Topic:"Demand Side Management" in M10830

EXECUTIVE SUMMARY EfficiencyOne (E1) delivers demand side management (DSM) programs that offer benefits to customers and the electric utility. While cost-effective DSM is a key resource option for delivering clean, affordable, reliable, an...

AI summary EfficiencyOne (E1) analyzes demand side management (DSM) programs' rate and bill impacts, highlighting that while DSM may increase rates, it typically reduces customer bills. Equity concerns arise as non-participants face higher rates. E1's 2022 Rate and Bill Impact Analysis (RBIA) evaluates DSM impacts from 2011-2021 and projects outcomes until 2039, emphasizing the balance between rate increases and bill reductions.

1. INTRODUCTION EfficiencyOne (E1) files a historical Rate and Bill Impact Analysis (RBIA) by October 31st of each year.[2](#page-8-1) The purpose of E1's Historical RBIA is to provide insight into the rate and bill impacts resulting from...

AI summary EfficiencyOne (E1) submitted a Historical Rate and Bill Impact Analysis (RBIA) analyzing Demand Side Management (DSM) impacts from 2011 to 2025, comparing scenarios with and without DSM. The analysis examines ratepayer groups and estimates impacts until 2039.

2. UPDATE ON MODEL EVOLUTION - E1 filed its 2021 RBIA Report with the NSUARB on November 1, 2021. In response to requests by - Synapse and Resource Insight, Inc. (RI), to increase transparency in the NS Power rate analysis, - NS Power inco...

AI summary E1 submitted RBIA reports in 2021 and 2022, incorporating model updates like transfer tables, cost allocation summaries, and demand response (DR) programs. The 2023-2025 DSM Plan introduced DR, leading to model refinements by Elenchus to include fractional measure life calculations, improving accuracy in DSM impact assessments.

2.1 AVOIDED COSTS The 2022 RBIA used the following avoided costs. All values are nominal. There have been no changes to avoided costs since the 2023-2025 DSM Plan RBIA. - Energy : Updated avoided costs of energy from the recent NS Power 20...

AI summary The 2022 RBIA incorporated avoided costs from the NS Power 2020 Integrated Resource Plan, specifically the Actual Annual avoided costs of energy as calculated for the IRP Reference Plan (scenario 2.0C), provided to the DSMAG in August 2021. No changes to avoided costs have occurred since the 2023-2025 DSM Plan RBIA.

- used the Fitted Series Planning Reserve Margin (PRM) adjusted stream of avoided costs of - capacity, as calculated by NS Power for the IRP Reference Plan (Scenario 2.0C) and provided to - the DSMAG on August 20, 2021 for the E1 RBIA. The...

AI summary The text discusses the use of the Fitted Series Planning Reserve Margin (PRM) adjusted stream of avoided costs of capacity, calculated by NS Power for the IRP Reference Plan (Scenario 2.0C) and provided to the DSMAG on August 20, 2021 for the E1 RBIA, with details in Table 2.

- and distributed to the DSMAG on May 22, 2021. The calculated values are presented as a - snapshot in time for the year 2021. E1 applied a 2 percent inflation rate to this starting point to

AI summary The document discusses the distribution of calculated values to the DSMAG on May 22, 2021, with a 2 percent inflation rate applied to the starting point for the year 2021.

Table 4: Federal Carbon Pollution Pricing Benchmark Values Used for This Analysis Year Federal Carbon Pollution Pricing Benchmark ($/tonne) 2020 $30 2021 $40 2022 $50 2023 $65 2024 $80 2025 $95 2026 $110 2027 $125 2028 $140 2029 $155 2030...

AI summary The text presents Table 4, which outlines the Federal Carbon Pollution Pricing Benchmark values from 2020 to 2030. These values are used to calculate the avoided costs of carbon emissions from Demand Side Management (DSM) initiatives, using the DICE methodology. The avoided cost of carbon per MWh saved by DSM is determined by multiplying the benchmark by savings intensity.

- on a comparison between the IRP Scenario 2.0C with Base-DSM, and with No-DSM, shown in 6,

AI summary The text references a comparison between IRP Scenario 2.0C with Base-DSM and No-DSM, as shown in figure 6, highlighting the impact of demand-side management on the integrated resource plan.

4 Table 7: Full Range of Avoided Cost Values Used for This Analysis Category Years Details 2011-2014 • 79 $/kW-yr • 2009 IRP refresh (levelized over 2010-2032) Capacity 2015-2022 • 197 $/kW-yr • 2014 IRP, Base DSM scenario (levelized over...

AI summary Table 7 presents avoided cost values for capacity, transmission, distribution, energy, and carbon across different time periods. Values are based on studies like the 2009 and 2014 IRP, and calculations provided by NS Power for the DSMAG. Carbon costs are based on federal trajectories and emissions intensity.

