoor Motion Sensors Parameter Instant Savings EPI Reference Average Wattage [W] (85% x 2 x 44.6 W) + (15% x 2 x 21.6) = 82.3 W 2 x 15 W = 30.0 W Assumed two controlled lamps per motion sensor Instant...
AI summary Table 19 provides unitary savings values for outdoor motion sensors, including average wattage, operating times, and energy savings calculations. It references the 2011 OPA Prescriptive Measures and Assumptions List and the United States Department of Energy for data on lamp wattages and operating times. The table also mentions the 2024-2025 DSM Measure Assessment.
Final Report 25 & lt;sup>36 Ontario Power Authority (OPA), 2011 Prescriptive Measures and Assumptions Version 1, March 2011. 37 NMR Group Inc. and DNV GL, Residential Lighting Hours-of-Use Quick Hit Study, March 31, 2020, p. 22. & lt;sup>3...
AI summary The document references studies and reports on lighting market characterization and prescriptive measures, including a 2020 U.S. Lighting Market Characterization and a 2011 Prescriptive Measures and Assumptions Version 1 from the Ontario Power Authority. It also discusses the use of specific LED lamps in residential lighting programs.
Table 20: Representative Lamp Mix Calculation for Outdoor Motion Sensor Security Lighting Lamp Wattage Parameter Value Reference Representative 150 W x 16% [incandescent] + 90 W Assumed a representative lamp mix using the United States lam...
AI summary Table 20 presents a representative lamp mix calculation for outdoor motion sensor security lighting, assuming a mix of incandescent, halogen, CFL, and LED lamps based on U.S. Department of Energy data. The calculation results in an average lamp wattage of 44.6 W.
Table 21: LED Nightlight Measure Summary Parameter EPI Reference Measure Description and Identification Measure LED nightlights with direct installation - Baseline Existing nightlight being replaced, which must be incandescent General Para...
AI summary Table 21 presents a summary of the LED nightlight measure, including parameters such as installation rate, energy savings, and peak demand savings. The table outlines the baseline, measure description, and various energy efficiency metrics associated with the replacement of incandescent nightlights with LED alternatives.
Table 22 lists the parameters and corresponding values used in the equation below for LED nightlights and the resulting unitary values. The values for displaced wattages and hours of operation are consistent with the values used by other j...
AI summary The text discusses the calculation of energy savings for LED nightlights using a formula involving old and new wattages, hours of operation (HOU), and references a technical manual from Pennsylvania. It also mentions a 2024-2025 DSM Measure Assessment Final Report.
Table 22: Electrical Unitary Savings Values for LED Nightlights Parameter Value Reference Old Wattage [W] 7.0 Assumption based on the typical wattage value of an incandescent nightlight New Wattage [W] 0.3 Wattage value of the LED nightlig...
AI summary Table 22 presents the electrical unitary savings values for LED nightlights, including old and new wattage, average displaced wattage, hours of operation, and annual energy savings. The table is based on assumptions and calculations related to the installation of LED nightlights through the Efficient Product Installation (EPI) program.
Table 23: EPI LED Nightlight Installation Rate Installation Rate Margin of Error Reference 94% 3.0% 2024 EPI evaluation (on-site visits) (6) Solar Fixtures
AI summary Table 23 presents the EPI LED Nightlight Installation Rate at 94% with a margin of error of 3.0%, referencing the 2024 EPI evaluation. The section also mentions 'Solar Fixtures' as a subsequent topic.
Table 24: Solar Fixture Measure Summary Parameter Instant Savings EPI Reference Measure Description and Identification Measure LED solar fixtures rebate with direct installation (Ef d in store (Instant Savings) or PI) - Baseline Standard-c...
AI summary Table 24 presents a summary of the Solar Fixture Measure, including parameters such as installation rates, energy savings, and peak demand savings. The table compares baseline and measure descriptions, and provides details on energy efficiency metrics like unitary energy savings and peak demand-to-energy ratios.
Since solar fixtures consume no electricity from the grid, all the electrical energy consumed by the baseline fixture is saved. The only solar fixtures currently offered are outdoor security fixtures with motion sensors. The unitary saving...
AI summary The text discusses the energy savings calculation for solar fixtures with motion sensors, highlighting that these fixtures consume no electricity from the grid. The unitary savings value is calculated using a specific equation involving baseline wattage, old hours-of-use, and a conversion factor. E1 mandates that electricians replace non-LED outdoor fixtures with solar fixtures.
Table 25: Unitary Savings Values for Solar Fixtures Parameter Instant Savings EPI Reference Baseline Wattage [W] 46.7 53.4 Instant Savings: Standard compliant lamps providing the same lighting output as the rebated solar fixtures EPI: See...
AI summary Table 25 provides unitary savings values for solar fixtures, comparing instant savings and EPI values. It references baseline wattage, old operating time, and energy savings calculations. Table 26 outlines a representative lamp mix calculation, using wattage values from the United States Department of Energy for outdoor lighting.
2.2 Water Heating
AI summary Section 2.2 outlines water heating programs and initiatives, referencing acronyms like DSM, ARet, and CGH Grant. It highlights regulatory frameworks and efficiency measures, though no explicit arguments or stakeholder positions are presented in the provided text.
Hot Water Insulation Measures For hot water insulation measures, namely pipe insulation and hot water tank wraps, the interactive effects factors are based on engineering calculations to account for the duration of the heating and cooling...
AI summary The text details methodology for calculating interactive effects of hot water insulation measures (pipe insulation and tank wraps), considering heating/cooling seasons, system efficiency, and heat distribution in conditioned spaces. It highlights differences between single-family homes and apartments due to installation likelihood in conditioned areas.
Single-family Homes Based on site visit results from the 2015 evaluation[48](#page-112-2) and accounting for the proportion of DHW insulation measures installed in conditioned spaces, the average number of months during which heating inter...
AI summary The analysis estimates that heating interactive effects in single-family homes occur for 3.8 months annually, with DHW insulation measures having minimal cooling impact. Heat loss assumptions and COP adjustments for heat pumps (dividing by 1.8) are applied to refine efficiency calculations based on Federal Energy Efficiency Regulations.
Apartments Based on the assumption that DHW insulation measures are installed in conditioned spaces, a heating period of eight months was used as the average number of months during which heating interactive effects occur in an apartment....
AI summary The analysis assumes DHW insulation measures in apartments are installed in conditioned spaces, using an 8-month heating period and 2-month cooling period. COP values of 3.5 (heat pumps) and 2.9 (air conditioning) were applied to adjust for interactive effects, aligning with Subsection 2.1.1 assumptions.
Peak Demand As for the impact on peak demand savings, it is assumed that all the DHW tanks in a conditioned or semiconditioned space create interactive effects. Therefore, similar to lighting products, the interactive effects factor for pe...
AI summary The document discusses the impact of domestic hot water (DHW) tanks on peak demand savings, assuming interactive effects in electrically heated homes. It cites regulatory documents and an evaluation report, and references a table summarizing interactive effects factors for DHW insulation measures.
Table 27: Interactive Effects Factors for Pipe Insulation and Hot Water Tank Wraps Parameter Energy Interactive Effects During Heating Period Energy Interactive Effects During Cooling Period Total Energy Interactive Effects Peak Demand Int...
AI summary Table 27 presents interactive effects factors for pipe insulation and hot water tank wraps in different housing types and heating/cooling scenarios. The table calculates energy and peak demand impacts, showing varying percentages depending on the heating and cooling methods used.
Table 28: Interactive Effects Factors for Water Heating Measures Measure Type of Home Interactive Effects Factors for Energy Savings Interactive Effects Factors for Peak Demand Savings Source Drain Water Heat Recovery N/A 0% 0% Assumption...
AI summary Table 28 presents interactive effects factors for various water heating measures on energy savings and peak demand savings, varying by home type and heating system. Factors range from -60% to +5.2% for peak demand savings, with calculations and assumptions provided for each measure.
Table 29: Peak Demand-to-energy Ratios for Water Heating Measures Measure Peak Demand-to energy Ratio (W/kWh) Source Drain Water Heat Recovery 0.162 RES-Water Heat, Navigant 2016-2018 DSM Plan Heat Pump Water Heater Low-flow Showerhead Fau...
AI summary Table 29 presents peak demand-to-energy ratios for various water heating measures, including Drain Water Heat Recovery and Solar Domestic Hot Water. The table highlights that solar DHW systems provide no peak demand savings during peak periods as the sun sets. The section '2.2.3 Water Heating Measures' discusses these measures in detail.
Table 30: Drain Water Heat Recovery Measure Summary Parameter MHEEP Reference Measure Description and Identification Measure Drain water heat recovery for electric DHW heating with direct installation - Baseline Shower drains without drain...
AI summary Table 30 summarizes the Drain Water Heat Recovery Measure for electric domestic hot water heating. It outlines parameters like installation rate, effective useful life, energy savings, and peak demand savings, along with references to specific subsections in the document.
The DWHR unitary savings values were determined using the HOT2000 simulation tool since it includes DWHR as an option. Although a typical single-family home and multifamily building were modelled, the savings for DWHR were the same regardl...
AI summary The document discusses the determination of unitary savings values for DWHR using the HOT2000 simulation tool. The savings values were calculated using an equation and data from a table, and the savings were consistent across different building types when measured per occupant.
(2) Solar Domestic Hot Water
AI summary The section focuses on solar domestic hot water (DHW) systems, likely discussing their role in energy efficiency programs, regulatory considerations, or technical specifications within Nova Scotia's energy framework.
Summary [Table](#page-117-2) 32 presents a summary of the values used to calculate solar domestic hot water (DHW) savings. The detailed methodology follows.
AI summary Table 32 summarizes the values used to calculate solar domestic hot water (DHW) savings. The detailed methodology for these calculations is provided in the document.
Table 32: Solar Domestic Hot Water Measure Summary Parameter Green Heat Reference Measure Description and Identification Measure Solar domestic hot water heating rebated after purchase - Baseline Existing conventional electric water heater...
AI summary Table 32 summarizes the Solar Domestic Hot Water Measure, detailing parameters such as installation rate, effective useful life, and energy savings. The measure involves rebating solar domestic hot water heating systems after purchase, with a baseline of conventional electric water heaters.
Table 33: Heat Pump Water Heater Measure Summary Parameter HEA, MHEEP Instant Savings, HPWH Reference Measure Description and Identification Measure transformation initiative (HPWH) Heat pump water heaters for electric DHW heating with dir...
AI summary Table 33 summarizes the energy savings parameters for heat pump water heaters (HPWH) under different programs, including Instant Savings, HEA, and MHEEP. It outlines metrics such as unitary energy savings, peak demand savings, and installation rates, with references to subsections for detailed calculations.
The unitary savings for HPWHs are taken from a metering study conducted for NEEA. [54](#page-119-0) They include interactive effects. Instant Savings Average Unitary Energy Savings is a weighted average based on the share of space heating...
AI summary The document discusses unitary savings for heat pump water heaters (HPWHs) derived from a metering study by NEEA. It highlights the calculation of average unitary energy savings, considering the share of space heating systems in Nova Scotia and the type of water heaters replaced. A table provides equation parameters and resulting savings values.
Table 34: Electrical Unitary Savings Values for Heat Pump Water Heaters HEA, MHEEP Instant Savings, HPWH Parameter Symbol Non- electric Space Heating Electric Resistance Space Heating Heat Pump Space Heating Non- electric Space Heating Ele...
AI summary Table 34 presents electrical unitary savings values for heat pump water heaters in Nova Scotia, comparing different space heating systems and providing data on the share of electric water heaters and space heating systems. The data is sourced from Ecotope inc., EPI tracking sheets, and Statistics Canada.
(4) Low-flow Showerheads
AI summary The section titled '(4) Low-flow Showerheads' likely addresses regulatory considerations or program initiatives related to low-flow showerhead efficiency standards, energy savings, or appliance retirement programs in Nova Scotia.
Table 35: Low-flow Showerhead Measure Summary Parameter EPI Reference Measure Description and Identification Measure Low-flow showerheads for electric DHW heating with direct installation - Baseline Standard showerhead with a flow rate of...
AI summary Table 35 summarizes the low-flow showerhead measure, including parameters such as flow rate reductions, installation rates, effective useful life, and energy savings. The table details different subcategories and provides references for further information.
The equations below are used to determine the annual unitary savings values for low-flow showerheads. The reduction in domestic hot water consumption is established by the difference between the base and efficient domestic hot water consum...
AI summary The text provides equations to calculate annual energy savings from low-flow showerheads by reducing domestic hot water consumption. It outlines parameters and their values used in these calculations, focusing on energy savings and domestic hot water reduction.
Table 36: Electrical Unitary Energy Savings Values for Low-flow Showerheads Parameter Symbol EPI Reference Single-family Homes Apartments Baseline Flow Rate [gpm] qbase Variable (2.0 gpm, 2.25 gpm, or 2.5 gpm) Variable (2.0 gpm, 2.25 gpm,...
AI summary Table 36 presents electrical unitary energy savings values for low-flow showerheads, including parameters such as baseline flow rate, low-flow rate, number of people per household, average shower time, and efficiency of water heaters. The data is sourced from various studies and references, including the EPI Program Manual and technical reports.
Table 39: Faucet Aerator Measure Summary Parameter EPI Reference Measure Description and Identification Measure Faucet aerators for heating with direct i 0.000 - Baseline Standard faucet wit h no aerator Application Single-family homes Apa...
AI summary Table 39 provides a summary of the Faucet Aerator Measure, including parameters such as installation rates, energy savings, and peak demand savings. The table outlines the measure description, baseline, application, and various energy efficiency metrics related to faucet aerators in single-family homes and apartments.
The equation below is used to calculate the annual unitary savings value for faucet aerators. $$\begin{split} &Energy \, Savings \left[\frac{kWh}{yr}\right] \\ &= \frac{\left(DHW_{base} - DHW_{efficient}\right) \left[\frac{gal}{day}\right]...
AI summary The text provides equations for calculating annual energy savings from faucet aerators by comparing base and efficient domestic hot water consumption values. These calculations involve parameters like flow rates, water properties, and conversion factors.
Table 40: Electrical Unitary Savings Values for Faucet Aerators Parameter Symbol Value for Single-family Homes Value for Apartments Source Baseline Flow Rate [gpm] Q base 1.39 1.39 DeOreo et al. in Residential End Uses of Water Study Updat...
AI summary Table 40 presents electrical unitary savings values for faucet aerators in single-family homes and apartments, including baseline and low-flow rates, water usage parameters, and energy savings calculations based on various sources and conventions.
Table 42: Thermostatic Shower Valve Measure Summary Parameter EPI Reference Measure Description and Identification Measure Thermostatic shower valves for electric DHW heating with direct installation - Baseline Showerheads with a flow rate...
AI summary Table 42 summarizes the energy savings parameters for thermostatic shower valves installed in single-family homes and apartments. It includes details such as installation rates, useful life, unitary energy savings, and peak demand-to-energy ratios, referencing various subsections for further information.
The equation below is used to determine the annual unitary savings values for thermostatic shower valves. Energy savings are established by calculating the reduction in domestic hot water usage, as presented in the second equation below.
AI summary The text provides equations to calculate annual unitary savings for thermostatic shower valves based on reduced domestic hot water usage.
ne the annual unitary savings values for thermostatic shower valves. Energy savings are established by calculating the reduction in domestic hot water usage, as presented in the second equation below.
AI summary The text discusses calculating annual unitary savings for thermostatic shower valves by quantifying reductions in domestic hot water usage through a specific equation. This method establishes energy savings based on decreased water consumption from improved valve efficiency.
$$DHW \ Reduction \ \left[\frac{gal}{year}\right] = q \ \left[\frac{gal}{min}\right] \times n_{people}[person] \times \%_{DHW} \times \ t_w \left[\frac{min}{shower}\right] \times n_{shower} \left[\frac{shower}{day \cdot person}\right] \tim...
AI summary The formula calculates annual domestic hot water (DHW) reduction based on flow rate, number of people, DHW percentage, shower duration, frequency, and showerhead count. It emphasizes variables influencing water usage and efficiency in residential settings.
Table 43: Electrical Unitary Energy Savings Values for Thermostatic Shower Valves Parameter Symbol Value for Single- family Homes Value for Apartments Reference Flow Rate [gpm] q 2.5 gp m EPI 2024 Program Manual Number of People per Househ...
AI summary Table 43 presents electrical unitary energy savings values for thermostatic shower valves in single-family homes and apartments. It includes parameters such as flow rate, number of people per household, average number of showers, and energy efficiency metrics. The values are calculated based on conventions, references, and program manuals.
Table 44 lists the installation rate for thermostatic shower valves. & lt;sup>74 Pennsylvania Public Utility Commission, Technical Reference Manual Volume 2: Residential Measures , September 2024, p. 82. Final Report 48 2024-2025 DSM Measu...
AI summary The text references a table listing the installation rate for thermostatic shower valves and includes citations from technical manuals and studies related to residential water use and efficiency measures.
Table 45: Pipe Insulation Measure Summary Parameter EPI Reference Measure Description and Identification Measure Pipe insulation of 0.75 in. in thickness for electric DHW heating with direct installation - Baseline Pipes with no insulation...
AI summary Table 45 summarizes the pipe insulation measure, including details such as the measure description, baseline, installation rate, effective useful life, and energy savings parameters. The table provides specific values for unitary energy savings, peak demand-to-energy ratio, and other related metrics.
As presented in [Table](#page-130-6) 46, the annual unitary savings value for pipe insulation was identified through Ontario Power Authority (OPA) 2011[75](#page-130-7) values and amounts, established at 12.7 kWh per linear foot.
AI summary The annual unitary savings value for pipe insulation was determined using data from the Ontario Power Authority (OPA) in 2011, with a value of 12.7 kWh per linear foot.
Table 46: Unitary Savings Value for Pipe Insulation Parameter EPI Unitary Energy Savings (per ft) [kWh/year] 12.7
AI summary Table 46 presents the unitary energy savings value for pipe insulation, showing a value of 12.7 kWh/year per foot. This data is part of an analysis related to energy efficiency measures, specifically under the Efficient Product Installation (EPI) program.
Table 48: Hot Water Tank Wrap Measure Summary Parameter EPI Reference Measure Description and Identification Measure Existing electric DHW heater with added tank wrap with direct installation - Baseline Existing hot water tanks without wra...
AI summary Table 48 provides a summary of the Hot Water Tank Wrap Measure, focusing on energy savings and installation parameters. It outlines the measure description, baseline conditions, application scope, and various energy-saving metrics such as unitary energy savings, peak demand-to-energy ratio, and interactive effects factors.
The following equations are used to determine the annual unitary savings associated with hot water tank wraps. The energy savings are equal to the difference in heat losses associated with tank circumference $(Q_{tank})$ before and after a...
AI summary The text outlines equations used to calculate annual unitary savings from hot water tank wraps by comparing heat losses before and after insulation. It includes formulas for heat transfer in an insulated cylinder and calculates energy savings based on thermal resistance and tank specifications.
Table 49: Electrical Unitary Savings Values for Hot Water Tank Wraps Parameter Symbol Value for Single-family Homes Value for Apartments Reference Layer 1: Interior Insulation of Tank External Radius of the Layer [m] re 0.300 0.280 Giant76...
AI summary Table 49 provides electrical unitary savings values for hot water tank wraps, including parameters such as thermal resistance, heat transfer, and energy savings. The table differentiates between single-family homes and apartments and includes references to various sources and calculations.
2.3.1 Interactive Effects Since space heating measures target heating and cooling loads directly, the impact of these measures on heating and cooling is considered in the unitary savings. Therefore, as presented in [Table](#page-134-9) 51,...
AI summary The document discusses the interactive effects of space heating measures, noting that their impact on heating and cooling is already considered in unitary savings. As a result, interactive effects factors for these measures are assumed to be zero.
Table 51: Interactive Effects Factors for Space Heating Measures Measure Interactive Effects Factor for Energy Savings Interactive Effects Factor for Peak Demand Savings Source Mini-split Heat Pump 0% 0% No interactive effects for space he...
AI summary Table 51 outlines interactive effects factors for various space heating measures, indicating no interactive effects for mini-split heat pumps and noting that some measures impact heating and cooling. The table includes measures such as air-source and ground-source heat pumps, wood and pellet stoves, and thermostats.
Table 52: Peak Demand-to-energy Ratios for Space Heating Measures Measure Peak Demand-to energy Ratio (W/kWh) Reference Mini-split Heat Pumps (MSHPs) - - Central Air-source Heat Pumps Ground-source Heat Pumps Wood and Pellet Stoves/Firepla...
AI summary Table 52 outlines peak demand-to-energy ratios for various space heating measures, including heat pumps, wood and pellet stoves, and air sealing products. The data includes references to studies and assumptions used in the analysis, such as the Navigant 2016-2018 DSM Plan.
Table 53: Mini-split Heat Pump Measure Summary Parameter Green Heat, ASFH HEA MHEEP Reference Measure Description and Identification Measure Mini-split heat pumps for high-efficiency space heating with direct installation (HEA, MHEEP) or r...
AI summary Table 53 provides a summary of mini-split heat pump measures, including parameters such as installation rate, effective useful life, and energy savings. It compares different programs like Green Heat, ASFH HEA, and MHEEP, and references subsections for detailed calculations.
For Green Heat, the electrical unitary energy savings for MSHPs are based on the billing analysis results of the 2024 Green Heat evaluation, which yielded savings per unit of capacity for both homes that were fully electrically heated and...
AI summary The document outlines how energy savings for Green Heat, HEA, and MHEEP are calculated. For Green Heat, savings are based on billing analysis results from the 2024 evaluation, while for HEA and MHEEP, savings are derived from HOT2000 simulation outputs adjusted by ratios from the same evaluation. Different methods are used depending on whether homes are fully or mainly electrically heated.
Table 54: Adjustment Ratios for HEA and MHEEP Modelled Savings Scenario Adjustment Ratio A participant who registered with a heat pump 1.24 A participant who registered without a heat pump and who did not install one 0.58 A participant who...
AI summary Table 54 outlines adjustment ratios for HEA and MHEEP modelled savings, showing different scenarios based on heat pump registration and installation. The ratios vary significantly depending on whether a participant registered with or without a heat pump and whether installation occurred.
For Green Heat and HEA, the unitary peak demand unitary savings for MSHPs are calculated using the variables defined and listed in the equation and [Table](#page-137-3) 55 below. $$Peak\ Demand\ Savings_W = \frac{1{,}000}{3.412} \times HC_...
AI summary The text discusses the calculation of unitary peak demand savings for MSHPs using a specific formula involving variables such as HC_min, COP_base_min, and COP_ee_min, referencing a table for detailed variables.
Table 55: Unitary Peak Demand Savings Values for Mini-split Heat Pumps Variable Symbol Green Heat Reference Rated heating capacity of the new heat pump at outdoor air temperature of -15°C [kBtu/h] 𝐻𝐶𝑚𝑖𝑛 Specification data for each installe...
AI summary Table 55 provides unitary peak demand savings values for mini-split heat pumps, focusing on the rated heating capacity, coefficient of performance, and conversion factors. Peak demand savings are only claimed for households with fully electrically heated baselines, with no savings for mainly electrically heated baselines due to nil electrical energy savings.
Table 56: Central Air-source Heat Pump Measure Summary Parameter Green Heat HEA Reference Measure Description and Identification Measure rebated after purchase Central air-source (air-to-air and air-to-water) heat pumps - Baseline Electric...
AI summary Table 56 provides a summary of the Central Air-source Heat Pump Measure, including parameters such as installation rate, effective useful life, energy savings, and peak demand savings. The measure involves rebating after purchase for central air-source heat pumps, with energy savings calculated using the HOT2000 simulation model.
Table 57: Unitary Peak Demand Savings Values for Central Air-source Heat Pumps Variable Symbol Green Heat Reference Rated heating capacity of the new heat pump at outdoor air temperature of -15°C [Btu/h] 𝐻𝐶𝑚𝑖𝑛 26,261 Average specification...
AI summary Table 57 presents unitary peak demand savings values for central air-source heat pumps, including rated heating capacity, coefficient of performance for baseline and new heat pumps, and calculated peak demand savings. The data is sourced from the 2022 Green Heat tracking sheet and uses standard conversion factors.
Table 58: Ground-source Heat Pump Measure Summary Parameter Green Heat HEA Reference Measure Description and Identification Measure Ground-source heat pumps for high-efficiency space rebated after installation (HEA) or rebated after purcha...
AI summary Table 58 outlines the parameters for the Ground-source Heat Pump Measure Summary, including installation rates, effective useful life, and energy savings calculations based on HOT2000 simulation data. The table provides details on baseline heating systems, unitary energy savings, and peak demand-to-energy ratios.
Table 59: Electrical Unitary Savings Values for Ground-source Heat Pumps in Green Heat Parameter Symbol Value Reference Rated heating capacity of the new heat pump [Btu/h] 𝐻𝐶 Specification data for each installed system AHRI certified valu...
AI summary Table 59 presents electrical unitary savings values for ground-source heat pumps in the Green Heat program, including parameters such as heating and cooling capacities, performance factors, and load hours, with references to AHRI certified values and technical reference manuals.
Table 60: Wood and Pellet Stove and Fireplace Insert Measure Summary Parameter Green Heat HEA Reference Measure Description and Identification Measure purchase (Green Heat) Wood and pellet stoves and fireplace inserts rebated after install...
AI summary Table 60 provides a summary of energy savings parameters for wood and pellet stove and fireplace insert measures, including installation rates, useful life, and energy savings in kWh/year and peak demand savings in watts.
$Peak \ Demand \ Savings_W = Previous \ Peak \ Demand \ Savings_W \times \frac{Energy \ Savings_{kWh}}{Previous \ Energy \ Savings_{kWh}}$ Table 61: Unitary Peak Demand Savings Values for Wood or Pellet Stoves and Fireplace Inserts Green n...
AI summary The document provides a formula for calculating peak demand savings and includes a table with values for wood or pellet stoves and fireplace inserts. It references past and current demand-side management (DSM) measures and their energy savings.
