Topic:"Residential Demand Response Program" in M12186

5 The New Residential program, featuring the New Home Construction program component, ended on December 31, 2023. The wind-up of the program was outlined in E1's 2023-2025 DSM Plan. 6 Affordable Single-family Home and Mi'kmaw Home Energy E...

AI summary The New Residential program ended on December 31, 2023, as outlined in E1's 2023-2025 DSM Plan. Participation in various programs, such as Affordable Single-family Home and Mi'kmaw Home Energy Efficiency Project, Residential Behaviour, and Demand Response, is defined and fluctuates based on billing cycles and participation metrics.

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 evaluation parameters. A comprehensive impact evaluation is a full impact evaluation 2 involving review of baselines, methodologies, values, and net-to-gross-ratios. Instant 3 Savings, Efficient Product Installation, Affordable Multi-f...

AI summary The 2024 evaluation activities include comprehensive impact evaluations for programs like Instant Savings, Efficient Product Installation, and Residential Demand Response, along with condensed evaluations for others. Market and process evaluations were also conducted to assess program effectiveness and market conditions.

Program Components - The Residential Demand Response program component aims to help facilitate a more flexible residential load that provides residential customers with economic incentives and more visibility and control of their loads. E1...

AI summary The document outlines two demand response programs: Residential and BNI (Business, Non-Profit, Institutional). E1 implements pathways like hot water load control, smart thermostats, EV telematics, and battery control (2024/2025). BNI programs aim for non-residential flexibility via aggregators, standalone batteries, and solar PV integration. Both programs offer economic incentives and load visibility.

Demand Response Residential Highlights - The Residential Demand Response program component achieved 0.1 MW of available capacity for the 2023/2024 season, through the Eco Shift pilot. Two eligible devices (smart thermostats, EV telematics...

AI summary The Residential Demand Response program achieved 0.1 MW of available capacity in 2023/2024, below the 0.2 MW mid-course adjustment. Key factors include preheating implementation issues and E1 finalizing its capacity methodology. The pilot involved 353 participants with 1,257 smart thermostats and 50 EV devices, with 10 demand response events triggered by NS Power.

DEMAND RESPONSE (2024) - o Not all registered devices participated in each event as registration was ongoing throughout the season, participants could opt out of any event, and device connectivity issues meant that not all enrolled partici...

AI summary The 2023/2024 Demand Response season faced challenges with device participation due to ongoing registration, opt-outs, and connectivity issues. Post-season efforts focused on recruiting for the 2024/2025 season, including expanding eligible devices, installing smart thermostats, and resuming domestic hot water controller installations after a 2023 pause due to quality concerns. 803 controllers were installed in 2024.

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.

Residential Demand Response › Tracked results were not fully compiled, as multiple methodologies for establishing the available DR capacity of the measures included in 2024 were being considered. The Evaluator decided on the final methodol...

AI summary The 2024 evaluation of residential demand response (DR) programs faced delays due to unresolved methodologies for measuring DR capacity. The Evaluator finalized the methodology as part of the 2024 evaluation, resulting in the absence of tracked results or realization rates for the program component.

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.

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.

Residential DR Findings and Recommendations This subsection presents the key findings and recommendations from the Residential DR evaluation. 2024 Res DR-Finding: In 2024, Residential DR new and total available DR capacities both amounted...

AI summary The 2024 Residential DR evaluation found underperformance in achieving planned DR capacity (0.057 MW vs. 0.210 MW). Mysa thermostats dominated (83% of devices), but preheating errors reduced capacity. Whole-house data regression models were used for baseline calculations, with plans to refine unitary savings metrics. A 2025 recommendation calls for re-analyzing Eco Shift Pilot data to improve accuracy.

1 Residential DR Overview This section describes the Residential DR program component, follows up on past evaluation recommendations, and provides an overview of Residential DR participation history.

AI summary This section outlines the Residential Demand Response (DR) program, addresses past evaluation recommendations, and reviews participation history. It emphasizes program evolution and historical engagement data.