3.1 SCENARIOS - E1's RBIA model compares two scenarios: a DSM scenario and a no-DSM scenario. The DSM scenario includes the actual utility costs and resulting energy and system-peak demand reductions of DSM programs that ran from 2011 thro...

AI summary E1's RBIA model compares a DSM scenario (including 2011-2021 DSM program costs and savings, plus 2022-2025 projections) with a no-DSM scenario. Rate impacts reflect year-to-year differences between scenarios, not actual rate increases. A 1% rate impact in 2025 indicates a 1% variance between DSM and no-DSM rates for that year, not a 1% increase from 2024 to 2025.

3.3 TIME PERIOD DEFINITIONS - In this analysis, - The DSM delivery period is the timeframe over which DSM programs are delivered. The DSM delivery period is 2011-2025. - The cost recovery period is the timeframe over which DSM program cost...

AI summary The document defines three time periods: DSM delivery (2011-2025), cost recovery (2011-2025 with 2015 costs deferred and amortized over eight years), and study (2011-2039). These periods govern DSM program delivery, cost recovery, and impact modeling, respectively.

3.4 PROGRAMS Since the entire portfolio of electricity DSM programs impacts future rates and bills, the analysis includes all DSM programs that are funded by NS Power and for which costs are recovered from electricity system ratepayers.

AI summary The analysis includes all electricity DSM programs funded by NS Power, as these programs impact future rates and bills. Costs are recovered from electricity system ratepayers, emphasizing the significance of DSM programs in the regulatory proceeding.

3.5 CALCULATING RATE IMPACTS - Using the RBIA approach implemented for the first time for the 2020 RBIA, rate impacts are now - calculated in NS Power's Historical Rate Model (Appendix F, filed electronically) to reflect NS - Power's Cost...

AI summary The document outlines the methodology used in NS Power's Historical Rate Model to calculate rate impacts using the RBIA approach. It highlights the integration of DSM energy and demand impacts into a single rate and the exclusion of customer charges in certain model outputs. The RBIA isolates the effects of DSM on rates by comparing DSM and no-DSM scenarios.

Non-participant consumption and bill impacts - In the DSM scenario, non-participants in DSM programs are assumed to use the same amount of - energy as they do in the no-DSM scenario. Their bill impacts are therefore driven only by changes...

AI summary Non-participants in DSM programs experience bill impacts solely from rate changes under the with-DSM scenario, not energy use. Fixed customer charges cause percentage bill impacts to differ from rate impacts. This analysis highlights the role of fixed charges in shaping bill outcomes for non-participants.

Participant consumption and bill impacts For the DSM scenario, within each rate class, in each year, total annual savings (i.e. current-year savings plus persistent savings from past years) are divided equally amongst the cumulative number...

AI summary The DSM scenario calculates annual savings by equally distributing total savings across all participants in each rate class, assuming uniform energy and peak demand reductions. This approach averages savings and uses with-DSM rates to estimate average bill impacts, though real-world participation depth varies.

Total customer consumption and bill impacts The output graphs include a third category of participants, called Total Customers. Impacts for this category are determined by allocating DSM savings for the class equally among all customers in...

AI summary The text explains that impacts for Total Customers are calculated by allocating DSM savings equally among all customers in the class, using average savings and with-DSM rates to estimate bill impacts without distinguishing participants and non-participants.

Cumulative and annual participation Each year, E1 combines participant records (for programs that track participant information) with participant records from previous years. In this way, E1 can identify the first year that a customer part...

AI summary E1 tracks cumulative and annual participation by combining records and using transaction data and scaling factors. For some programs, Guidehouse's ProCESS model is used, while others rely on 2021 data scaled by energy savings and product rebates. Custom Incentives use different assumptions.

3.8 DEMAND RESPONSE - This section discusses how demand response has been incorporated into the E1 RBIA model and - NS Power Rate Model. - Demand Response costs, savings, measure life, and customer incentives are first calculated and - pro...

AI summary Demand response is integrated into the E1 RBIA model and NS Power Rate Model, with costs and savings calculated separately from energy efficiency. Scenarios include combinations of DSM, energy efficiency, and demand response. Demand response programs are assumed to shift consumption without energy savings, targeting peak demand reduction.

3.9 TRANSFER TABLES - As part of the 2021 RBIA, the "Transfer Function & Cost Factor" tab was added to NS Power's - Rate Model to allow stakeholders to explore new DSM scenarios, or to better understand how - changes in one rate class will...