(5) Wood and Pellet Boilers and Furnaces
AI summary Section 5 of the document addresses the regulatory considerations for wood and pellet boilers and furnaces, including their role in energy efficiency programs, potential incentives, and compliance with regulatory standards. It outlines implications for program design, cost recovery, and environmental impact assessments.
Table 62: Wood and Pellet Boiler and Furnace Measure Summary Parameter Green Heat HEA Reference Measure Description and Identification Measure purchase (Green Heat) Wood and pellet boilers and furnaces rebated after installation (HEA) or r...
AI summary Table 62 provides a summary of energy savings parameters for wood and pellet boilers and furnaces under the Green Heat and HEA programs. It includes details on installation rates, effective useful life, unitary energy savings, peak demand savings, and interactive effects factors.
esources.canada.ca/energy-efficiency/energy-efficiency-regulations/guide-canadas-energy-efficiency-regulations/split-system-central-air-conditioners-and-heat-pumps/6895) 90 The HOT2000 energy models were developed as part of the 2013 evalu...
AI summary The HOT2000 energy models were developed as part of the 2013 evaluation, which is referenced in the context of energy efficiency regulations on the Canadian government website.
Table 63: Electrical Unitary Energy Savings Values for Wood and Pellet Boilers and Furnaces Green Green Heat ĒΑ Parameter Symbol Wood Furnace or Boiler Pellet Furnace or Boiler Wood Furnace or Boiler Pellet Furnace or Boiler Reference Coef...
AI summary Table 63 presents electrical unitary energy savings values for wood and pellet boilers and furnaces, including coefficients of performance for baseline electric resistance and heat pumps, and corresponding energy savings calculations based on these values.
Table 64: Unitary Peak Demand Savings Values for Wood and Pellet Boilers and Furnaces Green Heat Parameter Wood Furnace or Boiler with Electrical Baseline Pellet Furnace or Boiler with Electrical Baseline Wood Furnace or Boiler with ASHP B...
AI summary Table 64 presents unitary peak demand savings values for wood and pellet boilers and furnaces under different baseline scenarios. The table highlights the energy efficiency benefits of these heating systems, with values ranging from 7,660 to 7,750 watts. The section on installation rates likely discusses the rate at which these systems are being installed.
Table 65: Solar Air Heating Measure Summary Parameter Green Heat Reference Measure Description and Identification Measure Solar air heating systems rebated after installation - Baseline Electric space heating (resistance or heat pump) Gene...
AI summary Table 65 outlines the parameters for the Solar Air Heating Measure, including installation rates, useful life, and energy savings calculations using RETScreen. The table highlights energy savings and peak demand savings, with various parameters detailed in subsections of the document.
Table 66: Air Sealing Product Measure Summary Parameter EPI Reference Measure Description and Identification Measure Air sealing products in electrically heated homes with direct installation - Baseline Door and/or windows without added ai...
AI summary Table 66 summarizes air sealing product measures for electrically heated homes, including installation rates, energy savings, and peak demand savings. It provides data on different types of air sealing products and their effectiveness in reducing energy use and demand.
Table 67: Savings Values for Air Sealing Products in Electric Resistance and Heat Pump Heated Homes Measure Electric Resistance Heated Homes Heat Pump Heated Homes Reference Annual Energy Savings from Foam Gaskets [kWh/gasket] 9 5.00 Elect...
AI summary Table 67 provides savings values for air sealing products in homes heated by electric resistance and heat pumps, including foam gaskets, door sweeps, window air sealing, and door weather stripping. References are provided for the data, including Connecticut and TRM95.
Table 69: Window Film Kit Measure Summary Parameter EPI Reference Measure Description and Identification Measure Window film kits installed by the participant (left behind by the delivery agent), in electrically heated homes - Baseline Win...
AI summary Table 69 provides a summary of the Window Film Kit Measure, including parameters such as installation rate, energy savings, and peak demand savings. The measure involves installing window film kits in electrically heated homes and is categorized under Electrical Resistance Heated Homes and Heat Pump Heated Homes.
The electrical unitary energy savings values of the window kit measure are calculated using the equations below. $$Energy \, Savings \, (kWh) = ES_{sealing} + ES_{insulation}$$ $$ES_{sealing} = \frac{n_{window} \times p_{window} \times ESP...
AI summary The document explains how energy savings from window film kits are calculated, combining savings from insulation and sealing. It references technical documents from Illinois, Connecticut, and Iowa, adjusting values to the Nova Scotia context using heating degree days and resistance values.
Table 70: Electrical Unitary Savings Calculations for Window Film Kits Parameter Symbol Value for Electrical Resistance Heated Homes Value for Heat Pump Heated Homes Number of Windows Insulated Nwindow 2 Assumption that one window kit can...
AI summary Table 70 presents electrical unitary savings calculations for window film kits, comparing resistance heated homes and heat pump heated homes. It includes parameters such as number of windows, perimeter, area, heating degree days, coefficient of performance, and energy savings from air sealing and insulation. The data is sourced from Connecticut and Iowa technical reference manuals.
Table 71: Programmable Thermostat Measure Summary Parameter Instant Savings MHEEP Reference Measure Description and Identification Measure Programmable thermostats rebated in store for controlling electric baseboards Programmable thermosta...
AI summary Table 71 provides a summary of two programmable thermostat measures: 'Instant Savings' and 'MHEEP'. It outlines parameters such as measure description, baseline, installation rate, useful life, and energy savings. Both measures involve programmable thermostats for controlling electric baseboards, with differences in rebate methods and energy savings estimates.
Electrical Unitary Energy Savings For programmable thermostats, the electrical unitary energy savings are based on the results from a Hydro-Québec 2009 program evaluation of electronic thermostats in residential new construction.[100](#pag...
AI summary The document discusses the calculation of electrical unitary energy savings for programmable thermostats, referencing a 2009 Hydro-Québec evaluation and a 2021 Statistics Canada census profile. It highlights differences in savings values for single-family homes versus other dwelling types and mentions the Instant Savings program's baseline assumptions.
Table 72: Electrical Unitary Savings Calculations for Programmable Thermostats Instant Savings MHEEP Parameters Symbol Single-family Duplex/Triplex/ Townhouse Apartment Single-family Reference Proportion of Each Dwelling Type 𝐷𝑤𝑒𝑙𝑙𝑖𝑛𝑔 𝑃𝑟𝑜𝑝...
AI summary Table 72 presents electrical unitary savings calculations for programmable thermostats across different dwelling types, including single-family homes, duplexes, and apartments. The table includes parameters such as proportion of each dwelling type, gross energy savings per thermostat, and total savings per dwelling type.
Table 73: Smart Thermostat for Electrical Heating System Measure Summary Parameter Instant Savings, EPI MHEEP, ASFH Reference Measure Description and Identification Measure floor heating Smart thermostats controlling electric baseboards, M...
AI summary Table 73 summarizes the Smart Thermostat for Electrical Heating System Measure, detailing parameters such as installation rates, energy savings, and peak demand savings for different subcategories of electric heating systems.
Some models of smart thermostats sold through Instant Savings or installed through EPI or MHEEP are compatible with electrical heating systems. They operate by connecting to a single baseboard, MSHP, or infloor heating system as opposed to...
AI summary The text discusses the calculation of energy savings for smart thermostats compatible with electrical heating systems, using a formula and referencing studies on Nest thermostats installed on central heating systems. The studies indicate a 12% heating consumption savings, which is applied as a baseline for similar systems.
Table 74: Billing Analysis Savings Results for Smart Thermostats for Electrical Heating Systems Jurisdiction Measure Sample Size Heating Consumption Savings Oregon105 Nest thermostats 185 12% (for ASHPs) Bonneville Power Administration106...
AI summary Table 74 presents billing analysis savings results for smart thermostats used with electrical heating systems in Oregon and the Bonneville Power Administration. The data shows 12% savings for air-source heat pumps (ASHPs). The savings are calculated based on assumptions about the number of heating systems per dwelling.
105 Apex Analytics LLC, Energy Trust of Oregon Nest Thermostat Heat Pump Control Pilot Evaluation , October 10, 2014, p. 123. [Table](#page-160-1) 75 below presents the variables used for the unitary savings calculation and the resulting v...
AI summary The text references a study by Apex Analytics LLC on a heat pump control pilot program and mentions a table presenting variables for unitary savings calculation. No direct arguments or entities are discussed in the provided text.
Table 75: Electrical Unitary Energy Savings Calculation for Smart Thermostats for Electrical Heating Systems Instant Savings, MHEEP, ASFH, EPI Single-family homes EPI Apartments Parameter Symbol Value for Electric Baseboard or Electric In-...
AI summary Table 75 provides an electrical unitary energy savings calculation for smart thermostats in electrical heating systems, including data for single-family homes and apartments, with values for different heating systems and assumptions used in the calculations.
Table 77: Advanced Learning Thermostat for Central Heating System Measure Summary Parameter EPI Reference Measure Description and Identification Measure Wi-Fi enabled advanced thermostats with 7-day or learning-based scheduling and remote...
AI summary Table 77 provides a summary of the Advanced Learning Thermostat for Central Heating System measure, including details on the measure description, baseline, subcategory, installation rate, effective useful life, and energy savings parameters. The table outlines energy savings, peak demand savings, and interactive effects factors.
The equation below is used to calculate the unitary savings value for learning thermostats compatible with central electrical heating systems and installed through EPI. $$Energy Savings_{kWh} = \frac{Heating Energy \times \%Savings}{COP}$$...
AI summary The text provides an equation for calculating energy savings from learning thermostats installed through EPI, using heating energy, savings percentage, and COP. It references tables that detail the billing analyses and variables used in the calculation.
Table 78: Electrical Unitary Energy Savings Calculation for Smart Thermostats for Electrical Heating Systems Parameter Symbol Value for Central Heat Pump Value for Electric Furnace Reference Average Heating Energy Consumption of a Home [kW...
AI summary Table 78 outlines the calculation of electrical unitary energy savings for smart thermostats used in electrical heating systems, including parameters such as average heating energy consumption, percentage of heating load saved, and heating system coefficient of performance. It also provides installation rates for different heating systems.
2.4.1 Interactive Effects Retiring old appliances causes an increase in the heating load in the winter and a decrease in the cooling load in the summer since compressors on old appliances release significantly more waste heat than newer, m...
AI summary Retiring old appliances increases heating loads in winter and decreases cooling loads in summer, but interactive effects are largely offset by factors such as the proportion of households using electric heating, appliance placement, and air conditioning usage. Overall, interactive effects are considered negligible, leading to a 0% factor for energy and peak demand savings.
Table 79: Interactive Effects Factors for Appliances Measure Interactive Effects Factor for Energy Savings Interactive Effects Factor for Peak Demand Savings Source Clotheslines and Outdoor Drying Racks 0% 0% Assumption Refrigerator Retire...
AI summary Table 79 outlines interactive effects factors for various appliance measures related to energy and peak demand savings. The table includes measures such as clotheslines, refrigerator replacements, and ENERGY STAR® certified appliances, though many entries are incomplete or reference text above the table. The section also mentions peak demand savings factors in 2.4.2.
Table 80: Peak Demand-to-energy Ratios for Appliances Measure Peak Demand to-energy Ratio (W/kWh) Source Clothesline and Outdoor Drying Racks 0.000 Calculated by the Evaluator Refrigerator Retirements/Replacements 0.138 RES-Appliance-Fridg...
AI summary Table 80 presents peak demand-to-energy ratios for various appliances, calculated by the Evaluator or based on specific data sources like the NREL ResStock end-use load profiles. The data includes ratios for refrigerators, freezers, dehumidifiers, and other appliances, with sources citing the Navigant 2016-2018 DSM Plan and other studies.
Summary Table 81 presents a summary of the values used to calculate clothesline and outdoor drying rack savings. The detailed methodology follows.
AI summary Table 81 summarizes the values used to calculate savings from clothesline and outdoor drying rack usage. The detailed methodology for these calculations is provided in the following sections.
The savings from this measure are due to avoided clothes dryer loads. The following equation is used to establish the unitary savings associated with clotheslines and outdoor drying racks. $$\begin{split} Energy Savings & \left[\frac{kWh}{...
AI summary The text discusses energy savings from using clotheslines and outdoor drying racks, using a formula that multiplies annual laundry loads, the proportion of loads dried outdoors, and energy consumption per load to calculate annual energy savings in kWh.
Table 82: Electrical Unitary Savings Values for Clotheslines and Outdoor Drying Racks Parameter Value Source Number of Laundry Loads per Year [loads/year] 197 Research to update this value showed that it hardly changed, so the one establis...
AI summary Table 82 provides electrical unitary savings values for clotheslines and outdoor drying racks, including parameters like laundry loads per year, proportion of loads dried on clotheslines, energy consumption per load, and calculated unitary energy savings. The data references sources from 2011 and 2015.
(2) Refrigerator Retirements/Replacements
AI summary The section discusses refrigerator retirements/replacements programs, focusing on Appliance Retirement (ARet) initiatives under Efficiency Nova Scotia (ENS) and Nova Scotia Power (NSP). It highlights energy efficiency gains, GHG emission reductions, and alignment with DSM goals.
Table 83: Refrigerator Retirement/Replacement Measure Summary Parameter ARet HomeWarming / MHEEP Reference Measure Description and Identification Measure Retirement and recycling of old refrigerators New efficient refrigerators - Baseline...
AI summary Table 83 provides a summary of the Refrigerator Retirement/Replacement Measure, detailing parameters such as measure description, baseline, installation rates, energy savings, and peak demand savings for different refrigerator categories.
The following equations are used to determine the electrical unitary energy savings value of retired and replaced refrigerators. ℎ = × × × − = ∑( × %) For regular and small refrigerators retired through ARet, average annual per-cubic-foot...
AI summary The document outlines the methodology for calculating electrical unitary energy savings from retired and replaced refrigerators, using data from 2017 metering activity, NRCan analyses, and EnerGuide directories. It also accounts for aging efficiency loss and occupant adjustment factors.
t factor is based on the metering protocol of the New York Department of Public Service[128](#page-170-7) and the part-use factor is calculated based on 2022 participant survey data.[129](#page-170-8) For refrigerators replaced through Hom...
AI summary The calculation of unitary savings for refrigerators replaced via HomeWarming and MHEEP uses 1994-era energy consumption data, assumes primary refrigerator replacements, and relies on EnerGuide and ENERGY STAR product ratings from tracking sheets (2021–2023). Part-use factors are omitted due to program criteria.
122 Natural Resources Canada, EnerGuide appliance directory , https://publications.gc.ca/site/eng/9.500453/publication.html. (last accessed October 10, 2024). 123 Only two years of data were used since the exercise of matching NRCan data b...
AI summary The text references energy efficiency regulations, appliance standards, and studies on refrigeration efficiency, citing Natural Resources Canada, the U.S. Department of Energy, and New York's energy savings estimation methods. It highlights data collection efforts and regulatory frameworks for appliance efficiency.
nt of Public Service, New York Standard Approach for Estimating Energy Savings from Energy Efficiency Programs - Residential, Multi-Family, and Commercial/Industrial Measures, April 15, 2019, p. 29. 129 Econoler, Residential Efficient Prod...
AI summary The text references a report on estimating energy savings from efficiency programs and a DSM evaluation report, including a table with parameters and unitary savings calculations for refrigerator retirement and replacement measures.
Table 84: Electrical Unitary Savings Values for Refrigerator Retirements/Replacements Parameter Symbol Manufacture year Class ARet (Retirement) HomeWarming / MHEEP (Replacement) Reference ft.3 Full-sized Refrigerators (≥ 10 ) Small Refrige...
AI summary This table presents electrical unitary savings values for refrigerator retirements and replacements, including parameters like annual consumption, refrigerator size, and energy savings. It includes data from various sources such as NRCan and NYPDS, and covers different refrigerator classes and years of manufacture.
Table 85: Freezer Retirement/Replacement Measure Summary Parameter ARet HomeWarming / MHEEP Reference Measure Description and Identification Measure Retirement and recycling of old freezers New efficient freezers - Baseline Continued usage...
AI summary Table 85 presents a summary of the Freezer Retirement/Replacement Measure, detailing parameters such as installation rates, energy savings, and peak demand savings for both old and new freezers. It includes baseline scenarios, measure descriptions, and references to subsections for further details.
To determine the electrical unitary energy savings value of retired (ARet) and replaced (ASFH, MHEEP) freezers, the following equations are used. ℎ = × × × − = ∑( × %) For regular and small freezers retired through ARet, the average annual...
AI summary The text outlines the methodology for calculating the electrical unitary energy savings value of retired and replaced freezers through programs like ARet, ASFH, and MHEEP. It references data from NRCan, EnerGuide, and metering studies to adjust for aging appliances and calculate weighted averages based on 2024 tracking sheet data.
132 Natural Resources Canada, EnerGuide appliance directory , https://publications.gc.ca/site/eng/9.500453/publication.html (last accessed October 10, 2024). 133 Only two years of data were used since the exercise of matching NRCan data be...
AI summary The text cites regulatory and research sources on appliance energy efficiency, including Natural Resources Canada's EnerGuide directory, U.S. Department of Energy standards, and studies on aging refrigerators. It references updates to measure assessments and regulatory amendments related to energy efficiency regulations for household appliances.
nt of Public Service, New York Standard Approach for Estimating Energy Savings from Energy Efficiency Programs - Residential, Multi-Family, and Commercial/Industrial Measures, April 15, 2019, p. 29. 139 Econoler, Residential Efficient Prod...
AI summary The text references a report on estimating energy savings from energy efficiency programs and a final evaluation of the Residential Efficient Product Rebates Program. It also mentions a table that presents parameters and unitary savings calculations for specific measures.
Table 86: Electrical Unitary Savings Values for Freezer Retirements/Replacements Parameter Symbol Manufacture-year Class ARet (Retirement) HomeWarming / MHEEP (Replacement) Reference Regular Freezers (≥ 7 ft.³) Small Freezers (< 7 ft. 3 )...
AI summary Table 86 presents electrical unitary savings values for freezer retirements and replacements, including annual consumption per size, proportion of freezers by manufacturing year, and energy savings calculations. This data is used to evaluate the impact of appliance retirement and replacement programs on energy efficiency.
(4) Room Air Conditioner Retirements
AI summary The section focuses on Room Air Conditioner Retirements, likely addressing policies or programs related to phasing out inefficient units. It may involve energy efficiency initiatives, appliance standards, or demand-side management strategies.
(5) Dehumidifier Replacements or Retirements/ENERGY STAR Certified Dehumidifiers
AI summary The section discusses dehumidifier replacements or retirements and ENERGY STAR certified dehumidifiers, likely within the context of energy efficiency programs. Key themes include appliance standards, demand-side management, and energy efficiency initiatives. No detailed content is provided in the text chunk.
Table 89: Dehumidifier Replacement or Retirement / ENERGY STAR Certified Dehumidifier Measure Summary Parameter ARet, ASFH, MHEEP146 Instant Savings Reference Measure Description and Identification Measure Replacement or retirement of old...
AI summary The table provides a comparison between the replacement or retirement of old dehumidifiers and the rebate for ENERGY STAR certified dehumidifiers. It outlines parameters such as energy savings, peak demand savings, and useful life for both measures.
Parameter Symbol ARet, ASFH, MHEEP Instant Savings Average Water Removal Capacity [L/day] 𝐴𝑊𝑅𝐶 3.87 2011 OPA Average Operating Days [days/year] 𝐴𝑂𝐷 168 2011 OPA Energy Factor of the Baseline Dehumidifier [L/kWh] 𝐸𝐹𝑏𝑎𝑠𝑒 0.66 1.60 ARet: 2011...
AI summary The table presents parameters related to average water removal capacity, average operating days, and energy factors for baseline and new ENERGY STAR certified dehumidifiers, along with energy savings calculations. The data is sourced from various regulatory proceedings and tracking sheets.
(6) ENERGY STAR Certified Clothes Dryers
AI summary This section heading references ENERGY STAR Certified Clothes Dryers, likely part of a regulatory proceeding discussing appliance efficiency standards or energy programs in Nova Scotia. The content is minimal, focusing on categorization rather than detailed analysis.
Table 91: ENERGY STAR Certified Clothes Dryer Measure Summary Parameter Instant Savings Reference Measure Description and Identification Measure ENERGY STAR certified clothes dryers rebated in store - Baseline New non-ENERGY STAR certified...
AI summary Table 91 summarizes the energy savings parameters for ENERGY STAR certified clothes dryers, including unitary energy savings, peak demand-to-energy ratio, and effective useful life. The measure involves rebating these dryers in store, with a 100% installation rate and a 12-year useful life.
The electrical unitary energy savings of the ENERGY STAR certified clothes dryer measure are calculated using the equations below. Energy Savings $$_{kWh} = ADL \times ALW \times \left(\frac{1}{CEF_{base}} - \frac{1}{CEF_{new}}\right)$$ Th...
AI summary This text discusses the calculation of electrical unitary energy savings for ENERGY STAR certified clothes dryers using equations involving average daily loads and combined energy factors. It references data from Natural Resources Canada and outlines the parameters used in the 2024-2025 DSM Measure Assessment.
Table 92: Electrical Unitary Savings Values for ENERGY STAR Certified Clothes Dryer Parameter Symbol Instant Savings Reference Average Dried Loads per Year [load/year] 𝐴𝐷𝐿 197 2015 NRCan150 Average Load Weight [lbs/load] 𝐴𝐿𝑊 8.45 2019 PUC...
AI summary Table 92 provides electrical unitary savings values for ENERGY STAR certified clothes dryers, including parameters such as average dried loads per year, combined energy factor of new and baseline units, and unitary energy savings. The table references various sources including NRCan and PUC TRM.
(7) Efficient Clothes Washers
AI summary The section titled '(7) Efficient Clothes Washers' likely discusses energy efficiency initiatives related to appliance standards and programs promoting efficient washing technologies, though no detailed content is provided in the excerpt.
Table 93: Efficient Clothes Washer Measure Summary Parameter Instant Savings Reference Measure Description and Identification Measure ENERGY STAR clothes washers, rebated in store - Baseline New non-ENERGY STAR clothes washer General Param...
AI summary Table 93 provides a summary of the Efficient Clothes Washer Measure, including details on energy savings, installation rates, and useful life. The measure involves rebating ENERGY STAR clothes washers, with a baseline of non-ENERGY STAR washers. Energy savings parameters and interactive effects factors are also outlined.
Energy Consumption Calculation First, the energy consumption values of both baseline and efficient clothes washers are determined using the following equation. $$Clothes\ Washer\ Energy\ Consumption\ [kWh]\ = \frac{Number\ of\ Loads\ \left...
AI summary The document outlines the method for calculating the energy consumption of baseline and efficient clothes washers using a specific formula. It references a table that provides the parameters and resulting energy consumption values for these washers.
Table 94: Clothes Washer Energy Consumption Parameter Symbol Value for Baseline Clothes Washer Value for Efficient Clothes Washer Reference Number of Loads [Loads/Year] 𝑁𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝐿𝑜𝑎𝑑𝑠 218 2015 NRCan152 Capacity [L] 𝐶𝑎𝑝𝑎𝑐𝑖𝑡𝑦 127 Weighted a...
AI summary Table 94 compares energy consumption between baseline and efficient clothes washers. It includes parameters such as number of loads, capacity, and integrated modified energy factor (IMEF), with data sourced from Natural Resources Canada and ENERGY STAR Certified Clothes Washers database.
Water Heating Adjustment Both energy consumption values do not take into account the proportion of hot water for clothes washers produced with electricity in Nova Scotia, nor the use of cold water for washing. Therefore, the energy consump...
AI summary The text discusses the need to adjust energy consumption values for clothes washers in Nova Scotia, considering the proportion of hot water used and the use of cold water for washing. It highlights the breakdown of energy consumption for both baseline and efficient washers during each stage of the washing process to apply correction factors.
Table 95: Energy Consumption Breakdown for Baseline and Efficient Clothes Washers Energy Consumption Breakdown for Clothes Washers Proportion of Overall Consumption155 Baseline Clothes Washer Electricity Consumption (kWh/year) Efficient Cl...
AI summary Table 95 compares the energy consumption of baseline and efficient clothes washers, breaking down usage by components like water heating and drying. Table 96 provides the proportion of electrical versus non-electrical DHW tanks in Nova Scotia, which is used to calculate energy savings from efficient washers. An adjustment factor of 0.67 is applied for cold water washing, based on Hydro-Québec survey data.
Adjusted Energy Consumption [Table](#page-183-0) 97 and [Table](#page-183-1) 98 present the calculations of total electricity consumption for baseline and efficient clothes washers respectively. 158 Ad Hoc Recherche, Rapport d'évaluation,...
AI summary The document discusses the calculation of electricity consumption for baseline and efficient clothes washers, referencing reports and data from the EPI program. It highlights discrepancies in data from NRCan and the use of updated EPI tracking sheets from 2022 and 2023 due to program changes in 2021.
Table 97: Electricity Consumption for Baseline Clothes Washers Energy Consumption Component Energy Consumption (kWh/year) Adjustment Factor for Electrical Water Heating Adjustment Factor for Cold Water Usage Adjusted Energy Consumption (kW...
AI summary The text presents two tables comparing the electricity consumption of baseline and efficient clothes washers, highlighting energy savings through adjusted energy consumption values. The unitary energy savings value is derived from the difference between the two sets of data.
Table 99: Electrical Unitary Savings Value for Clothes Washer Parameters Value Adjusted Energy Consumption of Baseline Clothes Washer [kWh/year] 432 Adjusted Energy Consumption of Efficient Clothes Washer [kWh/year] 294 Unitary Energy Savi...
AI summary Table 99 presents the electrical unitary savings value for clothes washers, comparing the adjusted energy consumption of baseline and efficient models. The unitary energy savings amount to 138 kWh/year, indicating the energy efficiency benefit of using an efficient clothes washer.
(8) Efficient Washer-Dryer Combination Units
AI summary The section discusses efficient washer-dryer combination units, likely addressing their role in energy efficiency programs, regulatory considerations, or appliance standards in Nova Scotia.