Table 5: Eco Shift Pilot 2023-2024 Event Summary Event # Date Start Time Duration (Hours) Outdoor Temperature at Event Start (°C) 1 01-09-2024 6 p.m. 2 -5 2 01-16-2024 8 a.m. 2 -4 3 01-19-2024 5 p.m. 3 -5 4 01-24-2024 7 a.m. 4 -13 5 01-31-...

AI summary Table 5 outlines the Eco Shift Pilot 2023-2024 events with details including dates, times, durations, and outdoor temperatures. It also defines terms related to residential demand response, distinguishing between enrolled and participating devices.

Figure 1: Overview of Residential DR Participation, 2024 Since participants continued to enroll throughout the season and they could opt out of any event, not all enrolled devices participated in each event. [Table](#page-2-0) 7 below pres...

AI summary The text discusses residential demand response (DR) participation in 2024, noting that not all enrolled devices participated in each event due to opt-outs and connectivity issues. The number of enrolled devices is referenced in Table 7, and participation details are covered in Subsection 3.2.1.

Note on Margins of Error For evaluation activities that yield quantitative results based on a sample, the Evaluator typically aimed to achieve a maximum margin of error of 10% at a confidence level of 90%. This means that, if measurements...

AI summary The evaluation of quantitative results in the Residential DR program aimed for a 10% margin of error at 90% confidence. Despite small sample sizes and complex load profile estimations, statistically significant results were ensured. Margins of error for unitary and per-event DR capacities are detailed, with examples in Appendix II of the 2024 DSM Programs Evaluation Executive Summary.

3.2 Demand Response Capacity For Residential DR, the metric is the available DR capacity that corresponds to the load reduction made available for peak demand events in participant homes. For the Eco Shift Pilot pathway, the Evaluator esta...

AI summary The document discusses residential demand response (DR) capacity metrics, noting that the Eco Shift Pilot pathway used a unitary DR capacity value multiplied by participating thermostats. While new and total capacities are reported separately, they are equivalent in the first year. However, low EV participation in 2024 prevented establishing a unitary DR capacity for that category.

4 Residential DR Key Findings and Recommendations As mentioned previously, the main objective of the 2024 Residential DR evaluation was as follows: › Calculate Residential DR results, namely new and total available DR capacities This secti...

AI summary The 2024 Residential DR evaluation found that targets were unmet, with 0.057 MW achieved versus 0.210 MW planned. Mysa thermostats dominated (83% of devices), but preheating errors reduced capacity. A regression model using whole-house data calculated DR capacity, and a 2025 Eco Shift Pilot data analysis is recommended to improve accuracy.

Demand Response Appendix I Residential DR: Tracking Sheet Audit Appendix II Residential DR: Detailed Metering Data Analysis Methodology Appendix III Residential DR: Regression Coefficients Appendix IV Residential DR: Event Day Graphs of Ex...

AI summary The document outlines appendices for residential and BNI (Business, Non-profit, and Institutional) Demand Response (DR) programs, including audit tracking sheets, metering data analysis, regression coefficients, load graphs, and 2024 recommendations. EfficiencyOne is referenced in an image caption.

APPENDIX II Residential DR: Detailed Metering Data Analysis Methodology This appendix summarizes the methodology used by the Evaluator to establish the available DR capacity as part of the 2024 evaluation of Residential DR. For the Eco Shi...

AI summary The appendix outlines the methodology for evaluating residential demand response (DR) capacity using Mysa thermostats. The Evaluator used whole-house consumption data from advanced metering infrastructure (AMI) to compare expected and actual hourly loads during events, calculating a unitary available DR capacity per thermostat.

APPENDIX III Residential DR: Regression Coefficients Hour of Week Baseload (𝜷𝑫,𝑯) HDD Coefficient (𝜶𝑫,𝑯) 1_00 0.595 0.0882 1_01 0.532 0.0830 1_02 0.661 0.0756 1_03 0.397 0.0907 1_04 0.390 0.0930 1_05 0.425 0.0996 1_06 0.535 0.1066 1_07 0.6...