AI summary The 2021 RBIA introduced a 'Transfer Function & Cost Factor' tab in NS Power's Rate Model to analyze DSM scenarios and assess cross-rate-class impacts. The model compares 'DSM Benchmark' (with DSM) and 'DSM Simulated' (no DSM) scenarios, allowing users to input historic or simulated data for cost, participant, and savings analysis by rate class.

4. 2022 ANALYSIS RESULTS - Results are summarized in Appendix A and have been presented for energy efficiency and - demand response separately, as well as combined. Summary sheets for rate, bill, and - participation impacts for each applic...

AI summary The 2022 analysis results summarize energy efficiency and demand response outcomes separately and combined, with rate, bill, and participation impact summaries in Appendix B. Sensitivity analysis results are detailed in Appendix C, using representative model outputs.

4.1 OVERALL RATE IMPACTS - DSM can lower rates by avoiding different types of electricity system costs (avoided energy, - capacity, transmission and distribution, and carbon costs). DSM may also increase rates, a result - of recovering pro...

AI summary Demand Side Management (DSM) can lower or increase electricity rates depending on avoided costs versus program expenses. The 2022 RBIA analysis shows average rate impacts ranging from +0.2% to +3.0% over 2011-2039, with lower impacts in 2022 compared to 2021 due to incorporated carbon costs. Post-2025, rate impacts are projected to range from -1.5% to +0.1%.

Figure 2: Average Rate Impacts (2011-2039) as a Result of DSM Activities in 2011-2025 - [Figure 3](#page-29-0) illustrates the annual rate effects (difference between the no-DSM scenario and the DSM - scenario for each year), assuming that...

AI summary Figure 2 and Figure 3 analyze average rate impacts from 2011-2039 due to DSM activities, highlighting that annual rate changes are influenced by DSM cost recovery and avoided cost fluctuations. The annual impacts in Figure 3 are clarified as not reflecting actual customer rate changes experienced.

Figure 3: Annual Rate Impacts as a Result of DSM Activities in 2011-2025 NS Power's RBIA Pricing Methodology (Appendix E) discusses the generic COSS results, including why there are different rate impacts over time and why rate impacts dif...

AI summary The document discusses the impact of Demand Side Management (DSM) activities on annual rates from 2011 to 2025. It explains how different rate classes experience varying benefits from DSM, with those bearing higher fuel costs seeing greater savings. The analysis also highlights methodological simplifications, such as assuming uniform measure lifespans, which may not reflect real-world variability.

15 Table 8: Average Rate Impact - 2021 Historical to 2022 Historical Results Comparison 2021 Historical RBIA Result (average rate impact over 2011- 2022 (average rate Historical RBIA Result impact over 2011- Rate Class 2038) 2039) (cents/k...

AI summary Table 8 compares the average rate impact of 2021 and 2022 historical results, showing the rate class impacts in cents per kWh and percentages. The Large Industrial class shows a negative average rate impact in cents/kWh but a positive percentage impact, which is an anomaly due to the long-term averaging over 29 years. Figure 4 contextualizes DSM rate impacts from 2011-2025 alongside other assumed rate impacts, noting an 83% increase in residential rates due to non-DSM factors.

Figure 4: Rates with and without 2011-2025 DSM for three classes

AI summary Figure 4 compares electricity rates with and without Demand Side Management (DSM) programs from 2011-2025 for three customer classes, illustrating the financial impact of DSM on rate structures over a 14-year period.

4.2 OVERALL BILL IMPACTS - Generally speaking, those ratepayers that participate in DSM programs most directly benefit - from DSM programs by reducing their electricity consumption and thereby lowering their - electricity bills. Together,...

AI summary The 2022 RBIA analysis shows DSM programs reduce electricity bills for participants by -10.2% to -1.9%, while non-participants see minor savings or increases (-0.03% to +2.4%). Total customer bill impacts range from -8.9% to -1.9%, with $2.5 billion in savings for Nova Scotia ratepayers over 2011-2039. Lower-consumption classes benefit more from efficiency measures.

Figure 5: Average Bill Impact (2011 – 2039) as a Result of DSM Activities in 2011-2025 When examining non-participant bill impacts, it is important to note the broad reach of E1's point-of-sale rebate program components, Instant Savings an...

AI summary The text discusses the impact of E1's rebate programs (Instant Savings and BER-IR) on non-participant and participant bill savings. It highlights that participation rates are high across customer classes, making non-participant scenarios rare. Non-participant results represent minimum savings, while participant results reflect average savings, with some participants achieving higher savings.

4.4.8 MUNICIPAL - As modelled, the Municipal class includes Rate Code 24 only. - The average rate impact over the study period is an increase of 0.9 percent, or 0.08 cents/kWh. ↑ 0.9% Rates ↓ 1.9% Average Bills - Municipal utilities see an...