Table 100: Efficient Washer-Dryer Combination Units Parameter Instant Savings Reference Measure Description and Identification Measure ENERGY STAR washer-dryer combination units rebated in store - Baseline New non-ENERGY STAR washer-dryer...
AI summary This table outlines the parameters for efficient washer-dryer combination units, including energy savings, peak demand savings, and useful life. The measure involves rebating ENERGY STAR units, with a baseline of non-ENERGY STAR units. The unitary energy savings are 144 kWh/year, and the peak demand-to-energy ratio is 0.138.
For efficient washer-dryer combination units, the current models available through the program consist of a dryer and a washer with separate drums that operate separately. Therefore, the energy savings are calculated by summing the savings...
AI summary The text outlines the methodology for calculating energy savings from efficient washer-dryer combination units, using data from the NRCan 2015 Survey and weighted average CEF values from 2024 models. It references equations and a table for detailed calculations.
Table 101: Electrical Unitary Savings Values for the Efficient Clothes Dryer Component of Efficient Washer-Dryer Combination Units Parameter Symbol Instant Savings Source Average Dried Loads per Year [load/year] 𝐴𝐷𝐿 197 2015 NRCan159 Avera...
AI summary The table outlines electrical unitary savings values for efficient clothes dryers in washer-dryer combination units, including parameters such as average dried loads, energy factor of new and baseline units, and calculated energy savings. The savings are derived from comparing the energy consumption of efficient and baseline units, adjusted for hot water usage.
First, the energy consumption values of both baseline and efficient clothes washers are determined using the following equation. $$Clothes \ Washer \ Energy \ Consumption \ [kWh] \ = \frac{Number \ of \ Loads \ \left[\frac{Loads}{Year}\rig...
AI summary The document provides an equation for calculating clothes washer energy consumption based on number of loads, capacity, and IMEF. It references data from Natural Resources Canada and the Pennsylvania Public Utility Commission's Technical Reference Manual.
Table 102: Clothes Washer Energy Consumption Parameter Value for Baseline Clothes Washer Value for Efficient Clothes Washer Source Number of Loads [Loads/Year] 218 2015 NRCan162 Capacity [L] 127 Weighted average capacity based on rebated m...
AI summary The table compares energy consumption of baseline and efficient clothes washers, highlighting differences in parameters such as number of loads, capacity, and energy factor. It notes that energy consumption values do not account for hot water usage or cold water washing, prompting a breakdown in Table 103 to apply correction factors at each stage of the washing process.
Table 103: Energy Consumption Breakdown for Baseline and Efficient Clothes Washers Energy Consumption Breakdown for Clothes Washers Proportion of Overall Consumption165 Baseline Clothes Washer Electricity Consumption (kWh/year) Efficient C...
AI summary Table 103 provides an energy consumption breakdown for baseline and efficient clothes washers, highlighting significant reductions in electricity use, particularly in water heating systems and clothes dryers. The data is based on participant information from the 2022 and 2023 EPI tracking sheets, which were used due to changes in the EPI program in 2021.
Table 104: Water Heating Sources for Clothes Washers DHW Tank Type Proportion Electrical 76% Non-electrical 24% For water heating consumption, an adjustment factor for cold water washing is applied. Thus, to account for the usage of cold w...
AI summary The text discusses the distribution of water heating sources for clothes washers, with 76% being electrical and 24% non-electrical. An adjustment factor of 0.67 is applied to account for cold water washing, based on a Hydro-Québec survey. Tables 105 and 106 provide calculations for electricity consumption of baseline and efficient washers.
Table 105: Electricity Consumption for Baseline Clothes Washers Energy Consumption Component Energy Consumption (kWh/year) Adjustment Factor for Electrical Water Heating Adjustment Factor for Cold Water Usage Adjusted Energy Consumption (k...
AI summary The text presents two tables comparing the electricity consumption of baseline and efficient clothes washers, including adjustments for water heating and cold water usage. It highlights the energy savings achieved by efficient models.
Table 107: Electrical Unitary Savings Value for the Clothes Washer Component of Efficient Washer-Dryer Combination Units Parameters Value Adjusted Energy Consumption of Baseline Clothes Washer [kWh/year] 416 Adjusted Energy Consumption of...
AI summary Table 107 presents the electrical unitary savings value for the clothes washer component of efficient washer-dryer combination units, showing a reduction in energy consumption from 416 kWh/year to 295 kWh/year, resulting in 121 kWh/year of energy savings.
Table 108: ENERGY STAR Certified Room Air Purifier Measure Summary Parameter Instant Savings Reference Measure Description and Identification Measure ENERGY STAR certified room air purifiers, rebated in store - Baseline New Non-ENERGY STAR...
AI summary Table 108 provides a summary of the ENERGY STAR certified room air purifier measure, including parameters such as installation rate, effective useful life, energy savings, and peak demand savings. The table includes details on unitary energy savings and peak demand-to-energy ratio.
The electrical unitary energy savings value is determined by using the following equation for ENERGY STAR certified room air purifiers. $$\begin{split} Energy \, Savings \, \left[ \frac{kWh}{year} \right] \\ &= \left[ CADR[cfm] \times \lef...
AI summary The document provides an equation to calculate the energy savings of ENERGY STAR certified room air purifiers, using parameters like CADR, EF, SBP, and HOU. Most values are derived from the 10 most sold models in 2024, with others based on the Savings Calculator for ENERGY STAR Qualified Appliances due to the absence of Canadian minimum requirements for air purifiers.
Table 109: Electrical Unitary Savings Values for ENERGY STAR Certified Room Air Purifiers Parameter Symbol Instant Savings Reference Clean Air Delivery Rate [cfm] CADR 172 Weighted average of the 10 most sold models in the 2024 tracking sh...
AI summary Table 109 provides electrical unitary savings values for ENERGY STAR certified room air purifiers, including parameters such as Clean Air Delivery Rate, efficiency for baseline and efficient units, annual operating hours, standby power, and unitary energy savings. These values are calculated using data from the 2024 tracking sheet and the Savings Calculator for ENERGY STAR Qualified Appliances.
Summary [Table](#page-190-1) 110 below presents a summary of the values used to calculate ENERGY STAR certified dishwasher savings. The detailed methodology follows.
AI summary Table 110 summarizes the values used to calculate ENERGY STAR certified dishwasher savings, with a detailed methodology provided in the proceeding.
Table 110: ENERGY STAR Certified Dishwasher Measure Summary Parameter Instant Savings Measure Description and Identification Measure ENERGY STAR certified dishwashers that use less than 250 kWh, rebated in store - Baseline New non-ENERGY S...
AI summary The table outlines the energy savings parameters for ENERGY STAR certified dishwashers, including unitary energy savings, peak demand-to-energy ratio, and installation rates. These measures are part of a broader program to promote energy efficiency.
The electrical unitary energy savings value is determined by using the following equation for ENERGY STAR certified dishwashers. $$\begin{split} \textit{Energy Savings} & \left[ \frac{kWh}{year} \right] \\ & = \left( \textit{Consumption}_{...
AI summary The text presents an equation for calculating the energy savings of ENERGY STAR certified dishwashers, using parameters such as consumption, operation percentage, water heating, and number of loads. A table is referenced for the parameters and resulting savings values.
Table 111: Electrical Unitary Savings Values for ENERGY STAR Certified Dishwashers Parameter Symbol Instant Savings Source Baseline Consumption [kWh] Consumptionbase 260 Average of non-ES models in Natural Resources Canada, Searchable prod...
AI summary Table 111 provides electrical unitary savings values for ENERGY STAR certified dishwashers, including baseline and efficient unit consumption, percentages of energy consumption for operation and water heating, and average annual load numbers. These figures are sourced from various organizations and surveys.
Table 112: Humidity Sensor for Bathroom Exhaust Fan Summary Parameter Instant Savings, EPI Reference Measure Description and Identification Measure Added humidity sensors on existing bathroom exhaust fans with direct installation - Baselin...
AI summary Table 112 details the installation of humidity sensors on existing bathroom exhaust fans as part of the Efficient Product Installation (EPI) program. The measure includes parameters such as energy savings, peak demand savings, and the effective useful life of the sensors, with references to specific subsections for further details.
The electrical unitary energy savings for humidity sensor for bathroom exhaust fan are calculated using the variables defined and listed in the equation and Table 113 below. $$Energy \ Savings_{fan} \ \left[\frac{kWh}{year}\right] = \% \ S...
AI summary The document discusses the calculation of energy savings for a humidity sensor in a bathroom exhaust fan, using specific equations and data from Table 113. The equations account for variables such as fan usage, airflow, efficiency, and heating energy savings based on humidity and temperature changes.
Table 113: Electrical Savings Values for Humidity Sensors for Bathroom Exhaust Fans Parameter Symbol EPI Reference Fan Efficiency [CFM/W] 𝜂𝑓𝑎𝑛 3.5 ENERGY STAR min standard, 2024175 Savings Percentage % Savings 50% Demand controlled ventila...
AI summary Table 113 presents electrical savings values for humidity sensors used in bathroom exhaust fans, including fan efficiency, savings percentage, fan exhaust rate, annual operating hours, and annual energy savings. These values are based on standards and studies from various sources, and the savings are attributed to demand-controlled ventilation.
Table 114: Electrical Heating per Heating Source Savings Values for Humidity Sensors for Bathroom Exhaust Fans Parameter Symbol EPI Reference Density of Air [kg/m3 ] 𝜌 1.293 Convention Heat Capacity of Air [J/kg/°C] 𝐶𝑝 1005 Convention Fan...
AI summary The text presents two tables detailing energy savings values for humidity sensors used in bathroom exhaust fans, including parameters such as air density, heat capacity, operating hours, and COP for different heating sources. The tables also show energy savings calculations for electric resistance and heat pumps.
2.5 Plug Load Controls
AI summary The section titled '2.5 Plug Load Controls' is introduced, though no further details or content are provided in the text. The topic likely relates to energy efficiency measures targeting plug loads within demand-side management initiatives.
Table 116: Interactive Effects Factors for Plug Load Control Measures Measure Interactive Effects Factor for Energy Savings Interactive Effects Factor for Peak Demand Savings Reference Smart Power Controller for Audiovisual Equipment 0% 0%...
AI summary The text presents Table 116, which outlines interactive effects factors for plug load control measures, focusing on energy savings and peak demand savings. The table includes measures such as smart power controllers and timers, though many entries are incomplete. The section also references peak demand savings factors in 2.5.2.
Table 117: Peak Demand-to-energy Ratios for Plug Load Control Measures Measure Peak Demand-to-energy Ratio (W/kWh) Source Smart Power Controller for Audiovisual Equipment 0.000 RES-Plug Load Controls, Navigant Power Bar with Integrated Tim...
AI summary Table 117 presents peak demand-to-energy ratios for various plug load control measures, including a smart power controller and an ENERGY STAR certified pool pump. The table includes sources such as RES-Plug Load Controls and Navigant, and references the 2016-2018 DSM Plan.
Summary [Table](#page-196-2) 118 presents a summary of the values used to calculate smart power controller for audiovisual equipment savings. The detailed methodology follows.
AI summary Table 118 summarizes the values used to calculate smart power controller for audiovisual equipment savings, with a detailed methodology provided subsequently.
Table 118: Smart Power Controllers for Audiovisual Equipment Measure Summary Parameter EPI Instant Savings Reference Measure Description and Identification Measure Smart power controllers for audiovisual equipment with direct installation...
AI summary This table provides a summary of the Smart Power Controllers for Audiovisual Equipment Measure, including details on installation rates, effective useful life, and energy savings parameters for two programs: EPI and Instant Savings. It outlines the baseline, measure subcategories, and references for further information.
Smart power bars rebated under EPI are classified as Tier 2, while those rebated under Instant Savings are classified as Tier 1. Tier 1 smart power bars have a master outlet that switches off other outlets when the master device is turned...
AI summary The document discusses the classification of smart power bars under two rebate programs, EPI and Instant Savings, with Tier 1 and Tier 2 having different functionalities and energy savings. The energy savings values are based on a 2019 study conducted in Massachusetts.
Table 121: Power Bar with Integrated Timer Measure Summary Parameter Instant Savings Reference Measure Description and Identification Measure Description Power bars with integrated timer rebated in store - Baseline Power bars without an in...
AI summary Table 121 outlines the Power Bar with Integrated Timer Measure Summary, including parameters such as measure description, baseline, installation rate, effective useful life, and electrical savings parameters like unitary energy savings and peak demand-to-energy ratio. The table provides details on the energy and demand savings associated with this measure.
Table 122: Electrical Unitary Savings Value for Power Bars with Integrated Timers Parameter Entertainment Centre Computer System Lighting Other Proportion 40.3% 15.7% 19.4% 24.6% Average Standby Wattage 38.1 W 28 W 21.6 W186 28 W Old Opera...
AI summary Table 122 outlines the electrical unitary savings value for power bars with integrated timers across different categories such as entertainment centres, computer systems, lighting, and others. It provides data on proportion, average standby wattage, operating time, and calculated energy savings in kWh/year.
Table 123: Heavy-duty Outdoor Timer Measure Summary Parameter Instant Savings Reference Measure Description and Identification Measure Description Heavy-duty outdoor timers rebated in store - Baseline Outdoor outlets without timers General...
AI summary Table 123 summarizes the Heavy-duty Outdoor Timer Measure, including parameters like installation rate, energy savings, and peak demand savings. The measure involves rebating heavy-duty outdoor timers, with a baseline of outdoor outlets without timers. Energy savings are estimated at 122 kWh/year, and the peak demand-to-energy ratio is 0.000.
For heavy-duty outdoor timers, the electrical unitary energy savings value of 122 kWh is based on the results of the OPA 2012 Consumer Program Evaluation.[187](#page-0-0) The survey conducted for that evaluation states that heavy-duty outd...
AI summary The electrical unitary energy savings value of 122 kWh for heavy-duty outdoor timers is based on the OPA 2012 Consumer Program Evaluation. These timers are used for outdoor lighting, pool pumps, and car block heaters, similar to those sold through the Instant Savings program. Table 124 provides the annual unitary savings value for Instant Savings.
Table 124: Electrical Unitary Savings Values of Heavy-duty Outdoor Timers Parameter Value Source Unitary Energy Savings [kWh/year] 122 OPA, 2012188 Installation Rates
AI summary Table 124 presents the electrical unitary savings values of heavy-duty outdoor timers, with a unitary energy savings value of 122 kWh/year, sourced from the Ontario Power Authority in 2012188. The table also includes a section on installation rates.
(4) ENERGY STAR Certified Pool Pumps
AI summary The section discusses ENERGY STAR Certified Pool Pumps, likely in the context of energy efficiency programs and regulations in Nova Scotia. It may involve topics such as appliance standards and energy efficiency initiatives.
Summary [Table](#page-0-3) 125 presents a summary of the values used to calculate ENERGY STAR certified pool pump savings. The detailed methodology follows.
AI summary Table 125 summarizes the values used to calculate ENERGY STAR certified pool pump savings, with a detailed methodology provided afterward.
Table 125: ENERGY STAR Certified Pool Pump Measure Summary Parameter Instant Savings Reference Measure Description and Identification Measure Description ENERGY STAR certified pool pumps rebated in store - Baseline Standard efficiency elec...
AI summary This table provides a summary of the ENERGY STAR certified pool pump measure, including details on energy savings, installation rates, and useful life. It references a report from Research into Action presented to the Ontario Power Authority in 2013.
The electrical unitary energy savings values of ENERGY STAR certified pool pumps are calculated using the equations below. $$Energy \, Savings \, \left[ \frac{kWh}{yr} \right] = Base \, Consumption - Reduced \, Consumption$$ $$Base \, Cons...
AI summary The document outlines the calculation of energy savings for ENERGY STAR certified pool pumps using specific equations. It references the 2020 NEEP TRM189 and a Pool Pump Demand Response Potential Report, noting that savings are based on differences in consumption due to changes in pump speed and operation time, as dictated by pump affinity laws.
Table 126: Unitary Savings Values of ENERGY STAR Certified Pool Pumps Parameter Value Reference Average Power [kW] 1.36 Pool Pump Demand Response Potential Report, 2008 191 Old Operating Time [h/day] 5.18 Pool Pump Demand Response Potentia...
AI summary Table 126 presents unitary savings values for ENERGY STAR certified pool pumps, including parameters such as average power, operating time, and energy savings. The table includes references to reports and assumptions used in the calculations.
Table 127: Three-element Water Heater Measure Summary Parameter Green Heat Reference Measure Description and Identification Measure Description Three-element water heaters rebated after purchase - Baseline Conventional two-element water he...
AI summary The table outlines a program offering rebates for the purchase of three-element water heaters, with a focus on peak demand savings. No energy savings are expected from this measure, and the baseline is conventional two-element water heaters. The effective useful life is 12 years, and the unitary peak demand savings are 200 W.
Table 128: Domestic Water Heater Timer Measure Summary Parameter Green Heat Reference Measure Description and Identification Measure Description Domestic water heater timers rebated after purchase - Baseline Electric water heaters without...
AI summary Table 128 summarizes the Domestic Water Heater Timer Measure, including details such as installation rate, useful life, and peak demand savings. The measure involves rebating timers for electric water heaters, with a focus on energy efficiency and demand management.
Table 129: Electric Thermal Storage Measure Summary Parameter Green Heat Reference Measure Description and Identification Measure Description Electric thermal storage systems rebated after purchase - Baseline Heating systems without electr...
AI summary The table outlines the Electric Thermal Storage Measure Summary, indicating that no energy savings are expected from the Green Heat program. The measure involves rebating electric thermal storage systems after purchase, with a baseline of heating systems without such systems. Installation rates and other parameters are detailed in the document.
Table 130: Domestic Water Heater Load Control Measure Summary Parameter Demand Response Reference Measure Description and Identification Measure Direct load control for domestic water heaters with direct installation - Baseline Domestic wa...
AI summary Table 130 outlines the Domestic Water Heater Load Control Measure Summary, including parameters like installation rate, effective useful life, and available DR capacity. It provides details on energy savings and demand response for direct load control measures applied to domestic water heaters.
Table 131: Domestic Water Heater Load Control Measure In-service Rates Type In-service Rate Margin of Error Source Shifted 81% 4% Residential DR 2023 Evaluation 2.7 Renewables
AI summary Table 131 presents the in-service rate for the Domestic Water Heater Load Control Measure at 81% with a 4% margin of error, sourced from the Residential DR 2023 Evaluation. The section also introduces a discussion on renewables under section 2.7.
Table 133: Electrical Savings Values for SolarHomes Parameter Symbol Value Reference Modelled Energy Production [kWh] - Varies per project Project documentation, using PV Watts Snow Loss Factor [%] - For panel tilt angles ≥ 25°: 1% Norther...
AI summary Table 133 outlines the electrical savings values for the SolarHomes program, including parameters such as modelled energy production, snow loss factors, adjustment ratios, and unitary energy savings. Savings are calculated by multiplying system capacity in kW by a factor of 1,086 kWh/kW, derived from calibrated data.
3 Effective Useful Life This section outlines the EUL values used to calculate lifetime energy savings. This section also presents EUL values for demand reduction measures; these values are not used to calculate lifetime energy savings sin...
AI summary This section defines Effective Useful Life (EUL) values for calculating lifetime energy savings and demand reduction measures. It clarifies that EUL for demand response measures reflects the persistence of demand reduction, not energy savings, and emphasizes using EUL in cost-effectiveness ratio calculations to capture lifetime benefits.
3.1 LED Lamps and Fixtures To establish lifetime energy savings for LED lamps and fixtures, the equipment life is determined using rated lifetimes identified in product specification sheets and annual HOU, as described in the equation belo...
AI summary The document discusses the calculation of equipment life for LED lamps and fixtures using rated lifetimes and annual HOU, and the need to adjust equivalent EUL values annually due to regulatory changes affecting baseline energy use over time.
Table 134: EUL Values for Residential LED Lamps and Fixtures Measure Program Component Average Rated Lifetime (hours) Annual HOU (hours/year) Equipment Life (years) 2024 Equivalent EUL (years) LED A19 Lamps 9 W Replacing 25 W EPI 25,000 94...
AI summary Table 134 presents EUL (Effective Useful Life) values for various residential LED lamps and fixtures, including details on average rated lifetime, annual HOU (hours of use), equipment life, and 2024 equivalent EUL. The table includes data for different wattage replacements, types of lamps, and programs such as EPI and Instant Savings.
Table 135: EUL Values and Sources for Non-LED Lighting Residential Measures Measure Name Appliances Clotheslines and Outdoor Drying Racks Instant Savings 10 IESO PMA List, 2019 (Value for indoor clothes drying racks, retractable clotheslin...
AI summary Table 135 outlines the Energy Use Life (EUL) values and sources for non-LED lighting residential measures, including clotheslines, drying racks, and refrigerator retirements and replacements. The table provides data on the EUL values, associated programs, and the sources used to calculate these values.
200 Retrieved from [https://energy.gov/energysaver/heat-and-cool/heat-pump-systems/geothermal-heat-pumps#306534-tab-1.](https://energy.gov/energysaver/heat-and-cool/heat-pump-systems/geothermal-heat-pumps#306534-tab-1) 201 Retrieved from [...
AI summary The document provides data on the effective useful life (EUL) of various energy efficiency measures, including water heaters, heat pumps, and insulation. It references studies and reports from organizations such as Hydro-Québec, NREL, and the California Public Utilities Commission to support these estimates.
Table 136: Commercial Measure Assessment Change Log Change Type Section Description Date Update 1.1.1(2) Advanced RTU Controls Update savings calculation methodology 2023-03-09 Update 3.1 EUL - LED Lamps and Fixtures Appendix II Update EUL...
AI summary This table outlines changes to the Commercial Measure Assessment, including updates to savings calculations, new measures like compressed air leak repairs and variable frequency drives, and removal of the booster pump. It also notes the creation of separate residential and commercial reports and the addition of LED roadway lighting and smart thermostats for electric heating.
Table 137: Included Commercial Measures Program Components Lighting LED Lamps SBES LED Linear Fixtures BER-IR, BER-AR, SBES LED Linear Lamps BER-IR, BER-AR, SBES LED Outdoor Fixtures BER-IR, BER-AR, SBES LED Directional and Architectural F...
AI summary Table 137 outlines included commercial measures under various program components, such as lighting, pumps, heating, HVAC, water heating, and compressed air. Each component is associated with specific programs like BER-AR, SBES, and Custom, indicating the initiatives supporting these measures.
5.1.1 Interactive Effects The interactive effects methodology for commercial lighting was reviewed as part of the 2024 DSM Measure Assessment update. The updated interactive effect factors and methodology are presented in [Appendix IV.](#p...
AI summary The interactive effects methodology for commercial lighting was reviewed in the 2024 DSM Measure Assessment update. Updated factors will be applied in 2025, aligning with BER-AR adjustment ratios. The 2024 factors remain unchanged from 2023 and are based on building type and heating/cooling systems.
Table 138: BER-AR Interactive Effects (IE) Factors for Lighting IE Energy Building Type IE Peak Demand (if electrical heating) Electrical Heating Electrical Cooling Electrical Heating and Cooling Agriculture 0.75 0.81 1.04 0.85 Banking / F...
AI summary The document discusses interactive effects factors for lighting in different building types, based on data from BER-AR and SBES programs. These factors are used to calculate energy and peak demand savings, with adjustments made for recessed fixtures. The methodology follows ASHRAE guidelines and applies a 57% multiplier for limited interaction with heating and cooling systems.
Table 140: Interactive Effects for BNI Lighting Measures Measure Interactive Effects Factor for Energy Savings Interactive Effects Factor for Peak Demand Savings BER Instant Rebates Linear LED Fixtures Recessed -8.7% x 57% = -4.9% -16.1% x...
AI summary Table 140 presents interactive effects factors for energy and peak demand savings associated with various BNI lighting measures, including LED fixtures, occupancy sensors, and other efficiency initiatives, showing varying degrees of impact depending on the type and installation.
Unitary Peak Demand Savings Calculations Peak demand savings are calculated by multiplying the unitary demand savings value by the peak coincidence factor as detailed in the equation below. () = () × (%) The unitary demand savings value co...
AI summary Peak demand savings are calculated by multiplying unitary demand savings by a peak coincidence factor. Unitary demand savings are derived by dividing unitary energy savings (in kWh) by hours of use (HOU), then converting to watts (W) via multiplication by 1,000. The methodology emphasizes quantifying energy efficiency impacts through standardized formulas.
Table 141: 2023 Lighting Gross Savings Adjustments Ratios Program Component Source Evaluation Energy Savings Peak Demand Savings Report Adjustment Ratio Margin of Error Adjustment Ratio Margin of Error SBES Lighting Measures 2023 1.070 5.3...
AI summary Table 141 presents 2023 Lighting Gross Savings Adjustments Ratios for various programs, including SBES Lighting Measures and BER-AR Lighting Measures. The table includes adjustment ratios and margin of error for both energy savings and peak demand savings across different program components.
(1) LED Lamps
AI summary The document begins a section on LED lamps, likely discussing their role in energy efficiency programs. No specific claims or entities are mentioned in the provided text.
Table 142: LED Lamp Measure Summary Parameter SBES Reference Measure Description and Identification Measure Description LED lamps installed with direct installation - Baseline Existing lighting being replaced Measure Subcategory A-type, re...
AI summary Table 142 provides a summary of LED lamp measures, including installation rates, energy savings adjustment ratios, peak demand savings, and useful life. The table also references additional details in subsections and other tables for specific calculations and variations.
The equation below is used to determine the unitary savings values of LED lamps for each pairing of old and new wattages. Table 143 below lists the parameters and corresponding values used in the equation and the resulting unitary savings...
AI summary The document presents an equation to calculate the annual energy savings of LED lamps by comparing old and new wattages, taking into account operating hours. Table 143 provides the parameters and corresponding values used in the calculation.
Table 144: Electrical Unitary Peak Demand Savings Values for LED Lamps Type of LED Displaced Wattage (W) Peak Coincidence Factor (%) Unitary Peak Demand Savings Value (W) 9 W Replacing 25 W 16 54% 8.6 9 W Replacing 29 W 20 10.8 9 W Replaci...