AI summary This appendix presents regression coefficients for residential demand response (DR) programs, detailing baseload and HDD coefficients for various hours of the week. These coefficients are used to model energy consumption patterns and inform demand-side management strategies.

Residential DR: Event Day Graphs of Expected Vs Actual Loads 0 5 10 15 20 25 0 0.5 1 1.5 2 2.5 3 3.5 4 0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15 16 17 18 19 20 21 22 23 Load (kW) Hour of Day Event Hour Tag Expected Load (kW) Actual Load (kW) H...

AI summary The document presents event day graphs comparing expected versus actual residential demand response (DR) loads, highlighting discrepancies between projected and real-world energy consumption during specific events. Visual data illustrates load (kW) by hour of day, including HDD15 metrics, to evaluate DR program performance.

This appendix summarizes all the recommendations made by the Evaluator as part of the 2024 evaluation of Residential DR. Section Recommendations Executive Summary 2024 Res DR Recommendation 1: Gather and analyze the Eco Shift Pilot data ag...

AI summary This appendix summarizes the Evaluator's 2024 recommendations for the Residential Demand Response (DR) evaluation, including a recommendation to re-analyze the Eco Shift Pilot data in 2025 to improve DR capacity value accuracy and consistency.

(10) Smart Thermostats for Electrical Heating Systems

AI summary The section titled 'Smart Thermostats for Electrical Heating Systems' likely discusses the role and implementation of smart thermostats in electrical heating systems within a regulatory context in Nova Scotia.

Available DR Capacity The unitary available DR capacity for domestic water heater load controls is based on the metering data analysis results from the 2023 Residential Demand Response evaluation. During the 2021-2022 and 2022- 2023 heatin...

AI summary The available DR capacity for domestic water heater load controls is based on 2023 evaluation data showing an average 385 W demand reduction per unit during the first two hours of events, collected by E1 during 2021-2023 heating seasons.

(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 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.

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.

N. Demand Response (DR) There are two demand response programs, Residential Demand Response and Business-Nonprofit-Institutional (BNI) Demand Response. Demand response concerns capacity (Watts, kW, MW, GW) rather than energy (kWh, GWh). Th...

AI summary The document outlines Nova Scotia's Demand Response (DR) programs, distinguishing between Residential and BNI (Business-Nonprofit-Institutional) DR. DR focuses on capacity reduction during peak periods, with 353 residential and 76 BNI participants in 2024. The Evaluator defines DR as load reduction events triggered by Nova Scotia Power to manage capacity, not energy consumption.

1. Residential Demand Response (Eco Shift Pilot Pathway) For Residential Demand Response (DR), Efficiency Nova Scotia created a tracking sheet. The Residential DR tracking sheet is limited to a spreadsheet with participant raw thermostat a...

AI summary Efficiency Nova Scotia's Residential Demand Response program uses a tracking sheet with thermostat and consumption data, limited to Mysa thermostats due to data issues. A regression model predicts energy use based on time and temperature, analyzing 199 participants. The Evaluator recommends repeating the 2025 analysis for accuracy and consistency.

ding Energy Information Systems and Performance Monitoring Tools, 2014-2016 Assessment of Automated M&V Methods, Summary of Work [(http://eis.lbl.gov/auto-mv.html)](http://eis.lbl.gov/auto-mv.html). Morse, William L. & H. Gil Peach, "Contr...

AI summary The text lists references to energy efficiency studies, evaluation protocols, and publications, including works on automated measurement and verification (M&V) methods, residential lighting evaluation, smart thermostat protocols, and diffusion of innovations. Key entities include NREL and the Uniform Methods Project (UMP), with topics centered on energy management systems, evaluation methodologies, and behavioral efficiency programs.