AI summary The Municipal class includes Rate Code 24, with a 0.9% rate increase and 1.9% average bill decrease over the study period. Participation in E1 programs leads to matching bill impacts for participants and total customers, though individual participation isn't modeled. See Table 7 for details.

5. CONCLUSION - Highlights from the 2022 RBIA analysis include: - Over the 29 years of the study period, participants in DSM programs see average annual bill reductions ranging from a low of 1.9 percent (typical Municipal participant) to a...

AI summary The 2022 RBIA analysis highlights significant electricity bill savings for Nova Scotian ratepayers due to DSM programs, with non-participants experiencing mixed rate impacts. Collaboration with DSMAG and NS Power enhanced RBIA models, incorporating demand response and carbon avoidance. Over 29 years, DSM programs reduced bills by 1.9–10.2% for participants, while rate pressures ranged from 0.2–3.1%.

2022 Rate and Bill Impact Analysis

AI summary The 2022 Rate and Bill Impact Analysis document outlines regulatory proceedings related to utility rate structures and customer bill impacts. Key focus areas include demand-side management, cost of service studies, and regulated business investment applications, with references to various programs and initiatives aimed at energy efficiency and carbon emission reductions.

2022 Rate and Bill Impact Analysis ine# Rate and Bill Impa cts of DSN /I on the R esidential Class 1 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 203...

AI summary The 2022 Rate and Bill Impact Analysis outlines incremental and cumulative Demand Side Management (DSM) savings, expenditures, and participant numbers over multiple years. The data shows fluctuations in DSM savings, expenditures, and participant growth, with a focus on energy efficiency and cost metrics.

This graph shows estimated rate impacts of DSM, relative to the no-DSM scenario. 22 25 27 28 39 42 This graph shows bill impacts of DSM as percentage differences relative to the no-DSM scenario. 'Participants' represents a customer with av...

AI summary The text discusses the estimated rate and bill impacts of Demand Side Management (DSM) programs compared to a no-DSM scenario. Graphs illustrate the differences in rates and bills for participants, non-participants, and total customers, highlighting the financial effects of DSM on energy use.

ne# Rate and Bill Impacts of DSM on the Small General Class 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 Units Incremental DSM Savings 10.6...

AI summary This table presents the rate and bill impacts of Demand Side Management (DSM) on the Small General Class over multiple years, including incremental and cumulative DSM savings, expenditures, number of participants, and the levelized cost of saved energy. The data spans from 2011 to 2039 and provides insights into the financial and programmatic aspects of DSM implementation.

This graph shows estimated rate impacts of DSM, relative to the no-DSM scenario. This graph shows bill impacts of DSM as percentage differences relative to the no-DSM scenario. 'Participants' represents a customer with average energy use a...

AI summary The text includes graphs illustrating the estimated rate and bill impacts of Demand Side Management (DSM) compared to a no-DSM scenario, with different customer groups analyzed. The date filed is 31 October 2022.

Appendix B: Results by Rate Class ne# Rate and Bill Impacts of DSM on the General Class 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 Units...

AI summary This table presents the rate and bill impacts of Demand Side Management (DSM) on the General Class over multiple years, including incremental and cumulative DSM savings, expenditures, number of participants, and the levelized cost of saved energy. The data shows fluctuations in savings and expenditures from 2011 to 2039.

This graph shows estimated rate impacts of DSM, relative to the no-DSM scenario. This graph shows bill impacts of DSM as percentage differences relative to the no-DSM scenario. 'Participants' represents a customer with average energy use a...

AI summary The text discusses the estimated rate impacts of Demand Side Management (DSM) relative to a no-DSM scenario, illustrated through graphs showing bill impacts as percentage differences and absolute terms for participants, non-participants, and total customers.

ne# Rate and Bill Impacts of DSM on the Large General Class 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 Units Incremental DSM Savings 1.9...

AI summary This table presents the rate and bill impacts of Demand Side Management (DSM) on the Large General Class from 2011 to 2039. It includes incremental and cumulative DSM savings, expenditures, number of participants, and the levelized cost of saved energy over time.

This graph shows estimated rate impacts of DSM, relative to the no-DSM scenario. 21 27 This graph shows bill impacts of DSM as percentage differences relative to the no-DSM scenario. 'Participants' represents a customer with average energy...

AI summary This section presents graphs illustrating the estimated rate and bill impacts of Demand Side Management (DSM) programs compared to a no-DSM scenario, highlighting differences between participants, non-participants, and total customers.

This graph shows estimated rate impacts of DSM, relative to the no-DSM scenario. This graph shows bill impacts of DSM as percentage differences relative to the no-DSM scenario. 'Participants' represents a customer with average energy use a...