AI summary Table 144 presents electrical unitary peak demand savings values for various LED lamps replacing traditional incandescent bulbs. The table includes different types of LEDs, the wattage they replace, peak coincidence factors, and corresponding savings in wattage.
Summary [Table](#page-27-0) 145 presents a summary of the values used to calculate linear LED fixture savings, followed by the detailed methodology.
AI summary Table 145 summarizes the values used to calculate linear LED fixture savings, followed by a detailed methodology explaining the calculations.
Table 145: Linear LED Fixture Measure Summary Parameter BER-IR BER-AR SBES Reference Measure Description and Identification Measure Linear LED fixtures (Luminaires, Retrofit Kits, Linear Ambient and Low bay Luminaires), rebated in store Li...
AI summary Table 145 provides a summary of parameters related to linear LED fixture measures, including baseline fixtures, energy savings adjustment ratios, peak demand savings, effective useful life, and interactive effects based on fixture type and facility characteristics.
Table 146: Electrical Unitary Energy Savings Values for Linear LED Fixtures Parameter Symbol Value for BER-IR Value for BER AR and SBES Reference Baseline Wattage [W] 𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑊𝑎𝑡𝑡𝑎𝑔𝑒 Fixed baseline based on fixture type and lumen output A...
AI summary Table 146 outlines the electrical unitary energy savings values for linear LED fixtures, detailing parameters such as baseline wattage, new wattage, and hours of operation. It references Table 147 for baseline wattage calculations based on lumens output for T8 fluorescent luminaires.
Table 147: Linear LED Fixture Baseline Wattages for BER-IR Subcategory Lumens Output (lm) Baseline Wattage (W) 1 x 4 Luminaires 1,500 – 3,500 61.0 ≥ 3,500 83.3 2 x 2 Luminaires & Retrofit Kits 1,500 – 4,500 61.0 ≥ 4,500 84.0 2 x 4 Luminair...
AI summary Table 147 outlines baseline wattages for linear LED fixtures under the Building Energy Retrofit - Instant Rebate (BER-IR) program. It categorizes luminaires by subcategory, lumens output, and corresponding baseline wattage, providing data for energy efficiency assessments and rebate calculations.
Summary [Table](#page-29-0) 148 presents a summary of the values used to calculate linear LED lamp savings. The detailed methodology follows.
AI summary Table 148 summarizes the values used to calculate linear LED lamp savings, with a detailed methodology provided in the proceeding document.
Table 148: Linear LED Lamp Measure Summary Parameter BER-IR BER-AR SBES Reference Measure Description and Identification Measure Linear LED lamps, rebated in store Linear LED lamps, rebated after installation See Table 147 for BER-IR basel...
AI summary Table 148 provides a summary of parameters for the Linear LED Lamp Measure, including baseline measures, energy savings adjustment ratios, effective useful life, and interactive effects for recessed and non-recessed lamps. It references Subsections 5.1.1, 5.1.2, 5.1.3, and 6.1 for detailed calculations and explanations.
$$Energy \, Savings \, \left[\frac{kWh}{yr}\right] \\ = \frac{\left(Baseline \, Wattage \, [W] \times Ballast \, Factor \, \times Baseline \, Quantity - New \, Wattage [W] \, \times New \, Quantity\right) \times HOU\left[\frac{h}{day}\righ...
AI summary The text provides a mathematical formula for calculating annual energy savings in kilowatt-hours, based on baseline and new wattage, ballast factor, quantity, and hours of use per day.
Table 151: Outdoor LED Fixture Measure Summary Parameter BER-IR BER-AR SBES Reference Measure Description and Identification Measure Outdoor LED fixtures, rebated in store Outdoor LED fixtures, rebated after installation See Table 153 and...
AI summary Table 151 presents a summary of outdoor LED fixture measures, including details on baseline fixtures, energy savings adjustment ratios, peak demand savings, and useful life. The table compares different rebate programs such as BER-IR and BER-AR, and references specific subsections for further details on calculations and parameters.
Table 152 lists the parameters and corresponding values used in the equation below to calculate unitary energy savings for outdoor LED fixtures. $$Energy \ Savings \ \left[\frac{kWh}{yr}\right] = \frac{(Baseline \ Wattage - New \ Wattage)[...
AI summary The text presents a formula for calculating annual energy savings in kilowatt-hours for outdoor LED fixtures by using baseline and new wattage values, along with hours of operation per day.
Table 152: Electrical Unitary Energy Savings Values for Outdoor LED Fixtures Parameter Symbol Value for BER-IR Value for BER- AR and SBES Reference Baseline Wattage [W] Baseline Wattage Based on fixture type and lumen output Actual IR: See...
AI summary Table 152 outlines electrical unitary energy savings values for outdoor LED fixtures, including baseline and new wattage, hours of operation, and energy savings calculations. The data is based on fixture type, lumen output, and specification data for each rebated unit.
Lumens Range MH Baseline Fixture Wattage (W) HPS Baseline Fixture Wattage (W) Weighted Average Baseline Wattage (W) ≥ 300 and < 2,000 43 46 44.5 ≥ 2,000 and < 5,000 95 95 95.0 ≥ 5,000 and < 15,000 295 250 272.5 ≥ 15,000 and < 25,000 458 46...
AI summary The document presents tables comparing the wattage of baseline fixtures (MH and HPS) across different lumens ranges for architectural flood and spot luminaires. These tables are used to calculate energy savings for efficient LED fixtures. The baseline data is derived from the Duke Energy Fixture Wattage Table.
Table 155: Directional and Architectural LED Fixture Measure Summary Parameter BER-IR BER-AR SBES Reference Measure Description and Identific cation Measure Directional and architectural LED fixtures, rebated in store Directional an LED fi...
AI summary Table 155 provides a summary of energy savings parameters for directional and architectural LED fixtures under various programs, including baseline measures, energy savings adjustment ratios, and useful life estimates. The table references additional details in other sections of the document.
Table 156 lists the parameters and corresponding values used in the equation below to calculate unitary energy savings for directional and architectural LED fixtures. $$Energy \ Savings \ \left[\frac{kWh}{yr}\right] = \frac{(Baseline \ Wat...
AI summary The text provides a formula for calculating annual energy savings in kilowatt-hours for directional and architectural LED fixtures, using baseline and new wattage values, along with hours of use per day.
Table 156: Electrical Unitary Energy Savings Values for Directional and Architectural LED Fixtures Parameter Symbol Value for BER-IR Value for BER AR and SBES Reference Baseline Wattage [W] 𝐵𝑎𝑠𝑒𝑙𝑖𝑛𝑒 𝑊𝑎𝑡𝑡𝑎𝑔𝑒 Based on fixture type and lumen...
AI summary Table 156 outlines electrical unitary energy savings values for directional and architectural LED fixtures, comparing baseline and new wattage, hours of operation, and energy savings calculations. The baseline technology is halogen lamps with a lumens output of 17 lumens/W.
Table 157: Directional and Architectural LED Fixture Baseline Wattages for BER-IR Category Lumens Baseline Wattage (W) Track or Mono-point Directional Luminaires ≥ 250 60.4 Wall-wash Luminaires 517 - 1199 50.0 ≥ 1,200 100 In-service Rate
AI summary Table 157 provides baseline wattages for directional and architectural LED fixtures under the Building Energy Retrofit - Instant Rebate (BER-IR) program, categorizing luminaires by type and lumens. The table includes specific wattage values for different fixture categories.
Summary [Table](#page-36-1) 158 presents a summary of the values used to calculate occupancy/motion sensor savings. The detailed methodology follows.
AI summary Table 158 summarizes the values used to calculate occupancy/motion sensor savings. The detailed methodology for these calculations is provided in the document.
Table 158: Occupancy/Motion Sensor Measure Summary Parameter BER-IR BER-AR SBES Reference Measure Description and Identification Measure Occupancy/Motion sensors, rebated in store Occupancy/Motion sensors, rebated after installation - Base...
AI summary Table 158 provides a summary of occupancy/motion sensor measures, including details on energy savings adjustment ratios, peak demand savings, effective useful life, and other parameters. It outlines differences between BER-IR and BER-AR programs and references subsections for further details.
[Table](#page-37-0) 159 lists the parameters and corresponding values used in the equation below for occupancy and motion sensors and the resulting unitary values. Energy Savings $$\left[\frac{kWh}{yr}\right]$$ = Connected Wattage (W) × Sa...
AI summary The text provides a formula for calculating energy savings based on connected wattage, savings factor, OTF, and HOU. It references a table and an image that likely contain specific parameters and values used in the equation.
Table 159: Electrical Unitary Energy Savings Values for Occupancy/Motion Sensors Parameter Type of Occupancy Sensor Value for BER-IR Value for BER AR and SBES Reference Connected Wattage (W) Interior 110 Actual Average connected wattage fo...
AI summary Table 159 presents electrical unitary energy savings values for occupancy/motion sensors, including connected wattage, savings factors, and hours of operation. The data is based on installations through BER-AR and SBES from 2021 to 2023, with some values derived from the 2023 Efficiency Vermont TRM.
Table 160: Savings Factor per Control Type Control Type Savings Factor % Wall Occupancy Sensors 24% Fixture Mounted Occupancy 24% Remote Mounted Occupancy 24% Refrigerator Case Controls 40% Freezer Case Controls 40% Exterior Occupancy 41%...
AI summary Table 160 presents savings factors for various control types, including occupancy and daylight sensors, as well as refrigerator and freezer case controls. These percentages indicate the energy savings associated with each control type, which may be relevant for energy efficiency programs and cost calculations.
Table 161: LED Nightlight Measure Summary Parameter SBES Reference Measure Description and Identification Measure LED nightlights through direct installation N/A Baseline Existing nightlight being replaced, which must be incandescent Gener...
AI summary Table 161 outlines the LED nightlight measure summary, including parameters such as installation rate, energy savings adjustment ratio, and unitary energy savings. It provides details on the measure description, baseline, and various energy and demand savings factors.
Table 162 lists the parameters and corresponding values used in the equation below for LED nightlights and the resulting unitary values. The values for displaced wattages and hours of operation are consistent with the values used by other...
AI summary Table 162 presents parameters and values used in an energy savings equation for LED nightlights, with displaced wattages and hours of operation aligned with those used in Pennsylvania. The equation calculates annual energy savings in kWh based on old and new wattage, hours of operation, and a conversion factor.
Table 162: Electrical Unitary Energy Savings Values for LED Nightlights Parameter Value Reference Old Wattage [W] 7.0 Assumption based on the typical wattage value of an incandescent nightlight New Wattage [W] 0.3 Wattage value of the LED...
AI summary Table 162 provides energy savings values for LED nightlights compared to traditional incandescent models. It includes parameters such as old and new wattage, average displaced wattage, hours of operation, and annual unitary energy savings. The table is used to calculate unitary peak demand savings as outlined in Subsection 5.1.2.
Table 163: LED Roadway Lighting Measure Summary Parameter BER-AR Reference Measure Description and Identification Measure LED, DLC Premium qualified roadways lighting with a minimum efficacy of 150 lm/W, with advanced dimming based on real...
AI summary Table 163 summarizes the LED roadway lighting measure, including details such as the measure description, baseline, installation rate, effective useful life, and energy savings parameters. The table provides data on unitary energy savings, peak demand savings, and interactive effects factors.
Table 164 lists the parameters and corresponding values used in the equation below for LED roadway lighting and the resulting unitary values. $$Energy \ Savings \ \left[\frac{kWh}{yr}\right] = \frac{(Old \ Wattage - New \ Wattage)[W] \time...
AI summary Table 164 presents parameters and values used in an equation to calculate annual energy savings for LED roadway lighting, based on the difference in wattage between old and new lighting and annual hours of use.
Table 164: Electrical Unitary Energy Savings Values for LED Roadway Lighting Parameter Value Reference Old Wattage [W] Actual Use information in TS New Wattage [W] Actual Use information in TS Hours of Operation [hrs/year] Actual or 4662 C...
AI summary Table 164 outlines the parameters and calculations for determining electrical unitary energy savings from LED roadway lighting, including old and new wattage, hours of operation, and energy savings calculations based on specification data for each rebated unit.
Summary Table 165 presents a summary of the values used to calculate savings for horticultural lighting. The detailed methodology follows.
AI summary Table 165 outlines the values used to calculate savings for horticultural lighting, with a detailed methodology provided in the proceeding.
Table 165: Horticultural Lighting Measure Summary В ER-AR Baseline Existing lighting Metal halide HID fixtures
AI summary Table 165 provides a summary of the Horticultural Lighting Measure, with the baseline lighting system identified as existing metal halide HID fixtures.
Table 166 lists the parameters and corresponding values used in the equation below for horticultural lighting and the resulting unitary values. $$\label{eq:unitary_energy_savings} Unitary_{bounds} \left[ \frac{kWh}{yr} \right] = \frac{(W_b...
AI summary The text provides a mathematical equation used to calculate unitary energy savings for horticultural lighting, including parameters such as power consumption, quantity, hours of use per year, and an efficiency factor. A reference to an image is also included.
5.2.4 Pump Measures
AI summary The section '5.2.4 Pump Measures' outlines regulatory considerations for heat pump technologies, including efficiency standards, rebate programs, and compliance with energy codes like NECB 2020. It addresses implementation challenges, cost recovery, and performance metrics for heat pump adoption in residential and commercial sectors.
Summary Table 168 presents a summary of the values used to calculate circulator pump savings. The detailed methodology follows.
AI summary Table 168 summarizes the values used to calculate circulator pump savings, with the detailed methodology provided in the following sections.
Table 168: Circulator Pump Measure Summary Parameter BER-IR, BER-AR Reference Measure Description and Identifica ation Measure ed electronically concinculator pumps, - Baseline Single-speed d circulator pump Measure Subcategory Max input p...
AI summary Table 168 provides a summary of circulator pump measures, including baseline and measure descriptions, installation rates, effective useful life, and energy savings parameters such as unitary energy savings and peak demand savings.
Table 169: Electrical Unitary Energy Savings Values for Circulator Pumps Parameters Symbol Max Input Power < 150 W Max Input Power ≥ 150 W and < 500 W Max Input Power ≥ 500 W and < 2,500 W Reference Vermont Average Unitary Energy Savings [...
AI summary Table 169 presents electrical unitary energy savings values for circulator pumps in different power ranges, comparing Vermont and Nova Scotia average operating hours and calculating unitary energy savings based on these values.
The electrical unitary energy savings for booster pumps are calculated using the variables defined and listed in the equation and [Table](#page-48-0) 172 below. Energy Savings $$_{kWh} = 891.20 \times HP_{ee} + 3,523.08 \times \Delta HP_{s...
AI summary The document provides a formula for calculating electrical unitary energy savings for booster pumps, using variables HPee and ΔHPsys, with specific coefficients. A table on page 48-0 is referenced for further details on the variables.
Table 172: Electrical Unitary Energy Savings Values for Booster Pumps Parameter Symbol BER-AR Reference Rated Horsepower of the New Booster Pump or Pumping System [HP] 𝐻𝑃𝑒𝑒 Specification data for each system Tracking sheet Reduction in the...
AI summary Table 172 provides electrical unitary energy savings values for booster pumps, including parameters such as rated horsepower, energy savings per horsepower, and annual unitary energy savings. The data includes values derived from a 2020 Hawaii TRM218 reference and calculation results.
(1) Electric Thermal Storage
AI summary The document section titled 'Electric Thermal Storage' likely discusses energy efficiency programs involving electric thermal storage technology, though no detailed content is provided in the text chunk. The heading suggests a focus on residential or commercial heating solutions using thermal storage systems.
Table 175: Electric Thermal Storage Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure load, rebated after installation Electric thermal storage systems to reduce peak demand space heating - Base...
AI summary Table 175 provides a summary of electric thermal storage measures, including parameters such as measure description, baseline, installation rate, energy savings adjustment ratios, and effective useful life. It also references subsections for detailed calculations and considerations.
Table 176: Advanced RTU Control Measure Summary Parameter BER-AR Reference Measure Description and Identification Measure Advanced RTU controls that include demand-controlled ventilation (DCV) and an optional variable frequency drive (VFD)...
AI summary Table 176 outlines the parameters for advanced RTU control measures, including energy savings adjustment ratios, effective useful life, and calculation methods for unitary energy and peak demand savings. These measures include demand-controlled ventilation and variable frequency drives.
$$\begin{split} Energy \, Savings \, _{kWh} \\ &= \frac{1}{12,\!000} \, \times \left( Capacity_{cool} \times (AC \times CESF_{DCV} + VFD \times FESF_{VFD} \,) \right. \\ &+ ElecHeat \times \frac{Capacity_{heat} \times HESF_{DCV}}{COP_{heat...
AI summary The text presents a mathematical formula for calculating energy savings in kWh, incorporating factors such as cooling and heating capacities, efficiency factors for demand-controlled ventilation and variable frequency drives, and the coefficient of performance for heating systems.
Table 177: Electrical Unitary Energy Savings Values for Advanced RTU Controls Parameter Symbol BER-AR Reference Facility Type Supply Fan Energy Savings Factors from VFD224 [kWh/tonne] Cooling Energy Savings Factors for DCV225 [kWh/tonne] H...
AI summary Table 177 presents electrical unitary energy savings values for advanced RTU controls across various facility types, including cooling and heating energy savings factors for DCV and supply fan energy savings factors from VFD.
(3) Smart Thermostats for Electric Heating
AI summary The document discusses the role of smart thermostats in electric heating within Nova Scotia's regulatory framework, focusing on their integration into demand-side management (DSM) programs and energy efficiency initiatives. It highlights regulatory considerations, program design, and potential impacts on consumer behavior and grid management.
Table 180: Smart Thermostat for Electric Heating Measure Summary Parameter BER-AR, BER-IR, SBES Reference Measure Description and Identification Measure Smart thermostats for electric baseboards, in floor radiant heating, and heat pumps, r...
AI summary Table 180 outlines the Smart Thermostat for Electric Heating Measure, detailing energy and peak demand savings adjustment ratios, effective useful life, and unitary energy savings for various heating systems such as electric baseboards, in-floor heating, and heat pumps.
The electrical unitary energy savings for smart thermostats for electric baseboards for commercial applications are assumed to be equal to the savings for a residential application because the heating power of controlled thermostats is exp...
AI summary The text discusses the assumption that smart thermostat energy savings for commercial electric baseboards are similar to residential applications. It references a formula for calculating energy savings and cites studies on Nest thermostats for central heating systems, noting a 12% savings for air-source heat pumps as a relevant benchmark.
Table 181: Billing Analysis Savings Results for Smart Thermostats for Electrical Heating Systems Jurisdiction Measure Sample Size Heating Consumption Savings Oregon231 Nest thermostats 185 12% (for ASHPs) Bonneville Power Administration232...
AI summary Table 181 presents billing analysis savings results for smart thermostats used in electrical heating systems in Oregon and by the Bonneville Power Administration. The data shows a 12% heating consumption savings for air-source heat pumps (ASHPs) with Nest thermostats, based on a sample size of 185 and 176 respectively.
Table 182: Electrical Unitary Energy Savings Calculation for Smart Thermostats for Electric Heating Parameter Symbol Value for Electric Baseboard Value for MSHP Value for Electric In-floor Heating Value for Central Heat Pumps Reference Ave...
AI summary Table 182 provides a calculation of electrical unitary energy savings from smart thermostats for different heating systems, including electric baseboard, MSHP, electric in-floor heating, and central heat pumps. The table includes parameters such as average heating energy consumption, savings percentage, and coefficient of performance (COP). The calculation assumes no peak demand savings from smart thermostats.
Table 183: Air-source Heat Pumps Less Than 65,000 Btu/h, Measure Summary Parameter BER-AR SBES AMH (prescriptive) AMH (comprehensive) Reference Measure Description and Identification Measure Air-source heat pump less than 65,000 Btu/h used...
AI summary Table 183 summarizes air-source heat pumps under 65,000 Btu/h, including parameters like energy savings adjustment ratios, peak demand savings, and useful life. The table references specific subsections and calculation methods for energy and peak demand savings, with a note about the adjustment ratio being temporary for the 2024 AMH evaluation.
The electrical unitary energy savings for ASHPs of less than 65,000 Btu/h (excluding air-to-water) are calculated using the variables defined and listed in the equation[237](#page-60-0) and [Table](#page-60-1) 184 below.
AI summary The document discusses the calculation of electrical unitary energy savings for air-source heat pumps (ASHPs) with a capacity of less than 65,000 Btu/h (excluding air-to-water) using specific variables defined in an equation and a table.
$$\Delta kWh = \left(HC \left[\frac{1}{HSPF2_{base}} - \frac{1}{HSPF2_{ee}}\right] FLH_h + CC \left[\frac{1}{SEER2_{base}} AC - \frac{1}{SEER2_{ee}}\right] FLH_c\right)$$ Table 184: Electrical Unitary Energy Savings Values for Air-source H...
AI summary The document provides a formula to calculate electrical unitary energy savings for air-source heat pumps under 65,000 Btu/h. It includes parameters such as heating and cooling seasonal performance factors, full load hours, and cooling seasonal energy efficiency ratios, referencing the Minnesota TRM for FLH values in climate zone 4b.
Final Report 179 238 Efficiency Vermont, Technical Reference Manual (TRM) Program Year 2023 , p.91.
AI summary The text references Efficiency Vermont's Technical Reference Manual (TRM) for Program Year 2023, specifically page 91. This document is cited in the context of a regulatory proceeding, likely related to energy efficiency programs or technical standards.
Table 186: Unitary Peak Demand Savings Values for Air-source Heat Pumps Less Than 65,000 Btu/h Parameter Symbol BER-AR, SBES, AMH (prescriptive) Reference Heat Pump Rated Heating Capacity at -15°C (estimated temperature during NS peak dema...
AI summary The text presents a table detailing unitary peak demand savings values for air-source heat pumps with a rated heating capacity less than 65,000 Btu/h. It outlines parameters such as heat pump capacity, coefficient of performance, peak coincidence factor, and peak demand savings calculations. Assumptions and references for estimation methods are also included.
Table 187: Air-source Heat Pumps Greater Than 65,000 Btu/h, Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure system, rebated after installation Air-source heat pump greater than 65,000 Btu/h, g...
AI summary This table outlines energy savings parameters for air-source heat pumps greater than 65,000 Btu/h, including adjustment ratios, useful life, and calculation methods based on specification data for each rebated unit.
Table 188: Electrical Unitary Energy Savings Values for Air-source Heat Pumps Greater Than 65,000 Btu/h Parameter Symbol BER-AR, SBES Reference Heat Pump Rated Heating Capacity [kBtu/hr] 𝐻𝐶 Actual Use information in TS Heating Efficiency F...
AI summary Table 188 outlines the electrical unitary energy savings values for air-source heat pumps with a capacity greater than 65,000 Btu/h. It includes parameters such as heating and cooling efficiency factors, full load hours, and energy savings calculations, referencing the Minnesota TRM for FLH data from Duluth, Minnesota, in climate zone 4b.
$$\Delta kW = HC_{min} \left[1 - \frac{1}{HEF_{ee_min}}\right] \times PCF$$ Final Report 184
AI summary This section presents a mathematical formula used in energy efficiency calculations, involving parameters such as heating contribution, heating efficiency factor, and performance correction factor. It is part of a technical report and includes a reference to a page with an image.
Table 190: Unitary Peak Demand Savings Values for Air-source Heat Pumps Greater Than 65,000 Btu/h Parameter Symbol BER-AR, SBES Reference Heat Pump Rated Heating Capacity at -15°C (estimated temperature during NS peak demand) [kBtu/h] 𝐻𝐶𝑚𝑖...
AI summary The table presents unitary peak demand savings values for air-source heat pumps with capacities greater than 65,000 Btu/h, including parameters such as heating capacity, efficiency factors, and peak coincidence factor assumptions. The section also references dual enthalpy economizer controls.
Table 191: Dual Enthalpy Economizer Control Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure Dual enthalpy economizer controls which must be installed on new equipment that is also eligible for...
AI summary Table 191 outlines the Dual Enthalpy Economizer Control Measure Summary, including parameters such as energy savings adjustment ratios, peak demand savings, and effective useful life. The table provides details on how energy and peak demand savings are calculated based on specification data for each rebated unit.
$$\Delta kWh = SF \times Tonnes \times \frac{OTF}{EER} \times Quantity$$
AI summary The text presents a formula to calculate the change in kilowatt-hours (kWh) based on factors such as the seasonal factor (SF), tonnes, operating time factor (OTF), energy efficiency ratio (EER), and quantity. This formula is likely used in energy efficiency calculations or demand-side management contexts.
Table 192: Electrical Unitary Savings Values for Dual Enthalpy Economizer Controls Parameter Symbol BER-AR, SBES Reference Savings Factor SF SF (<5.4 tonnes) = 4,576 SF (>5.4 tonnes) = 3,318 Vermont TRM, 2015245 Annual kWh savings per tonn...
AI summary Table 192 provides electrical unitary savings values for dual enthalpy economizer controls, including parameters such as savings factor, tonnage of cooling equipment, operational testing factor, energy efficiency ratio, and unitary energy savings. The data is based on reference materials from Vermont TRM and simulation modeling for Burlington, VT.
Table 193: HVAC Hotel Occupancy Sensor Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure occupied, rebated after installation Year-round HVAC hotel occupancy sensor which controls electric heati...
AI summary Table 193 summarizes the energy and peak demand savings adjustment ratios and other parameters for HVAC hotel occupancy sensors. It includes details on baseline conditions, installation rates, energy savings, peak demand savings, and useful life. Table 194 provides specific electrical unitary energy savings values for these sensors.
Hot Water Insulation Measures For hot water insulation measures, namely pipe insulation and hot water tank wraps, the interactive effects factors are based on engineering calculations to account for the duration of the heating and cooling...