AI summary The text discusses the estimated rate impacts of Demand Side Management (DSM) compared to a no-DSM scenario, highlighting differences in bill impacts for participants, non-participants, and total customers. Graphs are used to illustrate these impacts.

Line# Rate and Bill Impacts of DSM on the Medium Industrial Class 1 2011 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 2037 2038 2039 Units 2 Incremental DSM Sa...

AI summary The text presents a table analyzing the rate and bill impacts of Demand Side Management (DSM) on the medium industrial class over multiple years, showing incremental and cumulative DSM savings, expenditures, participant numbers, and the levelized cost of saved energy.

This graph shows estimated rate impacts of DSM, relative to the no-DSM scenario. This graph shows bill impacts of DSM as percentage differences relative to the no-DSM scenario. 'Participants' represents a customer with average energy use a...

AI summary The document contains multiple graphs illustrating the estimated rate and bill impacts of Demand Side Management (DSM) relative to a no-DSM scenario. These graphs compare participants, non-participants, and total customers, highlighting the differences in energy use and savings. The final page includes a date filed (31 October 2022) and indicates the end of the document.

Figure 1: Avoided Costs Sensitivity Analysis: Average Rate Impacts (2011 – 2039)

AI summary Figure 1 presents a sensitivity analysis of avoided costs and their impact on average rates from 2011 to 2039. It examines how variations in demand-side management (DSM) and other factors influence rate structures, reflecting key considerations in regulatory proceedings related to energy efficiency and cost allocation.

Figure 2: Avoided Costs Sensitivity Analysis: Average Participant Bill Impacts (2011 – 2039)

AI summary Figure 2 presents a sensitivity analysis of avoided costs and their impact on average participant bills from 2011 to 2039. The analysis evaluates how variations in demand-side management (DSM) programs and other factors influence electricity costs over time.

Figure 3: Avoided Costs Sensitivity Analysis: Average Non-Participant Bill Impacts (2011 – 2039)

AI summary Figure 3 presents a sensitivity analysis of avoided costs on average non-participant electricity bills from 2011 to 2039. It evaluates impacts under different scenarios, focusing on demand-side management (DSM) and related programs, including carbon emission differences and energy rebate initiatives.

Appendix D: Assumptions

AI summary Appendix D outlines key assumptions for a Nova Scotia regulatory proceeding, referencing acronyms related to energy management, cost studies, and regulatory applications. It provides context for terms like DSM, COSS, and RBIA, which are central to the proceeding's analysis.

2022 Rate and Bill Impact Analysis 2022 Rate and Bill Impact Analysis Appendix D: Assumptions This document is intended to provide an overview of the assumptions used in EfficiencyOne's (E1) 2022 Rate and Bill Impact Analysis (RBIA). Gener...

AI summary EfficiencyOne's 2022 Rate and Bill Impact Analysis (RBIA) uses Synapse's 'snapshot' approach, analyzing 2011-2025 DSM programs in DSM and no-DSM scenarios. It includes multiple rate classes beyond Synapse's recommendations, excluding classes where E1 does not offer programs.

Energy and demand savings by class E1 uses evaluated and verified energy and system-peak demand savings for 2011-2021 DSM program years, which are allocated to rate classes within each program component. For 2022- 2025, first-year energy,...

AI summary The text outlines methods for allocating energy and demand savings by rate class for Nova Scotia's DSM programs. It details the use of evaluated savings data from 2011-2021 and proportional allocation methods for 2022-2025, with weighted-average measure lives (WAMLs) calculated based on lifetime and first-year energy savings ratios.

Participation counts by class Participation estimates used in the RBIA model are different than participation estimates used in development of DSM plans, since the RBIA tracks participating accounts , rather than the number of products sol...

AI summary The document explains how the RBIA model estimates participation by tracking unique accounts across programs and years, differing from DSM plans that track products. It uses historical data from E1 and customer records for 2011-2021, and projects 2022-2025 participation using factors based on energy savings and product rebates per GWh.

Residential Behaviour participation Home Energy Report (2013-2016) Customers receiving the Home Energy Report were modelled as new participants in 2013. The same cross-participation rates used for Residential Instant Savings are used for t...

AI summary The Home Energy Report (2013-2016) used cross-participation rates similar to Residential Instant Savings, assuming no impact on other DSM program participation. The program ended in 2015 but had residual access until 2016. E1's 2023-2025 DSM Plan introduces a separate Residential Behaviour program tracked independently due to uncertainty around cross-participation and re-participation, enabling clearer stakeholder analysis of its impacts.