AI summary The text discusses engineering calculations for hot water insulation measures (pipe insulation and tank wraps), including assumptions about heating/cooling season durations, system efficiency, and heat distribution. It notes that SBES assumes similar water heating conditions to single-family homes and adjusts interactive effects factors for heat pump systems using COP values from Federal Energy Efficiency Regulations.
Peak Demand As for the impact on peak demand savings, it is assumed that all hot water tanks in a conditioned or semiconditioned space create interactive effects. Therefore, similar to lighting products, the interactive effects factor for...
AI summary The text discusses the impact of hot water tanks on peak demand savings in electrically heated buildings, assuming an interactive effects factor of -90%. It references regulatory documents and evaluation reports related to energy efficiency and demand-side management (DSM) measures.
Table 196: Interactive Effects Factors for Pipe Insulation and Hot Water Tank Wraps Space Heating Energy Interactive Effects During Heating Period Energy Interactive Effects During Cooling Period Total Energy Interactive Effects Peak Deman...
AI summary Table 196 presents interactive effects factors for pipe insulation and hot water tank wraps on energy use and peak demand during heating and cooling periods. Heat pump heating shows a -15.8% energy effect during heating, while electrical heating shows -28.5%. No effects are observed with no electrical heating.
[Table](#page-70-1) 197 summarizes the interactive effects factors established for each water heating measure.
AI summary The text references a table that summarizes the interactive effects factors established for each water heating measure, providing insights into how these factors influence energy efficiency and performance.
Table 197: Interactive Effects Factors for Water Heating Measures Measure Type of Space Heating Interactive Effects Factors for Energy Savings Interactive Effects Factors for Peak Demand Savings Reference Low-flow Showerheads - 0% 0% Assum...
AI summary Table 197 outlines interactive effects factors for water heating measures, including energy and peak demand savings. Measures like pipe insulation and hot water tank wraps show significant savings under specific heating conditions, while others like low-flow showerheads show no savings.
Table 198: Peak Demand-to-energy Ratio for Water Heating Measures Parameter Symbol Value Reference Portion of Energy Savings Occurring During Winter Peak Hours %kWhWP 40.5% Illinois TRM249 Number of Days During Winter Peak Season DaysWP 21...
AI summary Table 198 provides the peak demand-to-energy ratio for water heating measures, including parameters such as the portion of energy savings during winter peak hours and the number of winter peak hours per year. The peak demand-to-energy ratio is calculated as 0.192. Table 199 summarizes the peak demand-to-energy ratio for various water heating measures, with thermostatic shower valves having a ratio of 0.192.
5.4.4 Water Heating Measures
AI summary The section outlines water heating measures under energy efficiency programs, including rebates, grants, and technical standards. Key entities involve organizations like NS Power and Efficiency Nova Scotia, with topics centered on residential and commercial energy efficiency initiatives.
(1) Low-flow Showerheads
AI summary The document discusses the evaluation of low-flow showerheads as part of energy efficiency initiatives under Efficiency Nova Scotia (ENS), aiming to reduce domestic hot water (DHW) consumption and associated energy use. These measures are considered within the broader context of demand-side management (DSM) programs to promote water and energy conservation.
Table 200: Low-flow Showerhead Measure Summary Parameter SBES Reference Measure Description and Identification Measure Low-flow sh with direct in nowerheads of nstallation 1.5 GPM, - Baseline Standard flo ow showerhead d - Measure Subcateg...
AI summary Table 200 provides a summary of the Low-flow Showerhead Measure, including parameters such as installation rate, effective useful life, unitary energy savings, and peak demand savings. It outlines the energy efficiency improvements associated with low-flow showerheads compared to standard showerheads.
The equations below are used to determine the annual unitary savings values for low-flow showerheads. The reduction in hot water consumption is established by the difference between the base and efficient hot water consumption levels, as p...
AI summary The text provides equations for calculating annual energy savings from low-flow showerheads based on differences in hot water consumption between base and efficient models. Parameters such as flow rates, time of use, and efficiency factors are used in the calculations.
Table 201: Electrical Unitary Energy Savings Values for Low-flow Showerheads Parameter Symbol Value Reference Proportion of Water Heating Supplied by Electric Resistance Heating %ElectricDHW 100% Electrical energy savings will only be clai...
AI summary Table 201 presents electrical unitary energy savings values for low-flow showerheads, including parameters like baseline and low-flow rates, annual shower time, and energy efficiency factors. The table includes calculations and references for values such as electric water heater efficiency and unit conversions.
Table 202: Average Showerhead Usage Building Type Annual Minutes per Showerhead (SHtime) Weight Reference Hospitality 3,509 86% Annual minutes per Health 2,528 0% showerhead: Iowa Energy Efficiency TRM – 2021253 Education 2,057 0% Commerci...
AI summary Table 202 provides data on average showerhead usage across different building types, including annual minutes per showerhead and weights assigned to each category. The data is sourced from various references, such as the Iowa Energy Efficiency TRM and SBES 2021 tracking sheets. The weighted average annual minutes per showerhead is calculated as 3,419.
Table 203: Faucet Aerator Measure Summary Parameter SBES Reference Measure Description and Identification Measure Faucet aerators, with direct installation - Baseline No faucet aerator on standard flow-rate faucets General Parameters Insta...
AI summary Table 203 provides a summary of the Faucet Aerator Measure under the SBES program, detailing parameters such as installation rate, energy savings, and peak demand savings. The table references subsections and a technical reference manual for further details.
The equations below are used to calculate the annual unitary savings value for faucet aerators. $$DHW \ Savings \ \left[\frac{L}{year}\right] = DHW_{base} \ \left[\frac{gal}{year}\right] \times \frac{(q_{base} - q_{low})}{q_{base}} \times...
AI summary The text provides equations for calculating annual unitary savings from faucet aerators, using parameters like DHW base, flow rates, and efficiency factors. Table 204 lists the parameters and resulting savings values.
Table 204: Electrical Unitary Energy Savings Values for Faucet Aerators Parameter Symbol Value Reference Baseline Flow Rate [gpm] q base 1.39 DeOreo et al. in Residential End Uses of Water Study Low-flow Rate [gpm] Qlow 0.94 Update, as cit...
AI summary Table 204 provides electrical unitary energy savings values for faucet aerators, including parameters such as baseline flow rate, hot water consumption, and energy efficiency. The table references various studies and technical manuals, such as the Residential End Uses of Water Study and the Pennsylvania Public Utility Commission TRM.
Table 206: Thermostatic Shower Valve Measure Summary Parameter SBES Reference Measure Description and Identification Measure temperature has been reached, with direct installation Thermostatic shower valves cutting off water after the targ...
AI summary Table 206 provides a summary of the Thermostatic Shower Valve Measure, including parameters such as installation rate, effective useful life, unitary energy savings, and peak demand savings. The table outlines different subcategories based on showerhead flow rates and associated energy and demand savings.
The equations below are used to determine the annual unitary savings values for thermostatic shower valves. Energy savings are established by calculating the reduction in hot water usage, as presented in the second equation below. $$Energy...
AI summary The document provides equations for calculating annual energy savings from thermostatic shower valves by reducing hot water usage. The equations involve parameters such as hot water reduction, energy per gallon, and efficiency factors, with results detailed in Table 207.
Table 207: Electrical Unitary Energy Savings Values for Thermostatic Shower Valves Parameter Symbol SBES Reference Flow Rate [gpm] q Variable (1.5 gpm for low-flow showerhead, otherwise: 2.0 gpm, 2.25 gpm, or 2.5 gpm) SBES tracking sheet A...
AI summary Table 207 provides energy savings values for thermostatic shower valves based on various parameters such as flow rate, shower time, and water heater efficiency. The data includes calculated unitary energy savings and references to studies and conventions used for the calculations.
Table 208: Pipe Insulation Measure Summary Parameter SBES Reference Measure Description and Identification Measure Added pipe insulation to hot water copper pipes, with direct installation - Baseline No pipe insulation General Parameters I...
AI summary Table 208 outlines the parameters for the pipe insulation measure, including installation rate, effective useful life, energy savings, and peak demand savings. It provides detailed values for unitary energy savings and peak demand-to-energy ratio.
As presented in [Table](#page-79-1) 209, the annual unitary savings value for pipe insulation was identified through Ontario Power Authority (OPA) 2011[262](#page-79-2) values and was established at 12.7 kWh per linear foot. While this val...
AI summary The annual unitary savings value for pipe insulation was determined using OPA 2011 values of 12.7 kWh per linear foot, assuming similar usage patterns for water heating systems in small businesses as in residential settings.
Table 209: Unitary Energy Savings Value for Pipe Insulation Parameter SBES Unitary Energy Savings (per ft) [kWh/year] 12.7 Installation Rates
AI summary Table 209 presents the unitary energy savings value for pipe insulation at 12.7 kWh/year per foot. The table also includes a section on installation rates, though specific details are not provided in the text.
Table 210: Hot Water Tank Wrap Measure Summary Parameter SBES Reference Measure Description and Identification Measure Hot water tank wrap, with direct installation - Baseline No tank wrap General Parameters Installation Rate 100% See deta...
AI summary Table 210 provides a summary of the hot water tank wrap measure, including parameters such as installation rate, effective useful life, and energy savings. The table outlines the calculation methods for energy and peak demand savings associated with this measure.
$$R_{layer} = \frac{\ln\binom{r_e}{r_i}}{2\pi k}$$ $$R_{cyl} = R_{layer1} + R_{layer2}$$ $$Q_{cyl} = \frac{T_i - T_e}{R_{cyl}} L$$ $$Q_{top} = \frac{A_{top} \times (T_i - T_e)}{R_{top}}$$ $$Q_{total} = Q_{cyl} + Q_{top}$$ $$Energy Savings_...
AI summary The text provides equations for calculating thermal resistance and energy savings from hot water tank wraps, assuming residential usage patterns. It references a table with values used in these calculations.
Table 211: Electrical Unitary Energy Savings Values for Hot Water Tank Wraps Parameter Symbol Value Reference Layer 1: Interior Insulation of Tank External Radius of the Layer [m] 0.300 Giant263 Internal Radius of the Layer [m] ri 0.249 Ib...
AI summary Table 211 provides detailed thermal resistance and energy savings values for hot water tank wraps, including insulation parameters and calculated energy savings. It includes data on thermal conductivity, radii, and heat transfer calculations, as well as assumptions and references for each value.
Table 212: DHW Heat Pump Water Heater Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Heat pump water heater with an Energy factor greater than 2.3, rebated after installation - Baseline Exis...
AI summary This table outlines the parameters for a heat pump water heater measure, including installation rates, energy savings, and peak demand savings. It provides details on the baseline system, effective useful life, and calculation methods for energy and demand savings. References are made to external documents and sources.
Table 215: Unitary Peak Demand Savings Values for DHW Heat Pump Water Heaters Parameter Symbol BER-AR, SBES Reference Peak Demand-to-Energy Ratio PDTER If water heating not used during this peak, assume peak demand-to-energy ratio to be 0...
AI summary This table outlines the unitary peak demand savings values for DHW heat pump water heaters, including the peak demand-to-energy ratio and the calculation method for unitary peak demand savings. It also mentions installation rates as a relevant parameter.
5.5.2 Peak Demand Savings Factors For compressed air measures, the peak demand savings factor is assumed to be 77% where it is unknown for the specific project.
AI summary The document specifies that for compressed air measures, a default peak demand savings factor of 77% is assumed when project-specific data is unavailable. This assumption is used to estimate energy savings in demand-side management initiatives.
(1) Compressed Air Leak Repairs
AI summary The document section titled '(1) Compressed Air Leak Repairs' appears to focus on energy efficiency initiatives related to identifying and repairing leaks in compressed air systems. These repairs are likely part of broader demand-side management (DSM) programs aimed at reducing energy waste and improving system efficiency in industrial or commercial settings.
Summary [Table](#page-86-1) 216 presents a summary of the values used to calculate compressed air leak repair savings. The detailed methodology follows.
AI summary Table 216 summarizes the values used to calculate compressed air leak repair savings, with a detailed methodology provided afterward.
Table 216: Compressed Air Leak Repair Measure Summary Parameter Custom Measure Description and Identification Measure Repair leaks in compressed air systems - Baseline - General Parameters Installation Rate 100% See details below under Ins...
AI summary Table 216 outlines the parameters for the compressed air leak repair measure, including installation rates, effective useful life, and energy savings calculations based on system performance data. It references subsections and tables for detailed information on energy and peak demand savings.
Table 217: Electrical Unitary Energy Savings Values for Compressed Air Leak Repairs Parameter Symbol Value Reference Size of Leak [cfm] - Actual Project documentation Plant Efficiency [kW/100 cfm] - Actual (If unknown, use 19.7 kWh/100 cfm...
AI summary Table 217 outlines the parameters and calculations involved in determining electrical unitary energy savings from compressed air leak repairs, including size of leak, plant efficiency, hours of use, and calculated unitary energy savings.
Table 218: Electrical Unitary Peak Demand Values for Compressed Air Leak Repairs Parameter Symbol Value Reference Peak Coincidence Factor PCF Actual Project Documentation Unitary Energy Savings [kWh/year] 𝑈𝑛𝑖𝑡𝑎𝑟𝑦 𝑆𝑎𝑣𝑖𝑛𝑔𝑠 [𝑘𝑊] Calculated ba...
AI summary Table 218 provides electrical unitary peak demand values for compressed air leak repairs, including parameters like the peak coincidence factor and unitary energy savings. The table references project documentation and calculation methods for determining these values.
Table 219: Cycling Air Dryer Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Cycling refrigerated dryers up to 300 cubic feet per minute (CFM) capacity which automatically turn on and off in...
AI summary This table summarizes the Cycling Air Dryer Measure, including its description, baseline, installation rate, effective useful life, and electrical savings parameters. It outlines details on energy and peak demand savings calculations based on specification data for each rebated unit.
Table 222: Air-entraining Air Nozzle Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Air-entraining air nozzles under 14 CFM at 100 psi - Baseline Hand-held or fixed air nozzles - General Par...
AI summary Table 222 provides a summary of air-entraining air nozzle measures, including parameters such as installation rate, effective useful life, and energy savings calculations. The table outlines baseline measures and specifications for energy savings based on unitary data.
The electrical unitary energy savings for air-entraining air nozzles are calculated using the variables defined and listed in the equation[276](#page-90-1) and [Table](#page-91-0) 223 below. $$\Delta kWh = (CFM_b - CFM_e) \times COMP \time...
AI summary The document discusses the calculation of electrical unitary energy savings for air-entraining air nozzles using a specific equation and variables defined in a referenced table. The equation involves factors such as CFM, COMP, HRS, %USE, and QTY.
Table 223: Electrical Unitary Energy Savings Values for Air-entraining Air Nozzles Parameter Symbol BER-AR, SBES Reference Compressor kW/CFM COMP Modulating w/ BD = 0.32 Load/No Load w/ 1 gal/CFM = 0.32 Load/No Load w/ 3 gal/CFM = 0.30 Loa...
AI summary Table 223 provides energy savings values for air-entraining air nozzles, including parameters like compressor kW/CFM, baseline and efficient nozzle CFM, and hours of use. Calculations for unitary energy savings are based on data from the table and referenced materials.
Table 225: No-loss Drain Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure A no-loss drain opens the valve only when signaled by a condensate-level controller, rebated after installation - Base...
AI summary Table 225 provides a summary of the no-loss drain measure, detailing its description, baseline, installation rate, effective useful life, and energy savings parameters. The measure uses a condensate-level controller to open the valve only when needed, offering energy savings compared to timed drains.
5.6 Variable Frequency Drives
AI summary The section titled '5.6 Variable Frequency Drives' introduces a topic related to variable frequency drives (VFDs) in the context of a Nova Scotia regulatory proceeding, though no detailed content or analysis is provided in the given text.
5.6.4 Variable Frequency Drive (VFD) Measure
AI summary The section discusses the Variable Frequency Drive (VFD) Measure, likely evaluating its role in energy efficiency programs. No detailed content is provided in the chunk, focusing only on the heading.
Summary Table 229 presents a summary of the values used to calculate savings for VFDs installed in non-HVAC applications. The detailed methodology follows.
AI summary Table 229 summarizes the values used to calculate savings for VFDs installed in non-HVAC applications, with a detailed methodology provided thereafter.
Table 229: VFD Measure Summary Parameter BER-AR Reference Measure Description and Identification Measure Variable frequency drive for non-HVAC applications, installed after installation - Baseline No VFD General Parameters Installation Rat...
AI summary Table 229 outlines the VFD Measure Summary, detailing parameters such as installation rate, effective useful life, and energy savings calculations for variable frequency drives in non-HVAC applications. The table provides a baseline and specific savings factors, referencing additional subsections for detailed information.
The electrical unitary energy savings for VFD for non-HVAC applications are calculated using the variables defined and listed in the equations and tables below. $$Unitary \, Savings \left[\frac{kWh}{yr}\right] = \left(0.746 \left[\frac{kW}...
AI summary The document provides formulas for calculating electrical unitary energy savings for Variable Frequency Drives (VFD) in non-HVAC applications, using variables such as horsepower, load factor, efficiency, hours of use, and energy savings factor.
Table 230: Electrical Unitary Energy Savings Values for VFD Pumps and Fans Parameter Symbol Value Reference Rated Horsepower of the Motor [HP] HP Varies per project Project documentation Motor Load Factor [%] LF Varies per project (If unkn...
AI summary Table 230 provides electrical unitary energy savings values for VFD pumps and fans, outlining parameters such as motor horsepower, load factor, efficiency, and annual operating hours. The table references project documentation and the Minnesota TRM for data inputs and includes a calculation for unitary energy savings based on system specifications.
(2) ENERGY STAR Pool Pumps
AI summary The section discusses ENERGY STAR-certified pool pumps, likely within the context of energy efficiency programs and standards. No detailed content is provided in the given text.
Summary [Table](#page-99-0) 233 presents a summary of the values used to calculate pool pump savings. The detailed methodology follows.
AI summary Table 233 summarizes the values used to calculate pool pump savings, with a detailed methodology provided in the document.
Table 233: Pool Pump Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® multi-speed and variable frequency drive (VFD) commercial inground pool pumps, rebated after installation - B...
AI summary This table summarizes the ENERGY STAR® multi-speed and variable frequency drive (VFD) commercial inground pool pump measure, including its baseline, installation rate, useful life, and energy savings parameters. The unitary energy savings are calculated using the ENERGY STAR Pool Pump Calculator.
Table 234: Solar PV Measure Summary Parameter Custom Retrofit, BER-AR Reference Measure Description and Identification Measure Solar PV systems for commercial, industrial, and agricultural facilities rebated after installation - Baseline F...
AI summary Table 234 outlines a Solar PV Measure Summary, focusing on the rebate program for commercial, industrial, and agricultural facilities. The table includes parameters such as installation rate, effective useful life, and energy savings calculations. The document provides details on energy savings and peak demand savings, with references to subsections for further information.
The electrical unitary energy savings for solar PV systems installed in commercial, industrial, and agricultural applications are calculated using the variables defined and listed in the equations and tables below. For each solar PV projec...
AI summary The document outlines the methodology for calculating electrical unitary energy savings for solar PV systems in commercial, industrial, and agricultural applications, emphasizing the use of specific modeling tools and accounting for losses and inverter capacity limitations.
Table 236: Solar Domestic Hot Water Measure Summary Parameter BER-AR Reference Measure Description and Identification Measure CSA approved Solar domestic hot water heating rebated after installation - Baseline Existing conventional electri...
AI summary Table 236 provides a summary of a solar domestic hot water measure, including details such as the measure description, baseline, installation rate, effective useful life, and energy savings parameters. The table references RETScreen for calculating unitary energy savings and includes a footnote citing a report from the Northern Alberta Institute of Technology.
Table 237: Solar Air Heating Measure Summary Parameter BER-AR Reference Measure Description and Identification Measure CSA approved Solar air heating systems rebated after installation - Baseline Electric space heating (resistance or heat...
AI summary This table provides a summary of the Solar Air Heating Measure, including parameters such as installation rate, effective useful life, and energy savings calculations using RETScreen. The measure involves CSA-approved solar air heating systems rebated after installation, with a baseline of electric space heating.
5.9.1 Interactive Effects For refrigeration measures, interactive effects are considered when reduced heat rejection occurs within the refrigerated space, which in turns reduces the electricity consumption of the refrigeration compressor....
AI summary Interactive effects in refrigeration measures reduce compressor electricity consumption by lowering heat rejection. These effects are incorporated into energy savings calculations via a bonus factor for applicable measures, enhancing accuracy in efficiency assessments.
(1) Cooler Night Covers and Display Case Strip Curtains
AI summary The document section discusses 'Cooler Night Covers and Display Case Strip Curtains' as potential energy efficiency measures, likely within the context of demand-side management programs. The text does not elaborate on specific arguments, entities, or regulatory decisions related to these items.
Table 238: Cooler Night Cover and Display Strip Curtain Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Night cover or strip curtain for refrigerated cases, rebated after installation - Basel...
AI summary Table 238 provides a summary of the Cooler Night Cover and Display Strip Curtain Measure, including parameters such as installation rate, effective useful life, and energy savings calculations. It outlines the baseline, measure description, and key energy efficiency metrics for the rebate program.
The electrical unitary energy savings for cooler night covers and display strip curtains are calculated using the variables defined and listed in the equation and [Table](#page-106-0) 239 below.[287](#page-105-1) ℎ = ( )⁄( 1,000) 365 287 U...
AI summary The text describes the calculation of electrical unitary energy savings for cooler night covers and display strip curtains using a formula and a reference table. It also notes that the equation is sourced from Efficiency Vermont's Technical Reference User Manual.
Table 239: Electrical Unitary Savings Values for Cooler Night Covers and Display Strip Curtains BER-AR R, SBES Parameter Symbol Cooler Night Covers Display Strip Curtains Reference Loss of Cold Air or Heat Gain for Refrigerated Cases with...
AI summary The table presents electrical unitary savings values for Cooler Night Covers and Display Strip Curtains, including parameters like heat gain, efficiency factors, and usage hours. These values are used to calculate energy savings and are referenced from Vermont TRM and other sources.
= ( )⁄( 1000) Table 240: Unitary Peak Demand Savings Values for Cooler Night Covers and Display Strip Curtains Parameter Symbol BER-AR, SBES Reference Cooler Night Covers Display Strip Curtains Peak Coincidence Factor PCF 1 As per Subsecti...
AI summary The table presents unitary peak demand savings values for Cooler Night Covers and Display Strip Curtains, focusing on the Peak Coincidence Factor (PCF) and calculation methods for peak demand savings. The PCF is set at 1, as per Subsection 5.9.2.
Table 241: Zero-energy Door Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Zero-energy doors, without electric resistance heating in - the door or frame, for Reach-in Coolers. Reach-in displ...
AI summary This table outlines the parameters for the Zero-energy Door Measure, including installation rates, energy savings calculations, and specifications for highly insulated doors used in reach-in coolers. The measure involves rebating doors without electric resistance heating and with low-E glass coatings.
The electrical unitary energy savings for zero-energy doors are calculated using the variables defined and listed in the equation and [Table](#page-108-0) 242 below. $$\Delta kWh = kW_{door} \times BF \times HOU$$
AI summary The electrical unitary energy savings for zero-energy doors are calculated using the formula Δ kWh = kW_door × BF × HOU, with variables defined in an equation and referenced in Table 242.
Table 242: Electrical Unitary Energy Savings Values for Zero-energy Doors Parameter Symbol BER, SBES Reference Connected Load of a Typical Reach-in Cooler Door and Frame with Electric Heaters [kW] kWdoor 0.131 Vermont TRM, 2015291 Bonus Fa...
AI summary The text presents Table 242, which outlines parameters and calculations for electrical unitary energy savings values associated with zero-energy doors. It includes connected load, bonus factor, hours of use, and unitary energy savings calculations based on specification data for each rebated unit.
Table 243: Unitary Peak Demand Savings Values for Zero-energy Doors Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 1 As per Subsection 5.9.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on specification data f...
AI summary Table 243 provides unitary peak demand savings values for zero-energy doors, including the peak coincidence factor (PCF) and calculation methods for demand savings based on specification data for each rebated unit.
Summary [Table](#page-109-0) 244 presents a summary of the values used to calculate electrical door heater control savings. The detailed methodology follows.
AI summary Table 244 summarizes the values used to calculate electrical door heater control savings, with a detailed methodology provided in the proceeding document.
Table 244: Door Heater Control Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Humidity or conductivity-based heater controls that limit heater operation to periods of high relative humidity...
AI summary Table 244 outlines a door heater control measure that limits heater operation based on humidity or conductivity, aiming to reduce energy use. The measure is rebated after installation, with a 12-year useful life and energy savings calculated per unit.
The electrical unitary energy savings for door heater controls are calculated using the variables defined and listed in the equation and [Table](#page-110-0) 245 below. $$\Delta kWh = kW_{door} \times N_{door} \times ES \times BF \times HO...
AI summary The document provides a formula for calculating electrical unitary energy savings for door heater controls, using variables such as kW, number of doors, efficiency factor, and hours of use.
Table 245: Electrical Unitary Energy Savings Values for Door Heater Controls Parameter Symbol BER-AR, SBES Reference Connected Load of a Typical Reach-in Cooler Door and Frame with Electric Heaters [kW] kWdoor Coolers = 0.131 Freezer = 0.2...
AI summary Table 245 outlines electrical unitary energy savings values for door heater controls, including parameters like connected load, number of doors, energy savings percentages, bonus factors, hours of use, and unitary energy savings. These values are based on data from Vermont TRM and are used in calculations for peak demand savings.
$$\Delta kW = kW_{door} \times N_{door} \times ES \times BF \times PCF$$
AI summary The text presents a mathematical formula for calculating the change in kilowatts (ΔkW) based on various factors including door kilowatts (kW_door), number of doors (N_door), energy savings (ES), building factor (BF), and peak coincidence factor (PCF).
Table 247: Evaporator Fan Motor Control Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure The control system rebated after installation: • Controls a minimum of 300 Watts or four evaporator fan...