Energy and demand rates - NS Power provided estimates for 2011 2022 of rates by class (including energy, demand, and - customer charges). Beyond 2022, energy and demand charges are assumed to escalate at 2.7% - per year, while customer cha...

AI summary NS Power provided rate estimates from 2011-2022, assuming 2.7% annual escalation for energy/demand charges post-2022. The 2020 RBIA model uses a blended energy/demand rate, whereas prior models excluded demand charges. E1's current model assumes equal energy/demand savings, which may slightly affect participant/non-participant bill impacts but not total customer impacts.

1 Energy and demand sales - 2 NS Power has provided historical and projected energy and demand sales within each rate class - 3 for 2011 2040. Energy sales are provided at the customer's meter for both the with DSM and - 4 without DSM scen...

AI summary NS Power has presented historical and projected energy and demand sales data from 2011 to 2040, differentiated by rate class and including scenarios with and without Demand Side Management (DSM). The data includes energy sales at the customer meter and average monthly demand forecasts under the DSM scenario.

6 Avoided Costs - 7 Avoided costs are calculated at the system level using evaluated DSM savings and avoided cost - 8 rates in four categories: generation, transmission, distribution, and energy. In addition, avoided - 9 cost of carbon was...

AI summary Avoided costs are calculated system-wide using DSM savings and rates for generation, transmission, distribution, and energy. A With Carbon sensitivity analysis also incorporates avoided carbon costs.

11 Table 1: Full range of avoided cost values used for this analysis CATEGORY YEARS DETAILS Capacity ($/kW-yr) 2011 - 2014 79 $/kW-yr 2009 IRP refresh (levelized over 2010-2032) 2015 – 2022 197 $/kW-yr 2014 IRP, Base DSM scenario (levelize...

AI summary The document presents Table 1, which outlines the range of avoided cost values used for analysis, including capacity, transmission, distribution, energy, and carbon costs from 2011 to 2040. These values are derived from various Integrated Resource Plans (IRPs) and adjusted for inflation and sensitivity analysis.

19 Calculation of rate impacts 20 Rate impacts are calculated in NS Power's Rate Model and used as inputs within E1's RBIA model. - Forecast Unit Revenue (c/kWh) is made up of the following components (presented in the 'NSP - Input' tab):...

AI summary Rate impacts are calculated using NS Power's Rate Model and E1's RBIA model. Forecast Unit Revenue includes components with and without DSM, with rate effects applied to energy rates and customer charges remaining unchanged in both scenarios.

Calculation of bill impacts - Bill impacts are calculated in three categories: Participants, Non-Participants, and Total - Customers. - Non-Participants are assumed to use the same amount of energy in the DSM scenario as they do - in the n...

AI summary Bill impacts are categorized into Participants, Non-Participants, and Total Customers. Non-Participants' bills are affected only by rate changes, while Participants consume less energy due to DSM. Total Customers combines both groups to show overall class rate and bill effects.

Methodology for determination of changes in NS Power's base cost rates as a result of DSM-induced changes in class usage and total system costs November 27, 2020

AI summary The document outlines a methodology to assess how Demand Side Management (DSM) initiatives impact NS Power's base cost rates by analyzing changes in class usage and total system costs. It emphasizes regulatory considerations for adjusting rates based on DSM-induced shifts in energy consumption patterns.

1.0. Introduction In an effort to more precisely and accurately align EfficiencyOne's (E1) RBIA Model with the methodological process used by NS Power in setting of its base cost rates, all rate setting functionality from E1's RBIA model h...

AI summary EfficiencyOne's (E1) RBIA model has had its rate-setting functionality removed, with NS Power now using its COSS methodology. NS Power will provide annual inputs to E1's RBIA model under 'With DSM' and 'No DSM' scenarios from 2011 to 2035, including revenue forecasts, demand forecasts, and customer data. NS Power assumes responsibility for cost allocation methods and data inputs.

Revenue Requirement Ordinarily, the base cost rate setting process used in rate case applications requires a great amount of detailed cost inputs to determine revenue requirement. Annual rate base data needs to be collected on a variety of...

AI summary The Revenue Requirement for the RBIA focuses on DSM Program impacts, avoiding detailed cost analysis. Unlike standard rate cases, RBIA only considers DSM-induced avoided costs, keeping other factors constant. This simplifies the process by omitting detailed inputs like plant-in-service or operating expenses.

Cost of Service Studies COSS provides the most insight into class cost causation as based on changes in its energy and demand usage. It shows in a transparent way how rate class usage of demand and energy services within each functional ar...

AI summary COSS provides transparency on how energy and demand usage by rate classes affect total service costs. Accurate tracking of DSM impacts on system and class usage is achievable via NS Power's annual Load Forecast Report and E1's long-term class usage forecasts, enabling simplified COSS analysis without detailed future investment data.

Conclusions Bypassing the detailed COSS ratemaking step, which is intended to show how DSM-induced, cost causative changes in usage affects rates will produce misleading results and create difficulties in interpretation. Any such rate anal...

AI summary Bypassing the detailed COSS ratemaking process leads to misleading rate analyses by failing to account for reallocation of embedded system costs due to DSM-induced usage changes. A simplified COSS approach would provide clearer insights into how DSM affects class-specific costs and rates.

3.0. Applied Approach The relative changes in rates due to DSM are determined by conducting two separate rate setting analyses under the "With DSM" and "No DSM" scenarios. The rate setting process under each scenario is broken out by two s...

AI summary The analysis compares rate changes under 'With DSM' and 'No DSM' scenarios by separating FAM-related and non-FAM-related costs. This approach evaluates DSM's impact on rate structures through distinct cost determination processes.

3.1 Revenue Requirement The annual revenue requirements under the "With DSM" scenario are kept consistent with the test year information from the preceding rate cases. The non-FAM costs in the years following the 2014 test year from the 20...

AI summary The document outlines revenue requirements under 'With DSM' and 'No DSM' scenarios, adjusting costs for inflation and DSM impact. FAM-related costs are based on test year data, with post-2022 adjustments for load changes and inflation. Non-FAM costs remain constant until 2022. The 'No DSM' scenario adds incremental load effects to the 'With DSM' case. Historic FAM cost true-ups are excluded due to minimal impact, lack of rigor, and complexity.

3.2.1 Functionalization of System Costs As indicated in the Revenue Requirement section above, NS Power has used the test year revenue requirements, already functionalized by the four areas, from the historic rate cases. In the "With DSM"...

AI summary NS Power calculates revenue requirements by functionalizing system costs, adjusting for load changes and inflation. In the 'With DSM' scenario, FAM-related costs are modified for load changes and inflation, while non-FAM costs remain flat. The 'No DSM' case adjusts revenue requirements for load differences due to absent DSM. True-up adjustments, like Maritime Link depreciation, slightly affect cost comparisons between scenarios.

3.2.2 Classification of System Costs Costs within each area are classified into appropriate services. Generation and transmission costs are classified into energy and demand. Distribution costs are classified between demand and customer. R...

AI summary System costs are classified into energy, demand, and customer categories. Generation costs split between energy (baseload, non-dispatchable) and demand (peaking units). Transmission costs align with system load factors. Distribution and retail costs remain static except for inflation. NS Power uses a linear equation to estimate generation cost classification for RBIA, based on simulated 2014 COSS data.

3.2.3 Allocation of Costs to Rate Classes Annual cost requirements within each service of each functional area are apportioned to rate classes based on class share in the underlying usage both in the "With DSM" and "No DSM" case.

AI summary Annual costs are allocated to rate classes based on usage in both 'With DSM' and 'No DSM' scenarios, reflecting class share in underlying usage for each service and functional area.

FAM-related Costs The FAM-related costs are allocated to rate classes using the following two-step process: Annual class energy usage is multiplied by the benchmark unit cost $/MWh Date Filed: 31 October 2022 Page 7 of 16 - o In the "With...

AI summary FAM-related costs are allocated using a two-step process involving benchmark unit costs from 'With DSM' and 'No DSM' cases, scaled to match annual FAM revenue. The method does not differentiate between energy- and demand-related costs, a limitation NS Power acknowledges due to outdated models. Demand-related costs now account for 15% of FAM total, necessitating future RBIA updates.

Non-FAM related Costs The non-FAM-related costs are allocated to rate classes using the following two-step process: - Annual class usages of energy and demand services are multiplied by benchmark $/MWh and $/MW unit costs, respectively - o...

AI summary Non-FAM-related costs are allocated to rate classes via a two-step process. Annual class usages are multiplied by benchmark costs from 'With DSM' and 'No DSM' scenarios, then scaled to align with revenue requirements for each service.

DSM Costs The annual DSM-related costs incurred by individual rate classes, as provided by E1, are apportioned to rate classes based on the 25/75 rule. 75 percent of the costs incurred by each class is treated as direct responsibility of e...

AI summary DSM costs are allocated to rate classes using a 25/75 rule, with 75% directly assigned to each class and 25% distributed based on energy and demand usage. Energy costs are apportioned by system generation share, while demand costs use winter peak load factors.

3.2.4 Generic COSS Results The actual results from the above cost allocation process under the "With DSM" and "No DSM" scenarios are presented in the "COSS Outputs" tab within NS Power's rate model, where the long-term trends in annual rel...