AI summary The table outlines a measure involving the control system for evaporator fan motors, which reduces air flow by at least 50% when the compressor is not running or when no refrigerant is flowing through the evaporator. It provides details on installation rates, effective useful life, and energy savings parameters.
The electrical unitary energy savings for evaporator fan motor controls are calculated using the variables defined and listed in the equation and [Table](#page-112-0) 248 below. $$\Delta kWh = \left( \left( kW_{evap} \ x \ n_{fans} \ x \ D...
AI summary The document provides a formula for calculating electrical unitary energy savings for evaporator fan motor controls, using variables such as kW for evaporator and circulator fans, demand control factors, a balancing factor, and hours of use.
Table 248: Electrical Unitary Energy Savings Values for Evaporator Fan Motor Controls Parameter Symbol BER-AR, SBES Reference Connected Load kW of Each Evaporator Fan [kW] kWevap 0.11 Based on weighted average of 60% shaded pole at 132 Wat...
AI summary Table 248 outlines the electrical unitary energy savings values for evaporator fan motor controls, including parameters like connected load kW, duty cycles, and bonus factors, with references to Vermont TRM and adjustments for the Nova Scotia market.
$$\Delta kW = \left( \left( kW_{evap} \ x \ n_{fans} \ x \ DC_{evap} \right) - \ kW_{circ} \right) x \left( 1 - DC_{comp} \right) x \ BF \ x \ PCF$$ Table 249: Unitary Peak Demand Savings Values for Cooler Night Covers and Display Strip Cu...
AI summary The document presents a formula for calculating peak demand savings (∆kW) for energy efficiency measures such as Cooler Night Covers and Display Strip Curtains. It includes a table with parameters like the Peak Coincidence Factor (PCF) and unitary peak demand savings, referencing Subsection 5.9.2 of a regulation.
Table 250: Intelligent Freezer Defrost Control Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Control system which contains temperature and pressure sensors to monitor system operation and d...
AI summary Table 250 outlines the Intelligent Freezer Defrost Control Measure, detailing its description, baseline, installation rate, useful life, and energy savings parameters. The measure involves a control system with sensors to manage defrost cycles and is eligible for rebates after installation.
The electrical unitary energy savings for intelligent freezer defrost control are calculated using the variables defined and listed in the equation and [Table](#page-114-0) 251 below. $$\Delta kWh = n_{fans} x kW_{DE} x SVG x BF x FLH$$
AI summary The document discusses the calculation of electrical unitary energy savings for intelligent freezer defrost control, using a specific formula and referencing a table for variable definitions.
Table 251: Electrical Unitary Energy Savings Values for Intelligent Freezer Defrost Controls Parameter Symbol BER-AR, SBES Reference Number of Evaporator Fans nfans Actual Use information in TS kW of Defrost Element per Evaporator Fan kWDE...
AI summary Table 251 outlines the parameters and values used to calculate electrical unitary energy savings for intelligent freezer defrost controls, including values such as the number of evaporator fans, kW of defrost element per fan, and average full load defrost hours. These values are referenced from the Vermont TRM and used in calculations for energy savings.
Table 252: Unitary Peak Demand Savings Values for Intelligent Freezer Defrost Controls Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 1 See Subsection 5.9.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on spec...
AI summary Table 252 presents unitary peak demand savings values for intelligent freezer defrost controls, focusing on the peak coincidence factor (PCF) and the calculation of unitary peak demand savings (∆𝑘𝑊) based on specification data for each rebated unit.
Table 253: Vertical Refrigeration Open-to-closed Cooler Conversion Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Doored vertical refrigeration units, rebated after installation - Baseline O...
AI summary Table 253 provides a summary of the Vertical Refrigeration Open-to-closed Cooler Conversion Measure, including parameters such as installation rate, effective useful life, and energy savings calculations. The table outlines details related to electrical savings, peak demand savings, and interactive effects factors.
Table 254: Electrical Unitary Energy Savings Values for Vertical Refrigeration Open-to-closed Cooler Conversion Parameter Symbol BER-AR, SBES Reference Open-to-closed Case Savings Factor [kWh/(day feet)] OCSF With anti-sweat heaters = 0.5...
AI summary Table 254 outlines electrical unitary energy savings values for converting vertical refrigeration open-to-closed coolers, including parameters like open-to-closed case savings factor, operational days, and length of refrigerated space. It references the International Refrigeration and Air Conditioning Conference and provides calculation methods for energy savings.
Table 255: Unitary Peak Demand Savings Values for Vertical Refrigeration Open-to-closed Cooler Conversion Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 1 See Subsection 5.9.2 Hours of Use [h/year] HOU Actual Use infor...
AI summary Table 255 presents unitary peak demand savings values for vertical refrigeration open-to-closed cooler conversion, including parameters such as the Peak Coincidence Factor (PCF), Hours of Use (HOU), and Unitary Peak Demand Savings (∆𝑘𝑊). It references Subsection 5.9.2 and the use of information in TS for HOU.
(7) Efficient Refrigeration Compressors (Scroll Refrigeration Compressor)
AI summary The document section titled '(7) Efficient Refrigeration Compressors (Scroll Refrigeration Compressor)' appears to focus on regulatory considerations related to energy-efficient refrigeration compressor technologies, though no detailed content or analysis is provided in the excerpt.
Table 256: Efficient Refrigeration Compressor Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification tion Measure Efficient scroll compressor, rebated after installation - Baseline Hermetic or semihermetic...
AI summary Table 256 presents a summary of the Efficient Refrigeration Compressor Measure, including parameters such as installation rate, effective useful life, and energy savings calculations. The table outlines the baseline compressor type, energy savings parameters, and factors related to peak demand and energy savings.
Table 257: Electrical Unitary Energy Savings Values for Efficient Refrigeration Compressors Parameter Symbol BER-AR, SBES Reference Compressor Capacity at Standard Rating Conditions [Btu/h] 𝐶𝐴𝑃𝑎𝑣𝑔,𝑒𝑒 Actual Use information in TS Energy Eff...
AI summary The document presents tables detailing energy efficiency ratios (EER) for baseline and efficient refrigeration compressors under different temperature conditions. The tables include parameters such as compressor capacity, full load hours, and unitary energy savings, with references to technical manuals and calculation methods.
∆ = ∆ℎ ⁄ Table 260: Unitary Peak Demand Savings Values for Refrigeration Economizers Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 1 See Subsection 5.9.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on specif...
AI summary The text presents a table detailing Unitary Peak Demand Savings Values for Refrigeration Economizers, including parameters such as the Peak Coincidence Factor and Unitary Peak Demand Savings. It references Subsection 5.9.2 and outlines calculation methods based on specification data.
Table 261: Refrigeration Economizer Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Coolers capable of drawing in outdoor air when it is sufficiently cool (temperatures less than 34°F or 1°C)...
AI summary Table 261 outlines the Refrigeration Economizer Measure Summary, including parameters such as measure description, baseline, installation rate, effective useful life, and energy savings calculations. The table provides details on unitary energy savings and peak demand savings based on specification data for each rebated unit.
Table 262: Electrical Unitary Energy Savings Values for Refrigeration Economizers Parameter Symbol BER-AR, SBES Reference Power of Compressor [HP] HP Actual Use information in TS Condensing Unit Savings, per hp [kWh] kWhcond Hermetic / Sem...
AI summary Table 262 presents electrical unitary energy savings values for refrigeration economizers, including parameters such as compressor power, condensing unit savings, hours of use, and connected load values. The table references data from Vermont TRM and includes assumptions adjusted for the Nova Scotia market.
The unitary peak demand savings for refrigeration economizer are calculated using the variables defined and listed in the equation and [Table](#page-121-2) 263 below, as well as variables from [Table](#page-120-0) 262 above.
AI summary The text explains how unitary peak demand savings for refrigeration economizers are calculated using specific variables defined in equations and tables referenced in the document.
Table 264: Brushless DC Motor Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Brushless DC motors (or electrically commutated motors – ECM) for cooler of freezer evaporator fan, rebated after...
AI summary This table provides a summary of the Brushless DC Motor Measure, including details on energy savings, installation rates, and useful life. It outlines the baseline motor type, savings parameters, and factors related to energy and peak demand savings.
$$\Delta kWh = \left(\frac{kW_{output}}{\eta_{base}} - \frac{kW_{output}}{\eta_{ee}}\right) \times \; HOU \; \times DC \times LF \times \left(1 + \frac{1}{COP}\right)$$
AI summary The document provides a mathematical formula for calculating energy savings, involving variables such as output power, efficiency, hours of use, demand charge, load factor, and coefficient of performance.
Table 265: Electrical Unitary Energy Savings Values for Brushless DC Motors Parameter Symbol Value for BER-AR and SBES Reference Motor Output [kW] kWoutput 0.015 for cases and 0.042 for walk-ins Iowa TRM, 2023 Baseline Motor Efficiency [-]...
AI summary Table 265 presents electrical unitary energy savings values for brushless DC motors, including parameters such as motor output, efficiency, hours of use, and energy savings calculations. The table references various studies and assumptions for parameter values.
The unitary peak demand savings for brushless DC motors are calculated using the variables defined and listed in the equation and [Table](#page-122-4) 266 below, as well as variables from [Table](#page-122-1) 265 above. $$\Delta kW = \left...
AI summary The text explains the calculation of unitary peak demand savings for brushless DC motors using a specific formula that includes variables such as output power, efficiency, and factors like DC, LF, COP, and PCF, as defined in referenced tables.
(10) Refrigerated Vending Machine Controllers
AI summary This section addresses refrigerated vending machine controllers, likely within the context of energy efficiency regulations or demand-side management initiatives in Nova Scotia.
Summary [Table](#page-123-0) 267 presents a summary of the values used to calculate refrigerated vending machine controller savings. The detailed methodology follows.
AI summary Table 267 summarizes the values used to calculate refrigerated vending machine controller savings, with a detailed methodology provided in the proceeding.
Table 267: Refrigerated Vending Machine Controller Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Controller uses occupancy sensor based controls to de-energize refrigerated vending machines...
AI summary Table 267 outlines a measure involving the use of occupancy sensors on refrigerated vending machines to reduce energy consumption. The table includes parameters such as installation rate, useful life, energy savings calculations, and factors like the peak coincidence factor and interactive effects.
The electrical unitary energy savings for refrigerated vending machine controllers are calculated using the variables defined and listed in the equation[306](#page-123-1) and [Table](#page-124-1) 268 below. $$\Delta kWh = kW_{rated} \ x \...
AI summary The document discusses the calculation of electrical unitary energy savings for refrigerated vending machine controllers using a specific equation and variables defined in a referenced table and technical manual.
$$\Delta kW = kW_{rated} \ x \ SAVE \ x \ QTY \ x \ PCF$$ Table 269: Unitary Peak Demand Savings Values for Refrigerated Vending Machine Controllers Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 1 As per Subsection 5....
AI summary This section provides a formula for calculating unitary peak demand savings for refrigerated vending machine controllers, specifically focusing on the Peak Coincidence Factor (PCF) and the calculation method based on specification data for each rebated unit.
Table 271: High Volume Low Speed Fan Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure CSA / cUL rated High Volume Low Speed (HVLS) fans for agricultural facilities, rebated after installation -...
AI summary Table 271 presents a summary of the High Volume Low Speed Fan Measure under the Business Energy Rebates (BER) and Standard Building Efficiency Standards (SBES). It outlines parameters such as energy savings adjustment ratios, peak demand savings ratios, and useful life, along with references to specific subsections and tables for detailed calculations.
$$\Delta kWh = (P_b \ x \ QTY_b - P_e \ x \ QTY_e) \ x \ HOU/1,000$$ Table 272: Electrical Unitary Energy Savings Values for High Volume Low Speed Fans Parameter Symbol BER-AR, SBES Reference Power of the Baseline Fans [W] Pb Actual or bas...
AI summary The document presents a formula for calculating unitary energy savings (∆kWh) for high volume low speed (HVLS) fans based on baseline and new fan power consumption, quantity, and hours of use. It also provides a table with parameters and values used in the calculation.
Table 273: Unitary Peak Demand Savings Values for High Volume Low Speed Fans Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 0.84 As per Subsection 5.10.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on specifi...
AI summary Table 273 presents unitary peak demand savings values for high volume low speed fans, including parameters such as the Peak Coincidence Factor (PCF) and Unitary Peak Demand Savings (∆𝑘𝑊), with references to calculation methods and specifications.
(2) Energy Efficient Ventilation and Circulation Fans
AI summary The section addresses energy-efficient ventilation and circulation fans, likely discussing their role in energy efficiency programs, regulatory considerations, and potential impacts on building performance and energy consumption.
Summary [Table](#page-127-0) 274 presents a summary of the values used to calculate energy efficient ventilation and circulation fan savings. The detailed methodology follows.
AI summary Table 274 summarizes the values used to calculate energy efficient ventilation and circulation fan savings, with a detailed methodology provided.
$$\Delta kWh = \left(\frac{AF_b}{ER_b} \times Qty_b - \frac{AF_e}{ER_e} \times Qty_e\right) \times HOU/1,000$$
AI summary The text presents a mathematical formula used to calculate the change in energy consumption (Δ kWh) based on factors such as appliance factors (AF), efficiency ratings (ER), quantities (Qty), and hours of use (HOU). This formula is likely used in energy efficiency calculations or program evaluations.
Table 275: Electrical Unitary Energy Savings Values for Energy Efficient Ventilation and Circulation Fans BER-AR, SBES Parameter Symbol Ventilation Fan Circulation Fan Reference Airflow Produced by Baseline Fan [CFM] AFb Actual or assume s...
AI summary Table 275 provides electrical unitary energy savings values for energy-efficient ventilation and circulation fans. It includes parameters such as airflow produced by baseline and efficient fans, efficacy ratios, hours of use, and methods for calculating unitary energy savings. The data is sourced from the 2021 BESS Fan Performance Data and other references.
313 Independent Electrical System Operator, IESO Prescriptive Measures and Assumptions List , February 2024. The unitary peak demand savings for energy efficient ventilation & circulation fans are calculated using the variables defined and...
AI summary The document discusses the calculation of unitary peak demand savings for energy efficient ventilation & circulation fans using specific variables from two tables and a provided equation, which includes factors such as AF, ER, Qty, and PCF.
Table 276: Unitary Peak Demand Savings Values for Energy Efficient Ventilation and Circulation Fans Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 0.84 As per Subsection 5.10.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calcu...
AI summary The text presents Table 276, which outlines unitary peak demand savings values for energy efficient ventilation and circulation fans, including parameters like the Peak Coincidence Factor and Unitary Peak Demand Savings. It also references installation rates, though details are not provided in the excerpt.
Table 277: Dual and Natural Ventilation Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure Both natural and dual ventilation systems that meet the following criteria are eligible, rebated after i...
AI summary Table 277 outlines eligibility criteria and parameters for rebating dual and natural ventilation systems in agricultural facilities. It specifies measure descriptions, baseline conditions, installation rates, energy savings adjustment ratios, and other technical parameters relevant to the calculation of energy savings.
Table 278: Electrical Unitary Energy Savings Values for Dual and Natural Ventilation Parameter Symbol BER-AR, SBES Reference Livestock Capacity (number of animals the barn is designed for) LC Actual Use information in TS Airflow Requiremen...
AI summary Table 278 outlines electrical unitary energy savings values for dual and natural ventilation systems, including parameters like livestock capacity, airflow requirements, efficiency ratios, and savings factors for different types of livestock and ventilation systems.
(4) Zero-energy and Low-energy Livestock Waterers
AI summary The section discusses zero-energy and low-energy livestock waterers, focusing on energy efficiency in agricultural water management systems. It likely explores technologies, programs, or policies aimed at reducing energy consumption in livestock water heating and distribution.
Table 280: Zero-energy and Low-energy Livestock Waterer Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure rebated after installation Must contain a minimum of 2 inches insulation and an adjustab...
AI summary Table 280 provides a summary of the Zero-energy and Low-energy Livestock Waterer Measure, including parameters such as installation rates, energy savings adjustment ratios, and electrical savings parameters. The table outlines specifications for the measure, including insulation requirements and energy efficiency metrics.
The electrical unitary energy savings for zero-energy & low-energy livestock waterers are calculated using the variables defined and listed in the equation and [Table](#page-133-0) 281 below. $$\Delta kWh = (P_b - P_e) Qty HOU/1,000$$
AI summary The document discusses the calculation of electrical unitary energy savings for zero-energy and low-energy livestock waterers using a specific formula and a referenced table. The formula involves variables such as P_b, P_e, Qty, and HOU.
Table 281: Electrical Unitary Energy Savings Values for Zero-energy and Low-energy Livestock Waterers Parameter Symbol BER-AR, SBES Reference Wattage of the Heater in the Old Waterer Pb Actual or 800 Use information in TS Default: IESO Pre...
AI summary Table 281 outlines parameters for calculating electrical unitary energy savings for zero-energy and low-energy livestock waterers, including wattage of heaters, quantity, and hours of use. The data is used in conjunction with Table 282 to calculate peak demand savings.
Table 282: Unitary Peak Demand Savings Values for Zero-energy and Low-energy Livestock Waterers Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 0.84 As per Subsection 5.10.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculati...
AI summary This table outlines the unitary peak demand savings values for zero-energy and low-energy livestock waterers, including the peak coincidence factor and the method of calculation for unitary peak demand savings.
The electrical unitary energy savings for agriculture heat pads are calculated using the variables defined and listed in the equation and [Table](#page-135-0) 284 below. $$\Delta kWh = (P_b x Qty_b - P_e x Qty_e) x HOU/1,000$$
AI summary The text describes how electrical unitary energy savings for agriculture heat pads are calculated using a specific equation and a referenced table. The equation involves variables such as power before and after, quantities, and hours of use.
Table 284: Electrical Unitary Energy Savings Values for Agriculture Heat Pads Parameter Symbol BER-AR, SBES Reference Wattage of Inefficient Heat Lamps Pb Actual or 175 Use information in TS Default: IESO Prescriptive Measures and Assumpti...
AI summary Table 284 outlines the parameters used to calculate electrical unitary energy savings values for agriculture heat pads, including wattage, quantity, and hours of use. It references default assumptions from the IESO Prescriptive Measures and Assumptions document.
Table 285: Unitary Peak Demand Savings Values for Agriculture Heat Pads Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 0.84 As per Subsection 5.10.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on specificatio...
AI summary Table 285 presents unitary peak demand savings values for agriculture heat pads, including parameters such as the Peak Coincidence Factor and Unitary Peak Demand Savings. The table provides calculation methods and references for these values.
The electrical unitary energy savings for tractor engine block heater timers are calculated using the variables defined and listed in the equation and [Table](#page-137-0) 287 below. $$\Delta kWh = P_{heater} x (HOU_b - HOU_e) x DAYS / 1,0...
AI summary The document outlines the calculation method for electrical unitary energy savings related to tractor engine block heater timers, using a specific formula involving power, hours of use, and days.
The electrical unitary energy savings for dairy scroll compressors are calculated using the variables defined and listed in the equation[321](#page-138-2) and [Table](#page-139-0) 290 below. $$\Delta kWh = \frac{\left(\frac{1}{EER_b} - \fr...
AI summary The text discusses the calculation of electrical unitary energy savings for dairy scroll compressors using a specific equation and table. The equation involves variables such as EER (Energy Efficiency Ratio), hours of use, days, number of cows, milk production, and temperature change.
Table 290: Electrical Unitary Energy Savings Values for Dairy Scroll Compressors Parameter Symbol BER-AR, SBES Reference Efficiency of Existing Compressor [Btu/h/W] 𝐸𝐸𝑅𝑏 Actual or 8.4 Use information in TS Default: Illinois TRM V12322 Effi...
AI summary This table outlines the parameters used to calculate electrical unitary energy savings for dairy scroll compressors, including efficiency values, usage hours, milk weight, and temperature changes. Calculations are based on specific data from various technical references.
Table 292: Heat Reclaimer Unit Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure Heat reclaimer unit that electrically heats water, rebated after installation - Baseline No heat reclaimer - Gene...
AI summary Table 292 outlines the parameters for a heat reclaimer unit measure, including energy savings adjustment ratios, peak demand savings adjustment ratios, and other technical specifications. It provides details on installation rates, useful life, and calculation methods for energy and peak demand savings.
The electrical unitary energy savings for heat reclaimer units are calculated using the variables defined and listed in the equation and [Table](#page-141-0) 293 below. $$\Delta kWh = COWS \, x \, \frac{MILK}{COW} \, x \, (U_{warm} \, - \,...
AI summary The document explains how electrical unitary energy savings for heat reclaimer units are calculated using a specific equation that incorporates variables such as milk per cow, temperature differences, and efficiency factors.
Table 293: Electrical Unitary Energy Savings Values for Heat Reclaimer Units Parameter Symbol BER-AR, SBES Reference Average Number of Cows Milked per Day COWS Actual Use information in TS Average Amount of Milk Yielded per Cow Annually [L...
AI summary Table 293 provides electrical unitary energy savings values for heat reclaimer units, including parameters such as average number of cows milked per day, internal energy of warm and cooled milk, efficiency of heat exchangers and water heaters, and calculation methods for energy savings.
Table 295: Milk Pre-cooler Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure Milk pre-cooler, rebated after installation - Baseline No existing milk pre-cooler - General Parameters Installation...
AI summary Table 295 summarizes the Milk Pre-cooler Measure, including parameters such as energy savings adjustment ratios, peak demand savings ratios, and useful life. The table outlines technical details and references specific subsections in the document for further information.
Table 296: Electrical Unitary Energy Savings Values for Milk Pre-Coolers Parameter Symbol BER-AR, SBES Reference Average Number of Cows Milked per Day COWS Actual Use information in TS Average Amount of Milk Yielded per Cow Annually [L/cow...
AI summary Table 296 presents parameters and values related to electrical unitary energy savings for milk pre-coolers. It includes details such as milk temperature, specific heat capacity, and energy conversion factors, along with references to various sources. The table is used to calculate energy savings based on specification data for each rebated unit.
ke, and Milk Yield of Lactating Dairy Cows . Retrieved from: [https://www.sciencedirect.com/science/article/pii/S0022030203736029.](https://www.sciencedirect.com/science/article/pii/S0022030203736029) 331 Farm Energy Nova Scotia states a 6...
AI summary The text discusses energy efficiency measures on dairy farms, specifically the use of pre-coolers and variable frequency drive (VFD) milk transfer pumps, which significantly reduce milk temperatures. Farm Energy Nova Scotia and the Government of Alberta report temperature drops of 65% and 8 to 11 °C, respectively.
Table 297: Unitary Peak Demand Savings Values for Milk Pre-coolers Parameter Symbol BER-AR, SBES Reference Hours of Use [h/year] HOU Actual or 2,920 Use information in TS Default: Minnesota 2025 TRM334 Peak Coincidence Factor PCF 0.84 As p...
AI summary Table 297 outlines the unitary peak demand savings values for milk pre-coolers, including parameters such as hours of use, peak coincidence factor, and unitary peak demand savings. The table provides default values and references for calculations.
(10) VFDs for Milk Vacuum Pumps
AI summary The document analyzes the use of Variable Frequency Drives (VFDs) in milk vacuum pumps, focusing on their energy efficiency, cost-benefit analysis, and potential regulatory implications for Nova Scotia's utility sector. It evaluates technical performance and compliance with energy standards.
Table 298: VFD for Milk Vacuum Pump Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure VFD for milk vacuum pump which must milk at least 50 cows, rebated after installation - Baseline No existing...
AI summary Table 298 details the VFD for Milk Vacuum Pump Measure Summary, including parameters like installation rate, energy savings adjustment ratios, and effective useful life. It references Subsections 5.10.1, 5.10.2, and 5.10.3 for specific calculations and definitions.
Table 299: Electrical Unitary Energy Savings Values for Milk Vacuum Pumps Parameter Symbol BER-AR, SBES Reference Horsepower of Connected Pump Motor HP Actual Use information in TS Conversion from hp to kW - 0.746 Convention Efficiency of...
AI summary Table 299 provides electrical unitary energy savings values for milk vacuum pumps, including parameters such as horsepower, efficiency, load factor, and hours of use. The table outlines how energy savings are calculated based on specific data for each rebated unit.
Table 300: Unitary Peak Demand Savings Values for Milk Vacuum Pumps Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF 0.84 As per Subsection 5.10.2 Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on specification da...
AI summary Table 300 provides unitary peak demand savings values for Milk Vacuum Pumps, including parameters such as the Peak Coincidence Factor (PCF) and Unitary Peak Demand Savings (∆𝑘𝑊). The table references Subsection 5.10.2 for the Peak Coincidence Factor and outlines the calculation method for demand savings.
Table 301: VFD Milk Transfer Pump Measure Summary Parameter BER-AR SBES Reference Measure Description and Identification Measure VFD for milk transfer pump with pre cooler installed which must milk at least 75 cows, rebated after installat...
AI summary This table outlines the parameters for a VFD Milk Transfer Pump Measure, including installation rates, energy savings adjustment ratios, and electrical savings parameters, referencing specific subsections for detailed calculations.
The electrical unitary energy savings for VFD milk transfer pump are calculated using the variables defined and listed in the equation and [Table](#page-146-1) 302 below. ∆ℎ =
AI summary The text discusses the calculation of electrical unitary energy savings for a VFD milk transfer pump, referencing an equation and a table for variable definitions.
Table 302: Electrical Unitary Energy Savings Values for VFD Milk Transfer Pumps Parameter Symbol BER-AR, SBES Reference Energy Factor - Estimate of Energy Offset by Using VFD Milk Transfer Pump per Cow Milked EF 33.945 Massachusetts Farm E...
AI summary Table 302 presents electrical unitary energy savings values for VFD milk transfer pumps, including an energy factor and the average number of cows milked per day. The unitary peak demand savings are calculated using data from this table and Table 303.
$$\Delta kW = (EF \ x \ COWS \ x \ PCF)/HOU$$
AI summary The text provides a formula for calculating the change in kilowatts (ΔkW) using factors such as efficiency factor (EF), cost of water supply (COWS), power conversion factor (PCF), and hours of use (HOU). This formula is likely used in energy management or utility calculations.
5.11.2 Peak Demand Savings Factor For kitchen measures, peak demand savings are determined by multiplying the wattage by a PCF value of 68%, which was established as part of the 2015 evaluation of BER.[336](#page-147-3) Freezers and refrig...
AI summary The Peak Demand Savings Factor (PCF) for kitchen measures is 68%, established during the 2015 evaluation of Business Energy Rebates (BER). Freezers and refrigerators have a PCF of 100%, reflecting their higher impact on peak demand.
Table 304: Dishwasher Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Low or high temperature ENERGY STAR® rated dishwasher, rebated after installation - Baseline Standard dishwasher - Genera...
AI summary Table 304 provides a summary of the Dishwasher Measure under the Business Energy Rebates (BER) program. It outlines key parameters such as installation rate, effective useful life, and energy savings calculations for ENERGY STAR® rated dishwashers, with references to specific subsections for detailed information.
The electrical unitary energy savings for dishwashers are calculated using the ENERGY STAR Commercial Kitchen Calculator using the parameters in [Table](#page-149-0) 305 below.
AI summary The document discusses the calculation of electrical unitary energy savings for dishwashers using the ENERGY STAR Commercial Kitchen Calculator and specific parameters outlined in Table 305.
Table 305: Electrical Unitary Energy Savings Values for Dishwashers Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hours/day] HOU...
AI summary Table 305 outlines the parameters and values used to calculate electrical unitary energy savings for dishwashers, including inputs such as annual days of operation, average daily operation, racks washed per day, and energy and water use rates. Energy savings are calculated using the ENERGY STAR Commercial Kitchen Calculator.
Summary [Table](#page-150-0) 307 presents a summary of the values used to calculate electrical freezer/refrigerator savings. The detailed methodology follows.
AI summary Table 307 summarizes the values used to calculate electrical freezer/refrigerator savings, with a detailed methodology provided in the document.
The electrical unitary energy savings for freezers and refrigerators are calculated using the ENERGY STAR Commercial Kitchen Calculator using the parameters in [Table](#page-150-1) 308 below.
AI summary The document discusses the calculation of electrical unitary energy savings for freezers and refrigerators, using the ENERGY STAR Commercial Kitchen Calculator with specific parameters outlined in a referenced table.
Table 308: Electrical Unitary Energy Savings Values for Freezers/Refrigerators Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hou...
AI summary Table 308 provides parameters for calculating electrical unitary energy savings values for freezers and refrigerators, including annual days of operation, average daily operation, interior volume, energy use, and energy savings. The energy savings are calculated using the ENERGY STAR Commercial Kitchen Calculator.
Table 310: Fryer Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated fryer, rebated after installation - Baseline Standard electric fryer - General Parameters Installation Rate...
AI summary Table 310 outlines the Fryer Measure Summary, focusing on the ENERGY STAR® rated fryer under the Business Energy Rebates (BER) program. It provides details on the baseline, installation rate, useful life, and energy savings parameters, including unitary energy savings and peak demand savings calculations.
Table 311: Electrical Unitary Energy Savings Values for Fryers Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hours/day] HOU Actu...
AI summary Table 311 outlines the parameters and calculations for determining electrical unitary energy savings values for fryers, including factors like annual days of operation, fryer size, and energy efficiency. The table references the ENERGY STAR Commercial Kitchen Calculator for calculating energy savings.
Table 313: Griddle Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated griddle, rebated after installation - Baseline Standard electric griddle - General Parameters Installatio...
AI summary The table outlines the parameters for the ENERGY STAR® rated griddle measure under the Business Energy Rebates (BER) program. It includes details such as the baseline standard electric griddle, installation rate, useful life, and energy savings calculations based on specification data for each rebated unit.
The electrical unitary energy savings for griddles are calculated using the ENERGY STAR Commercial Kitchen Calculator using the parameters in [Table](#page-154-0) 314 below.
AI summary The document discusses the calculation of electrical unitary energy savings for griddles using the ENERGY STAR Commercial Kitchen Calculator with specific parameters outlined in a referenced table.
Table 314: Electrical Unitary Energy Savings Values for Griddles Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hours/day] HOU Ac...
AI summary Table 314 outlines parameters and their corresponding values for calculating electrical unitary energy savings for griddles, including operational days, hours, dimensions, and energy efficiency metrics. Energy savings are calculated using the ENERGY STAR Commercial Kitchen Calculator.
Table 316: Hot Food Holding Cabinet Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated hot food holding cabinet, rebated after installation - Baseline Standard hot food holdin...
AI summary This table outlines the parameters for the ENERGY STAR® rated hot food holding cabinet measure, including installation rate, effective useful life, and energy savings calculations. The baseline is a standard hot food holding cabinet, and the measure is rebated after installation.
The electrical unitary energy savings for hot food holding cabinets are calculated using the ENERGY STAR Commercial Kitchen Calculator using the parameters in [Table](#page-155-1) 317 below.
AI summary The document discusses the calculation of electrical unitary energy savings for hot food holding cabinets using the ENERGY STAR Commercial Kitchen Calculator with parameters outlined in a referenced table.
Table 317: Electrical Unitary Energy Savings Values for Hot Food Holding Cabinets Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [...
AI summary This table outlines parameters and energy savings calculations for hot food holding cabinets, including annual operation days, average daily operation hours, interior volume, and energy consumption rates. Energy savings are calculated using the ENERGY STAR Commercial Kitchen Calculator.
Table 318: Unitary Peak Demand Savings Values for Hot Food Holding Cabinets Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF Actual or 0.68 As per Subsection 5.11.2 Unitary Peak Demand Savings [W] 𝑃𝑒𝑎𝑘 𝐷𝑒𝑚𝑎𝑛𝑑 𝑆𝑎𝑣𝑖𝑛𝑔𝑠𝑘𝑊 C...
AI summary The text presents a table discussing unitary peak demand savings values for hot food holding cabinets, including parameters such as the peak coincidence factor and the calculation of peak demand savings based on specification data for each rebated unit.
Table 319: Ice Machine Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated ice machine, rebated after installation - Baseline Standard ice machine - General Parameters Installa...
AI summary This table summarizes the parameters for an ENERGY STAR® rated ice machine measure, including installation rate, useful life, and energy savings calculations based on specification data. The savings are calculated using the ENERGY STAR Commercial Kitchen Calculator.
Table 320: Electrical Unitary Energy Savings Values for Ice Machines Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hours/day] HO...
AI summary Table 320 outlines parameters for calculating electrical unitary energy savings values for ice machines, including operational days, hours, equipment categories, ice type, harvest rate, energy use, and energy savings. The table references the ENERGY STAR Commercial Kitchen Calculator for calculations.
Table 321: Unitary Peak Demand Savings Values for Ice Machines Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF Actual or 0.68 As per Subsection 5.11.2 Unitary Peak Demand Savings [W] 𝑃𝑒𝑎𝑘 𝐷𝑒𝑚𝑎𝑛𝑑 𝑆𝑎𝑣𝑖𝑛𝑔𝑠𝑘𝑊 Calculation ba...
AI summary Table 321 outlines unitary peak demand savings values for ice machines, focusing on parameters such as the peak coincidence factor and unitary peak demand savings. It references Subsection 5.11.2 and includes installation rates as a consideration.
Table 322: Oven Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated oven, rebated after installation - Baseline Standard oven - General Parameters Installation Rate 100% See de...
AI summary Table 322 provides a summary of an oven measure, including details such as the measure description, baseline, installation rate, effective useful life, and energy savings parameters. The table outlines the ENERGY STAR® rated oven as the measure, with a standard oven as the baseline and includes various technical parameters related to energy savings.
The electrical unitary energy savings for ovens are calculated using the ENERGY STAR Commercial Kitchen Calculator using the parameters in [Table](#page-159-0) 323 below.
AI summary The document outlines the method for calculating electrical unitary energy savings for ovens using the ENERGY STAR Commercial Kitchen Calculator with specific parameters provided in a referenced table.
Table 323: Electrical Unitary Energy Savings Values for Ovens Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hours/day] HOU Actua...
AI summary This table outlines the parameters used to calculate electrical unitary energy savings values for ovens, including operation days, size, cooking efficiency, and energy savings. The values are based on actual measurements or ENERGY STAR defaults, with energy savings calculated using the ENERGY STAR Commercial Kitchen Calculator.
Table 324: Unitary Peak Demand Savings Values for Ovens Parameter Symbol BER-AR, SBES Reference Peak Coincidence Factor PCF Actual or 0.68 As per Subsection 5.11.2 Unitary Peak Demand Savings [W] 𝑃𝑒𝑎𝑘 𝐷𝑒𝑚𝑎𝑛𝑑 𝑆𝑎𝑣𝑖𝑛𝑔𝑠𝑘𝑊 Calculation based on...
AI summary The document presents Table 324, which outlines unitary peak demand savings values for ovens, including parameters such as the peak coincidence factor and calculation methods for peak demand savings. The table references Subsection 5.11.2 for the peak coincidence factor and provides installation rates.
Table 325: Steam Cooker Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated steam cooker, rebated after installation - Baseline Standard steam cooker - General Parameters Insta...
AI summary Table 325 outlines the parameters for the ENERGY STAR® rated steam cooker measure, including installation rate, effective useful life, and energy savings calculations. The table provides details on baseline measures, energy savings, and peak demand savings factors.
The electrical unitary energy savings for steam cookers are calculated using the ENERGY STAR Commercial Kitchen Calculator using the parameters in [Table](#page-161-1) 326 below.
AI summary The document discusses the calculation of electrical unitary energy savings for steam cookers using the ENERGY STAR Commercial Kitchen Calculator with specific parameters outlined in a referenced table.
Table 326: Electrical Unitary Savings Values for Steam Cookers Parameter Symbol BER-AR R, SBES Reference Annual Days of Operation [days/year] DAYS Actual Measure specific - use information in TS Average Daily Operation [hours/day] HOU Actu...
AI summary Table 326 outlines parameters for calculating electrical unitary savings values for steam cookers, including operational days, hours, type of steam, and energy efficiency metrics. It references the ENERGY STAR Commercial Kitchen Calculator for energy savings calculations.
5.12.4 Commercial Laundry Measures
AI summary The section titled '5.12.4 Commercial Laundry Measures' outlines regulatory considerations for energy efficiency and demand-side management initiatives targeting commercial laundry operations in Nova Scotia.
Table 328: Commercial Washing Machine Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure ENERGY STAR® rated commercial washing machine used for commercial purposes, rebated after installation •...
AI summary Table 328 outlines the parameters for the Business Energy Rebates (BER) program, focusing on ENERGY STAR® rated commercial washing machines. It details the measure description, baseline, installation rate, useful life, and energy and peak demand savings parameters, with references to specific subsections and reports.
Table 329: Electrical Unitary Energy Savings Values for Commercial Washing Machines Parameter Symbol BER-AR, SBES Reference Modified Energy Factor of Baseline Equipment [ft3/kWh] MEFb 1.26 Canadian Min. Efficiency per EEA, compliance date...
AI summary Table 329 provides electrical unitary energy savings values for commercial washing machines, including parameters like Modified Energy Factor (MEF) for baseline and efficient equipment, equipment capacity, number of loads run per year, and quantity of washing machines. It references ENERGY STAR and other compliance standards.
Summary [Table](#page-164-0) 331 presents a summary of the values used to calculate commercial heat pump clothes dryers savings. The detailed methodology follows.
AI summary Table 331 summarizes values used to calculate commercial heat pump clothes dryers savings. The detailed methodology for these calculations is provided in the document.
Table 331: Commercial Heat Pump Clothes Dryer Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Commercial heat pump clothes dryer meeting a minimum Combined Energy Factor (CEF) of 4.5, rebated...
AI summary This table outlines the parameters for the Commercial Heat Pump Clothes Dryer Measure, including eligibility criteria, baseline standards, and energy savings calculations. The measure is eligible for rebates if it meets a minimum Combined Energy Factor (CEF) of 4.5 and is ENERGY STAR® rated.
The electrical unitary energy savings for commercial heat pump clothes dryers are calculated using the variables defined and listed in the equation[339](#page-164-1) and [Table](#page-165-0) 332 below. $$\Delta kWh = QTY \times C_{dry} \ti...
AI summary The document explains the calculation of electrical unitary energy savings for commercial heat pump clothes dryers using a specific formula and table. The formula involves variables such as quantity, load average, and combined energy factors for base and efficient models.
Final Report 283 Table 332: Electrical Unitary Energy Savings Values for Commercial Heat Pump Clothes Dryers Parameter Symbol BER-AR, SBES Reference Quantity QTY Actual Use information in TS Loads per Year Cdry Multi-unit Residential 1,095...
AI summary The document presents a table detailing electrical unitary energy savings values for commercial heat pump clothes dryers, including parameters such as quantity, loads per year, average load, and energy factor (CEF) for baseline and efficient equipment. Calculations for unitary energy savings are based on specification data for each rebated unit.
Table 333: Unitary Peak Demand Savings Values for Commercial Heat Pump Clothes Dryers Parameter Symbol BER-AR, SBES Reference Time Cycle timecycle 1 Vermont 2015 TRM Peak Coincidence Factor PCF Actual or 0.34 See Subsection 5.12.2 Unitary...
AI summary Table 333 presents unitary peak demand savings values for commercial heat pump clothes dryers, including parameters such as time cycle, peak coincidence factor, and unitary peak demand savings. The table references technical specifications and calculation methods for determining these values.
Table 334: Demand Controlled Kitchen Exhaust Measure Summary Parameter BER-AR, SBES Reference Measure Description and Identification Measure Controlled by temperature and/or optical sensors located in exhaust hood, rebated after installati...
AI summary Table 334 outlines the Demand Controlled Kitchen Exhaust (DCV) measure under the Business Energy Rebates (BER) program. It details parameters such as installation rate, useful life, and energy savings calculations based on specification data for each rebated unit.
Table 336: Unitary Peak Demand Savings Values for Demand Controlled Kitchen Exhaust Parameter Symbol BER-AR, SBES Reference Demand Savings Factor (kW/hp) DSVG 0.76 Pennsylvania TRM 2016 Peak Coincidence Factor PCF 0.68 As per Subsection 5....
AI summary Table 336 presents unitary peak demand savings values for demand controlled kitchen exhaust, including parameters like Demand Savings Factor and Peak Coincidence Factor, along with their respective values and references.
Summary [Table](#page-168-0) 337 presents a summary of the values used to calculate server-based power management software savings. The detailed methodology follows.
AI summary Table 337 summarizes the values used to calculate server-based power management software savings, with a detailed methodology provided in the document.
The electrical unitary energy savings for server-based power management software are calculated using the variables defined and listed in the equation[342](#page-168-1) and [Table](#page-169-0) 338 below. $$\Delta kWh = ESF_D Q_D + ESF_L Q...
AI summary The document explains how electrical unitary energy savings for server-based power management software are calculated using the equation Δ kWh = ESF_D Q_D + ESF_L Q_L, with reference to a technical manual and a table.
2024-2025 DSM Measure Assessment Table 338: Electrical Unitary Energy Savings Values for Server-based Power Management Software Parameter Symbol BER-AR, SBES Reference Energy Savings Factor for a Desktop Computer ESFD 356 Based on ENERGY S...
AI summary The document presents a table outlining energy savings values for server-based power management software, including energy savings factors and quantities for desktop and laptop computers. Calculations are based on assumptions from the ENERGY STAR Computer Power Management Savings Calculator and data from a 2004 Lawrence Berkeley National Lab Report.
$$\Delta kWh = (kWh_{BV} - kWh_{AV})/VH$$ $$kWh_{BV} = \frac{8,760}{1,000} \times RS \times \left(W_{rs, idle} + U_{rs} \left(W_{rs,full load} - W_{rs,idle}\right)\right)$$
AI summary The text contains mathematical formulas related to energy calculations, specifically focusing on kilowatt-hour (kWh) differences and calculations involving various energy-related variables such as RS, W_rs, idle, and U_rs. These formulas are likely used for energy efficiency or demand-side management purposes.
290 Table 342: Unitary Peak Demand Savings Values for Server Virtualization and Decommissioning Parameter Symbol BER-AR, SBES Reference Hours of Use [h/year] HOU 8760 Assumption Unitary Peak Demand Savings [W] ∆𝑘𝑊 Calculation based on spec...
AI summary The text presents a table detailing unitary peak demand savings values for server virtualization and decommissioning, including parameters such as hours of use and unitary peak demand savings. It also mentions installation rates, though details are not provided.
Table 344: Electrical Unitary Energy Savings Values for Uninterruptible Power Supply (UPS) Parameter Symbol BER-AR, SBES Reference Energy Use per Rated kVA - 204 CMUA California 2017 TRM UPS Power [kVA] 𝑘𝑉𝐴 Actual Use information in TS Uni...
AI summary Table 344 outlines the electrical unitary energy savings values for Uninterruptible Power Supply (UPS) systems, including parameters such as energy use per rated kVA and UPS power. It references the Business Energy Rebates (BER) program and provides calculation methods for energy savings.
6 Effective Useful Life This section outlines the EUL values used to calculate lifetime energy savings. This section also presents EUL values for demand reduction measures; these values are not used to calculate lifetime energy savings sin...
AI summary The section explains that Effective Useful Life (EUL) values are used to calculate lifetime energy savings for energy-saving measures, while demand response measures use EUL to represent the duration of demand reduction. EUL values are crucial for cost-effectiveness ratio calculations to ensure lifetime benefits are accounted for.
6.1 LED Lamps and Fixtures To establish lifetime energy savings for LED lamps and fixtures, the equipment life is determined using rated lifetimes identified in product specification sheets and annual HOU, as described in the equation belo...
AI summary The document explains how to calculate the equipment life of LED lamps and fixtures using rated lifetimes and annual HOU. It also discusses the need for an equivalent EUL to account for regulatory changes affecting baseline energy use over time, with detailed calculations provided in Appendix III.
Table 345: EUL Values for BNI LED Lamps and Fixtures Measure Program Component Average Rated Lifetime (hours) Annual HOU (hours/year) Equipment Life 2024 Equivalent EUL LED Decorative (Chandelier) SBES 25,000 3,600 6.9 1.0 LED Omnidirectio...
AI summary Table 345 presents EUL (Effective Useful Life) values for various BNI LED lamps and fixtures under different programs, including SBES and BER-AR. The table includes metrics such as average rated lifetime, annual HOU, equipment life, and 2024 equivalent EUL for different lamp types and replacements.
Table 346: EUL Values for Non-LED Lighting BNI Measures Measure Name Program Component EUL Value Reference Lighting Controls Occupancy Sensors BER-IR, BER-AR, SBES 10 GDS, 2007 (Table 2 – Commercial & Industrial Measures, value for occupan...
AI summary Table 346 presents Effective Useful Life (EUL) values for various non-LED lighting and related Building Efficiency Incentive (BNI) measures, including occupancy sensors, heat pads, ventilation fans, and waterers, with references to different studies and reports.
Verification of Climate Validity for Interactive Effects Calculations The climate data of Nova Scotia and Quebec for the duration of the heating and cooling seasons were analyzed as part of the 2015 evaluation and found to be comparable, a...
AI summary The 2015 analysis compared Nova Scotia and Quebec's climate data for heating/cooling seasons, finding them comparable, thus applying the 1992 ADS study results to E1 lighting measures.
APPENDIX II Detailed Calculations of 2024 Equivalent EUL Values for LED Lamps and Fixtures This appendix presents how the equivalent effective useful life (EUL) of LED lamps and fixtures were calculated for applicable measures in the EPI a...
AI summary This appendix explains the calculation of the equivalent effective useful life (EUL) for LED lamps and fixtures in the EPI and Instant Savings programs. The EUL is determined by comparing the manufacturer-rated lifetime of the equipment with annual HOU values used to calculate unitary savings.
Rationale for Using an Equivalent EUL The LED market is evolving rapidly, driven in part by government regulations. LED products installed today are likely to become the baseline before the end of their rated lifetime since LED technologie...
AI summary The text discusses the evolving LED market and the rationale for using an equivalent EUL (Energy Use Life) in light of government regulations and market trends. It notes that LED technologies are rapidly improving and becoming the baseline, with U.S. and Canadian regulations influencing the adoption of higher efficiency standards. The Evaluator expects LED to become the standard by 2025, making 2024 the last year with savings before the new baseline is applied.
Table 348: LED Baseline Evolution for Rebate on Purchase (Instant Savings) Baseline Minimum Wattage Requirement Years Rationale A-type Incandescent Baseline N/A 2024 (1,000 hours) Since incandescent lamps may no longer be replaced by incan...
AI summary The table outlines the evolution of LED baseline wattage requirements for rebate programs, referencing incandescent and halogen baselines. It discusses the transition from traditional lighting to LED, with savings calculations for direct-install programs, assuming LED bulbs become available starting in 2025.
LED A-type Lamps LED A-type lamps installed under EPI replace incandescent lamps. The calculation is based on 9 W lamps because they are the most common A-type lamps installed through EPI. The first baseline increase occurs one year follow...
AI summary LED A-type lamps under EPI replace incandescent lamps, using 9W as the standard. The baseline calculation accounts for a 25-year lifespan, with regulatory changes in 2025 shifting the baseline to LED equivalents. The equation and table detail the Equivalent Useful Life (EUL) calculation over 25 years, showing displaced wattage from incandescent to LED lamps.
Table 350: Equivalent EUL Calculation for Solar Fixtures Average Replaced Average Wattage of Efficient Lamp Halogen Incandescent Baseline – Canadian Legislation 1 Year (2024) LED Equivalent Baseline – American Legislation369 9 Years (2025-...
AI summary Table 350 provides an Equivalent Useful Life (EUL) calculation for solar fixtures, comparing halogen incandescent and LED baseline wattages. The table highlights the displaced wattage from replacing traditional lamps with more efficient alternatives, such as LED, and notes the significant difference in EUL between Canadian and American legislation standards.
LED Non-A-type Lamps For LED non-A-type lamps sold through Instant Savings, lifetime energy savings values were established for the different types of lamps replaced, which mostly included reflector (R, BR, GU, PAR, MR) and decorative lamp...
AI summary LED non-A-type lamps sold via Instant Savings will no longer generate energy savings after 2025 due to EISA 2020 regulations increasing baseline wattage to match LED efficiency. This results in an equivalent useful life (EUL) of one year for these lamps, as savings only occur in the year prior to the baseline adjustment.
LED Fixtures As for LED fixtures without motion sensors (including recessed downlight fixtures), the equivalent EUL is analyzed in the same manner as for replace-on-burn-out lamps since the energy consumption of these fixtures is the consu...
AI summary The analysis discusses LED fixture energy efficiency, noting that fixtures without motion sensors will no longer generate savings post-2025 due to regulatory baseline adjustments. For motion-sensor LED fixtures, savings calculations account for reduced wattage and usage hours, with reflector lamps as the baseline. Upcoming Amendments 18 & 19 influence these standards.
Table 351: Lifetime Energy Savings for LED Fixtures with Motion Sensors - Reduced wattage Average Replaced ed Wattage of 1 Year (2024) LED Equivale American Le 23 Years (2 Lifetime Energy Savings Lamp (W) (W) Baseline Wattage Displaced Wat...
AI summary Table 351 presents the lifetime energy savings for LED fixtures with motion sensors, showing a reduction in wattage and energy consumption over 23 years. It compares baseline and displaced wattage for different lighting technologies, highlighting the energy savings achieved by using LED fixtures.
Table 352: Lifetime Energy Savings for LED Fixtures with Motion Sensors - Reduced Hours of Use Old Average Hours of Use (hours per day) New Average Hours of Use (hours per day) Average Wattage of Efficient Lamp Measure Life (years) Lifetim...
AI summary Table 352 presents the lifetime energy savings for LED fixtures with motion sensors, showing a reduction in hours of use from 4.69 to 2.90 per day, resulting in 146 kWh of energy savings over a 10-year period. The equivalent useful life (EUL) was calculated as 1.6 years based on total savings and first-year savings.
Table 353: Equivalent EUL Calculation for Solar Fixtures Average Replaced Lamp (W) Average Wattage of Efficient Lamp Canadian escent Baseline – Legislation · (2024) LED Equivalent Baseline – American Legislation 371 9 Years (2025-2033) (VV...
AI summary Table 353 compares the Equivalent Useful Life (EUL) of solar fixtures under different legislative baselines. It includes data on average replaced lamp wattage, baseline wattage, and displaced wattage for Canadian and American legislation, with specific values provided for 2024 and 2025-2033.
APPENDIX III Detailed Calculations of 2024 Equivalent EUL Values for LED Lamps and Fixtures This appendix presents how the equivalent effective useful life (EUL) of LED lamps and fixtures were calculated for applicable measures in the SBES...
AI summary This appendix details the calculation of equivalent effective useful life (EUL) for LED lamps and fixtures in the SBES program component. The EUL is calculated as the ratio between the manufacturer-rated lifetime and the annual HOU values used to determine unitary savings.
Table 354: Equipment Life Value per LED Lamp and Fixture Types LED Lamp and Fixture Type Program Component Average Rated Lifetime Hours (hours)372 Annual HOU (hours/year)373 Equipment Life (years) LED General-use and Decorative Lamps SBES...
AI summary Table 354 provides equipment life value data for various LED lamp and fixture types, including average rated lifetime hours, annual hours of use, and equipment life in years for different programs and components.
Table 355: LED Baseline Evolution Baseline Minimum Wattage Requirement Years Rationale A-type Incandescent Baseline N/A 2024 (1,000 hours) Since incandescent lamps may no longer be replaced by incandescent lamps, there is a first increase...
AI summary The text discusses the evolution of LED baseline requirements in Nova Scotia, referencing American legislation and Canadian regulations. It outlines the minimum wattage requirements and timelines for different types of lamps, including incandescent, halogen, and LED equivalents, with rationale for changes in baseline standards.
Table 356: Baseline Evolution During the Effective Useful Life of LED General-use and Decorative Lamps Typical Replaced placed Efficient 1 Tear (2024) LED Equivale American L 5.9 Years ( Equivale nt EUL Lamp (W) Lamp (W) Baseline Wattage D...
AI summary Table 356 outlines the baseline evolution of LED general-use and decorative lamps over their effective useful life, comparing wattage and equivalent useful life (EUL) across different lamp types and years.
Table 357: Baseline Evolution During the Effective Useful Life of LED Reflector Lamps Typical Replaced laced Efficient LED Equival American L 5.9 Years Equivalent EUL Lamp (W) Lamp (W) Baseline Wattage Displaced Wattage Baseline Wattage Di...
AI summary Table 357 outlines the baseline evolution of LED reflector lamps over their effective useful life, comparing typical replaced lamps with their LED equivalents in terms of wattage and equivalent useful life (EUL). The table includes data for 43W and 12W lamps, with the latter having an EUL of 1.0 years.
Since non-recessed LED downlight fixtures replace fixtures using A-type lamps, the methodology for establishing their equivalent EUL is similar to that of A-type lamps in Efficient Product Installation (EPI). The equivalent EUL calculation...
AI summary The text discusses the methodology for calculating the equivalent EUL of non-recessed LED downlight fixtures, comparing them to A-type lamps in the Efficient Product Installation (EPI) program. The calculation takes into account the rated life of LED lamps and a regulatory change in 2025 that affects the baseline for energy savings.
Table 358: Baseline Evolution During the Effective Useful Life of Downlight Fixtures Typical Replaced Lamp Typical Efficient Incandesce Halogen Incandescent and Incandescent Baseline 1 Year (2024) LED Equivalent Baseline - American Legisla...
AI summary Table 358 details the baseline evolution of downlight fixtures over their effective useful life, comparing incandescent and LED lighting technologies. It highlights the displacement of wattage and the expected lifespan of these fixtures under different legislative standards.
Since LED recessed downlight fixtures replace fixtures typically housing reflector lamps for which the baseline technology is halogen lamps, the methodology for establishing their equivalent EUL is similar to that of reflector lamps. The E...
AI summary The document discusses the calculation of the Equivalent Useful Life (EUL) for LED recessed downlight fixtures, comparing them to halogen lamps. It outlines a methodology based on energy consumption differences and regulatory changes affecting reflector lamps, which are set to impact the baseline technology in 2025. The EUL for LED fixtures is calculated as 13.9 years, with a specific calculation example provided.
Table 359: Baseline Evolution During the Effective Useful Life of LED Reflector Lamps in Downlight Fixtures Typical Replaced Typical Efficient Baseline (2024) LED Equivale American Le 12.9 Years ( gislation 383 Equivalent EUL Lamp (W) Lamp...
AI summary Table 359 outlines the baseline evolution of LED reflector lamps in downlight fixtures, comparing typical replaced and efficient lamps, their wattage, and the equivalent useful life (EUL) based on U.S. federal legislation, specifically the Energy Independence and Security Act (EISA) 2007.
APPENDIX IV Interactive Effects Methodology for Commercial Lighting The interactive effects calculation methodology for commercial lighting was revised as part of the 2024-2025 DSM Measure Assessment update. This appendix details how the c...
AI summary The interactive effects methodology for commercial lighting was revised in the 2024-2025 DSM Measure Assessment update. The appendix explains revised calculation methods for interactive effect factors, applicable only to 2025 savings due to required changes in tracking data and adjustment ratios.
Calculation Approach Pursuant to a literature review of methodologies used by other jurisdictions and of the Uniform Methods Project recommendations, the Evaluator decided to continue applying an engineering calculation approach to estimat...
AI summary The Evaluator opted for an engineering calculation approach to estimate interactive effects, updating methods based on recent data and Uniform Methods Project recommendations. Equations for energy and peak demand savings interactive effects are outlined.
Where: - › %LightingIndoor : The percentage of fixtures and lamps that are installed in indoor conditioned spaces as only those result in interactive effects. - › %LightingHeatConditioned : The percentage of heat generated by lighting and...
AI summary The text defines technical variables used to calculate energy interactive effects factors for heating and cooling systems, including lighting impact fractions, building efficiency factors, and system COP values. It provides an equation for peak demand savings interactive effects, focusing on winter peak hours and excluding cooling system operations during these periods.
Calculation of Building and System-Specific Intermediate Values This first subsection details how the BuildingHeatE , BuildingCoolE, and BuildingHeatPD variables are calculated.
AI summary This section outlines the methodology for calculating BuildingHeatE , BuildingCoolE , and BuildingHeatPD variables, which are critical for assessing building-specific energy performance and cooling demand in regulatory analyses.
Table 360: Lighting Operation Schedule per Building Archetype Building Archetype 8 A.M to 4 P.M. 8 A.M. to 6 P.M. 24 hours Agriculture X Banking / Financial X Education X Entertainment / Public Assembly X Healthcare X Hospitality X Manufac...
AI summary Table 360 outlines the typical lighting operation schedules per building archetype, indicating when lighting is expected to be on during the day and throughout the 24-hour period. These schedules are used to calculate interactive effects factors for lighting operations across different building types.
Heating and Cooling Season Temperatures below 13°C might occur during parts of the year when heating systems are not active, in which case efficient lighting would have no impact on the heating load. The same concept is true of temperature...
AI summary The Evaluator defined heating and cooling seasons (October 1–April 30 and the remainder of the year, respectively) to determine when efficient lighting impacts heating/cooling loads, based on temperature thresholds (below 13°C and above 15°C). This delineation excludes periods with minimal degree-days from affecting heating/cooling demands.
For each measure installed in BER-AR or SBES, the space heating and cooling systems are known and the efficiency of each is applied as per the following table. Table 361: Coefficient of Performance (COP) by Space Heating and Cooling System...
AI summary The text outlines the coefficient of performance (COP) for various space heating and cooling systems, including electric resistance heating, heat pump heating, and air conditioning. These values are applied to measures installed in BER-AR or SBES and are based on conventions, standard mini-split heat pump COPs, and assumptions.
Using the equations and the parameters described above, the Evaluator developed the BuildingHeatE and BuildingCoolE tables below for electrical energy consumption and peak demand. The information in the tables is applicable to both SBES an...
AI summary The document discusses the development of BuildingHeatE and BuildingCoolE tables for electrical energy consumption and peak demand, applicable to both SBES and BER-AR. It notes that assumptions regarding interactive effects factors were not initially documented and references a 1992 study by ADS ASSOCIÉS for residential interactive effects.
Table 362: BuildingHeatE and BuildingCoolE by Facility Type and Heating and Cooling System Type Facility Type BuildingCoolE Electric Resistance Heating (COP = 1) Air-source Heat Pump Heating (COP = 1.8) Non electric Heating Cooling (COP =...
AI summary The tables present data on the percentage of heat generated in indoor conditioned spaces by facility type and heating/cooling system type. The data highlights significant variations in efficiency across different systems and facility categories.
Table 364: Values for %LightingHeatConditioned per Measure Type Measure Type % Heat in Conditioned Space Linear LED Fixtures Recessed 57%389 Non-recessed 100% Linear LED Lamps Recessed 57% Non-recessed 100% High Bay Fixtures 0%390 Outdoor...
AI summary Table 364 provides percentages of heat in conditioned space for various lighting and heating measures, including LED fixtures, motion sensors, and other efficiency-related measures. The data highlights differences in heat contribution based on fixture type and installation location.
Table 367: Participant Spillover Types Like Spillover Program-induced actions taken outside of the program that are similar to the actions taken as part of the program. (i.e. if a participant in a program that offers rebates on a menu of m...
AI summary The text discusses 'like' and 'unlike' spillover effects in energy efficiency programs, explaining that like spillover occurs when participants take similar actions outside the program, while unlike spillover involves different actions. Like spillover is more commonly captured in studies, whereas unlike spillover is harder to measure through surveys and often requires educational components in program design.
Spillover Scoring Typically, spillover is captured in a series of three to five questions to discern if any further energy efficiencyrelated actions took place after the participant took part in the program. If the participant took further...
AI summary Spillover scoring assesses additional energy efficiency actions taken by program participants post-enrollment. Savings from these actions are multiplied by a spillover score and divided by total program savings to calculate net spillover impact. Follow-up interviews are recommended for complex measures to estimate savings accurately.
Data Collection Elements - › Pretest the survey to ensure that: - › Questions are correctly understood - › Questions provide results that are valid and reliable - › Skips work as they should - › Questions and sections flow well - › To impr...
AI summary The text outlines best practices for data collection in energy efficiency programs, emphasizing pretesting surveys, improving response rates through branding and incentives, conducting fieldwork promptly to minimize recall bias, and using qualified interviewers. It also notes considerations for spillover effects and the importance of timing in survey design.
Table 369: Summary of E1's Current NTGR Approach Program Component Measures for Which FR Is Established Year of Last FR Update Current Spillover Methodology Year of Last Spillover Update Proposed Changes ARet FR determined for all measures...
AI summary This table outlines EfficiencyOne's (E1) current approach to Net-to-Gross Ratio (NTGR) for various program components, including the establishment of Free-Rider (FR) rates, spillover methodologies, and proposed changes. The table includes details for ARet, IS, and HEA, with specific FR rates, spillover methodologies, and planned updates for 2025.
9 Program Algorithms In the subsections that follow, two E1 program algorithms are evaluated in more detail – those of EPI and BER-IR as examples as the NTGR for these programs will be updated as part of the 2024 Evaluation. For each algor...
AI summary The document evaluates EPI and BER-IR program algorithms under E1, reviewing alignment with best practices. It outlines current and recommended algorithm elements, including variables, question design, scoring, and consistency checks, with revisions highlighted in light green for the 2024 NTGR update.
Final Report 341 Current A lgorithm Adjuste d Algorithm Quantity Score (PA4) E6 Quantity Score (QS) E6 Inconsistency Test IF E1=100% AND IF E3<70% OR E4<70% E1=EMPTY Inconsistency Test IF E1=100% AND IF E3<75% OR E4<75% E1= EMPTY Inconsist...
AI summary The text presents a comparison between current and adjusted algorithms for calculating quantity scores and inconsistency tests, including changes in thresholds and handling of empty values. It also includes a question about the influence of free installation of energy-efficient products on customer decisions.
Table 373: Instant Rebates Distributor Influence Level Algorithm Current Algorithm Adjusted Algorithm
AI summary This table outlines the current and adjusted algorithms for the Instant Rebates Distributor Influence Level, which is part of a broader discussion on energy efficiency programs and rebate distribution mechanisms.
G-Report_FINAL_2021.06.08.pdf)[PRODNTG\_Res-Products-NTG-Report\_FINAL\_2021.06.08.pdf.](https://www.ma-eeac.org/wp-content/uploads/MA20X04-E-PRODNTG_Res-Products-NTG-Report_FINAL_2021.06.08.pdf) NMR Group, Inc and DNV for Massachusetts Pr...
AI summary The document references multiple reports and memoranda related to energy efficiency program methodologies, focusing on Net-to-Gross Ratios (NTGR) for fuel-switching heat pumps and residential self-report measurement updates. Key entities include NMR Group, DNV, Tetra Tech, and Massachusetts Program Administrators, emphasizing standardized evaluation approaches for energy savings.
ww.iepec.org/wp-content/uploads/2018/04/Paper-](https://www.iepec.org/wp-content/uploads/2018/04/Paper-Violette.pdf)[Violette.pdf.](https://www.iepec.org/wp-content/uploads/2018/04/Paper-Violette.pdf) Violette, Daniel M., and Rathbun, Pame...
AI summary The text references a 2017 paper by Violette and Rathbun on the Uniform Methods Project's approach to estimating energy efficiency savings. It includes a project number (6562) and links to documents from NREL and IEPEC, focusing on methodologies for net savings calculations in energy efficiency programs.
This report, conducted by H. Gil Peach & Associates LLC, for the Nova Scotia Energy Board, verifies electricity energy savings and demand reduction for 2024. It reviews measurements, models, and estimates provided by Econoler, the Independ...
AI summary This report, conducted by H. Gil Peach & Associates LLC for the Nova Scotia Energy Board, verifies energy savings and demand reduction estimates for Efficiency Nova Scotia's DSM programs. It reviews Econoler's evaluations and provides recommendations for adjustments if necessary.
III. Resource Acquisition and Other Evaluation Frameworks Efficiency Nova Scotia programs are almost entirely resource acquisition programs that treat saved energy as equivalent to generated energy. This is the original framework for the e...
AI summary Efficiency Nova Scotia programs treat saved energy as equivalent to generated energy, evaluated via resource acquisition frameworks. Econoler's approach is highlighted, with references to market transformation evolution and evaluation methodologies like impact and process evaluations. The text cites Rogers' work on innovation diffusion.
2. Evaluated Net First-Year Energy Savings at the Generator Table 2 presents first-year savings, and lifetime energy savings from the Econoler evaluations
AI summary The document evaluates net first-year energy savings at the generator level based on Econoler evaluations. Table 2 provides data on first-year and lifetime energy savings from these assessments.
3. Sector Contributions In Figure 4, BNI contributes net peak demand savings at the generator of about 45%; about 55% is contributed from the Residential sector. 19 The whole numbers shown on the bars in [Figure 3](#page-17-1) can be consi...
AI summary The document highlights sector contributions to demand reduction and energy savings, showing BNI contributing 45-55% of net peak demand savings and energy savings across short-term and lifetime evaluations, with the Residential sector accounting for the remaining share.
VII. Savings Verification Approach The savings verification review was conducted as follows: - We focus on the "installed" annual energy savings and demand reductions. These are the annualized value of savings and demand reductions from th...
AI summary The savings verification approach focuses on annualized energy savings from installed measures, reviews methodological approaches for program analyses, and conducted 93 site visits for the 2024 program year. Mathematical calculations were not verified, but presentation of methods and interactions like free-ridership were assessed.
VIII. General Findings • The method followed in each program impact evaluation follows a recognized analytic approach appropriate for each program type. The structure and format of each impact evaluation follows a consistent template (exce...
AI summary The evaluation methods for program impacts are recognized and consistent, with clear structures and methodological models. The Evaluator demonstrates expertise in guidelines and calculations, though behavioral programs lack physical measures for evaluation. Four process evaluations and two market evaluations are noted, with recommendations for more process evaluations.
IX. General Recommendations SVR24-G-1. The Savings Verification study recommends acceptance of the 2024 evaluation estimates for energy savings and demand reduction except for four programs . These are the Residential Behavior program (6.2...
AI summary The Savings Verification study recommends accepting 2024 energy savings estimates for most programs but excludes four due to evaluation issues. The BNI Custom Incentive Program's compressed air audit lacks independent evaluation per protocols. Residential Behavior and Demand Response programs show statistically significant but impractically small savings, requiring reevaluation. Evaluators must flag low-impact programs and ensure transparency in statistical testing.
A. Appliance Retirement Program (ARet) The Appliance Retirement (ARet) program is one of two program components of the Residential Efficient Product Rebates program. Appliance Retirement advances the retirement of old, inefficient full siz...
AI summary The Appliance Retirement Program (ARet) retires inefficient appliances through rebates and free removal, retiring 77,696 appliances since 2012. Rebates include $50 for full-sized refrigerators/freezers and $10 for smaller appliances. Rule changes since 2016 link room air conditioner collection to full-sized appliance retirement for cost-effectiveness. ARCA Canada Inc. manages collection and recycling.
B. Instant Savings (IS) The Instant Savings program is one of two components of the Residential Efficient Product Rebates program. Instant Savings is an instant cash rebate program offered to purchasers of energy efficient products, delive...
AI summary The Instant Savings program, part of Efficiency Nova Scotia's Residential Efficient Product Rebates, offers cash rebates for energy-efficient products via retailers and online platforms. In 2024, 395,472 products were sold, a 82% increase from 2023, with Energy Start LED Fixtures leading sales. The program achieved 26.884 GWh energy savings and 2.955 MW peak demand reduction in 2024, with evaluations focusing on savings calculations, GHG reductions, and market spillover effects.
Evaluator Findings. The Evaluator reported the following key Instant Savings findings: - Instant Savings exceeded both 2024 planned net electrical energy and peak demand savings of 12.544 GWh and 1.680 MW, respectively. - 2024 net electric...
AI summary Instant Savings exceeded 2024 energy and peak demand savings targets by 77% and 45%, driven largely by ENERGY STAR LED products. Non-lighting savings increased 17% YoY, and free ridership for LEDs dropped from 59% to 39%. Evaluated savings were 16-10% higher than Efficiency Nova Scotia's tracked values. The evaluation methodology was deemed appropriate and excellent.
C. Home Energy Assessment (HEA) Home Energy Assessment (HEA) is a component of the Existing Residential Programs. This program encourages homeowners to increase the efficiency and comfort of their homes by providing rebates for qualified e...
AI summary The Home Energy Assessment (HEA) program promotes residential energy efficiency through rebates for retrofits and products. It uses 'test-in/test-out' audits and blower door testing to assess homes, with a 2024 focus on heat pump adoption. Evaluation included surveys, AMI data analysis, and assessments of energy savings and GHG reductions.
D. Green Heat Green Heat is a component of Efficiency Nova Scotia's Existing Residential program, providing financial incentives for the installation of efficient heating systems that use fuel from renewable resources. The new equipment ca...
AI summary Green Heat, part of Efficiency Nova Scotia's program, offers incentives for renewable heating systems. Installations declined by 21% in 2024 due to participants shifting to higher-incentive programs like HEA and CGH. Rebates vary by measure, including heat pumps, biomass, solar, and demand reduction. Nova Scotia Power provides on-bill financing for heat pumps.
Efficient Product Installation (EPI) The Efficient Product Installation program (EPI) provides free direct installation of energy-efficient products to homeowners and renters, provided through contractors. In 2024 the Evaluator conducted a...
AI summary The Efficient Product Installation (EPI) program offers free direct installation of energy-efficient products, including smart thermostats and air sealing measures. In 2024, a market evaluation identified new opportunities for electrician-installed measures as E1 phases out lighting programs. The program expanded to include eight new electrician-installed measures and conducted jurisdictional scans in nine regions to identify best practices.
Potential measures highlighted include: - Advance heat recovery ventilator controls consuming 67% less energy. - Bathroom fans -efficient models saving up to 35.4 kWh per year. - Block heater timers with unitary savings of 122 kWh/year. -...
AI summary The text outlines potential energy-saving measures, including heat recovery ventilators (67% energy reduction), efficient bathroom fans (35.4 kWh/year savings), block heater timers (122 kWh/year savings), and heat reflector panels (143 m³ natural gas/year savings), highlighting specific technologies and their estimated impacts.
EPI's two funding sources are: - 1. Electricity ratepayers to fund upgrades to reduce electricity consumption. - 2. Government of Nova Scotia and the federal Low Carbon Economy Fund funds upgrades that reduce the use of other fuels. The Ev...
AI summary The Efficient Product Installation (EPI) program's 2024 evaluation highlights a 2.4% increase in participation (9,993 vs. 9,763 in 2023) and 150,722 efficient products installed, though energy savings decreased by 6.3% per participant. LED lamps dominated installations (74%), but smart thermostat adoption dropped due to dissatisfaction. The Evaluator recommends improving installer education and customer support to address these issues.
F. Mi'kmaw Home Energy Efficiency Program (MHEEP) MHEEP is a component of the Existing Residential Programs. Initiated in June 2018 as the First Nations Home Energy Efficiency Pilot, MHEEP began operations in 2019 as a residential energy e...
AI summary The Mi'kmaw Home Energy Efficiency Program (MHEEP) provides no-cost energy efficiency upgrades to Mi'kmaw communities in Nova Scotia through collaboration with E1 Program Staff, community housing managers, and delivery agents. Measures include building envelope upgrades, heating equipment, and appliance replacements, funded by two sources. The program uses EnerGuide audits for home assessments.
G. Affordable Multifamily Housing (AMH) The Affordable Multifamily Housing (AMH) program provides affordable-housing owners and nonprofit organizations, including rehabilitation and transition housing, with incentives for building-wide ene...
AI summary The Affordable Multifamily Housing (AMH) program offers incentives for energy retrofits in affordable housing and nonprofits, with two funding streams: electric ratepayer-funded and province-funded measures. Participation increased from 79 to 83 projects in 2024, with comprehensive projects rising 70% and prescriptive projects declining 6%. Prescriptive projects showed higher energy savings than comprehensive ones, while 2024 rebate caps remained unchanged at $17,254 per unit and $300,000 per building.
The Evaluator: - Developed participant survey. - Conducted interviews with program staff, heat pump contractors, and delivery agents (DAs) To determine the gross and net electrical energy and peak demand savings and avoided annual GHG emis...
AI summary The evaluator conducted surveys and interviews to assess the Affordable Single-Family Homes (ASFH) program, finding high satisfaction but issues with wait times and information. The program exceeded energy savings and peak demand reduction targets, though adjustments reduced reported savings by 21% and 3%. Recommendations include improving delivery processes and communication.
participation in the measure-based programs[.42](#page-52-1) Out of nine similar analyses of possible effect, the Evaluator only claims a (very tiny) effect for three of the nine analyses (one-third). The three claims include for Green Hea...
AI summary The evaluation of measure-based programs shows minimal effectiveness, with only three out of nine analyses claiming a very small effect. Green Heat and Efficient Products Installation programs show effects of 0.1% and 0.4%, respectively, while the Home Energy Assessment program shows no effect. The analysis highlights concerns about selection bias and the importance of including opt-out subjects in evaluations.
Table 7: Evaluation Claimed Influence on Participation in Other Programs. Measure-Based Program Encouragement Results (Difference of Means) Subgroup Treatment Control (Size of) Difference (Is There a) Claimed Effect High Energy Use HEA 1.6...
AI summary Table 7 evaluates the influence of participation in energy efficiency programs on other programs. Results show no significant claimed effect for HEA and EPI in high and medium energy use subgroups, while Green Heat shows a claimed effect in high and medium energy use subgroups. The table references statistical methodologies and discussions on significance testing.
2. Recommendations SVR2024-Behaviour-5. Overall, we recommend that the program be continued, but not as a direct energy savings program. Rather, it should be redesigned and evaluated as a marketing and promotional program designed to (1) s...
AI summary The recommendations emphasize redesigning the program as a marketing initiative to boost recruitment for measure-based programs and raise energy efficiency awareness. Current evaluations lack data on effective household behaviors for real energy savings, necessitating improved measurement of participation and impact.
Recommendations SVR2024-BNI Efficient Products – 8. Change baselines for BER and IR rebates to reflect current market practices that have indoor DesignLights Consortium-Standard products as the new baseline with incentives offered for comp...
AI summary The recommendations propose updating BER and IR rebate baselines to use DesignLights Consortium-Standard products as the new benchmark, offering incentives for Premium equivalents. A review of in-situ meter studies for multi-wattage LED lighting products is also recommended, with a study commissioning option if no existing data is available.
K. BNI Custom Incentives Program (Custom Component) For 2024, the BNI Custom Incentives Program consists of two components, Custom and Strategic Energy Management (SEM). The Custom program is comprised of four parts: Retrofit, New Construc...
AI summary The BNI Custom Incentives Program (2024) includes Retrofit, New Construction, Pay-for-Performance, and Building Optimization components. Retrofit contributed 42% of total savings via compressed air audits, with a 522% increase in savings compared to 2023. Two sites accounted for 69.6% of total tracked savings, producing 364% of 2023 compressed air audit savings in 2024.
L. BNI Strategic Energy Management (SEM) Strategic Energy Management (SEM) is an approach for integrating energy management into business practice – so that a focus on continually advancing energyefficiency becomes an integral aspect of wo...
AI summary Strategic Energy Management (SEM) integrates energy efficiency into business practices, expanding from manufacturing to sectors like healthcare and education. The 2024 evaluation showed a 32.4% increase in tracked savings, driven by two major participants, with 53% from compressed air leak repairs. SEM's Net to Gross Ratio (NTGR) was set to 1, indicating no free ridership. Program targets for energy savings and peak demand were exceeded by 6% and 14%, respectively.
A. General Recommendations There are four general recommendations . SVR24-G-1. The Savings Verification study recommends acceptance of the 2024 evaluation estimates for energy savings and demand reduction except for four programs . These a...
AI summary The text outlines four general recommendations for evaluating energy savings programs. It highlights issues with the Residential Behavior and Demand Response programs, noting their minimal practical impact despite statistical significance. It also criticizes the lack of independent evaluation for compressed air projects under the BNI Custom Incentive Program and emphasizes the need for transparency in evaluation protocols and statistical reporting.
rs/sufficiency-introduction-final-oct2018.pdf)[introduction-final-oct2018.pdf.](https://www.energysufficiency.org/static/media/uploads/site-8/library/papers/sufficiency-introduction-final-oct2018.pdf) Dimetrosky, S.; Parkinson, K.; Lieb, N...
AI summary The text cites references to energy efficiency evaluation protocols and reports, including the Uniform Methods Project's residential lighting evaluation and a net-to-gross evaluation draft report. These documents provide methodologies for assessing energy savings and program effectiveness.
Table 10: Evaluation Questions - Summary Table. Asked and Answered for Program Year 2024 General Questions to Ask of Energy Efficiency Program Evaluations 1 Does the independent evaluator have control over methods and measurement approache...
AI summary The summary table evaluates the energy efficiency program for 2024, assessing whether the independent evaluator has control over methods and measurement approaches, transparency in evaluation, use of technical resources, and the inclusion of market evolution in reporting. Most criteria are met, though some areas require improvement in transparency and market evolution reporting.
XV. Appendix 3: Statistical vs. Practical Significance Statistical significance is a measure of the probability that a result in an analysis could have occurred by chance alone, out of many (theoretical) repetitions of a test. It can be re...
AI summary The text distinguishes between statistical significance (probability of results occurring by chance) and practical significance (real-world relevance). It argues that large samples can produce statistically significant results that lack practical value, emphasizing the need to prioritize practical significance in program evaluation, particularly in energy savings contexts.
Disclaimer: These summaries were generated by AI from the filings they describe. We take care to make them accurate, but errors are possible - and they aren't advice. Only the filings themselves are the record: if you're relying on something here, confirm it against the source documents or the Nova Scotia Energy Board's own record. Full disclaimer →