AI summary The Generic COSS Results analyze cost allocation trends under 'With DSM' and 'No DSM' scenarios, showing higher unit cost increases in historic periods due to DSM program recovery and declining differentials in later years as DSM measures expire. Large industrial classes benefit more from DSM due to fuel cost reductions, while domestic classes face greater fixed infrastructure cost impacts.

3.3 Unit Revenue Determination For the directional purposes of the RBIA model, it is not considered necessary to develop annual rates with all charges under the "With DSM" and "No DSM" cases. Rather, it is sufficient for NS Power to provid...

AI summary NS Power is using a simplified approach for the RBIA model, providing blended revenues without certain charges for Residential and Small General rate classes. Excluded factors like fuel cost true-ups and smoothing of rates are deemed to have no material effect on the comparison between 'With DSM' and 'No DSM' cases.

Overview of Spreadsheet Calculations

AI summary The document provides an overview of spreadsheet calculations used in a Nova Scotia regulatory proceeding, likely related to energy efficiency programs, cost studies, and demand-side management initiatives. Key entities include regulatory bodies, efficiency programs, and technical acronyms relevant to electricity generation and distribution.

"COSS Data Inputs" tab This tab includes all annual test year class usage and embedded costs from the COSS and BCF COSS filed in GRA and BCF proceedings as well as a forecast of annual usage by class per the most recent ten-year Load Forec...

AI summary The 'COSS Data Inputs' tab compiles annual test year usage and embedded costs from COSS and BCF COSS filings in GRA and BCF proceedings, along with a ten-year Load Forecast Report and DSM expenditures by rate class. These data are used to calculate class unit costs and revenues.

"E1 Data Inputs" tab This tab includes information provided to NS Power by E1 on DSM Program measures and avoided unit costs, all of which are used in determination of class unit costs and revenues.

AI summary The 'E1 Data Inputs' tab details data provided by E1 to NS Power regarding Demand Side Management (DSM) program measures and avoided unit costs, which are critical for calculating class unit costs and revenues.

Savings in energy and demand usage by rate class Savings in energy and demand usage arising from DSM programs for each class are tracked in the following class tabs: R-Savings, SG-Savings, G-Savings, LG-savings, SI-Savings, MI-Savings, LI-...

AI summary The document outlines a methodology for tracking energy and demand savings from DSM programs across eight rate classes (R-Savings, SG-Savings, etc.) from 2011 to 2022. Annual savings are calculated using E1's RBIA Reports and adjusted for transmission losses based on COSS data. This approach converts generator-level metrics to customer-metered usage.

Changes in total Revenue Requirement

AI summary Analysis of changes in total revenue requirement, focusing on cost of service studies (COSS) and regulated business investment applications (RBIA). Key considerations include demand-side management (DSM), efficiency programs, and regulatory proceedings impacting Nova Scotia's energy sector.

"Total-Savings" tab The "Total-Savings" tab provides a sum of annual class savings in energy and demand usage at the generator's gate and customer's meter. In addition, class demand savings at the high side of the bulk power substation are...

AI summary The 'Total-Savings' tab calculates annual energy and demand savings at the generator's gate, customer's meter, and bulk power substation. These savings determine avoided fuel, generation, transmission, and distribution costs. FAM-related costs use unit avoided fuel costs multiplied by energy savings, while non-FAM costs use avoided infrastructure costs multiplied by demand savings.

Cost of Service Studies Apportionment of costs to rate classes is done separately for the "With DSM" and "No DSM" cases" in the tabs bearing the same names.

AI summary The document describes the separate apportionment of costs to rate classes under 'With DSM' and 'No DSM' scenarios, as organized in tabs with corresponding names.

"With DSM" tab The "With DSM" tab provides annual cost allocation to rate classes based on long-term usage as included in NS Power's most recent Annual ten-year Load Forecast Report. This usage already reflects inclusion of DSM Program eff...

AI summary The 'With DSM' tab outlines annual cost allocation to rate classes based on NS Power's load forecast, incorporating DSM Program effects. FAM costs are adjusted from 2023-2035 using a two-step process involving blended unit costs and scaling to match total FAM costs, calculated via a formula considering previous year costs and energy requirement changes.

"No DSM" tab The "No DSM" tab provides annual cost allocation to rate classes absent DSM. The FAM-related costs in years 2011–2035 are calculated using the following process: - Annual FAM costs for each class are calculated by multiplying...

AI summary The 'No DSM' tab calculates annual costs without Demand Side Management (DSM) by using FAM costs, scaling them across rate classes, and applying a formula involving the 'With DSM' case and energy requirement deltas. The process includes pre- and post-external effect adjustments and references the 'Total' column in the 'After External Effect' table.

Comments The applied process is a simplification of a more elaborate cost allocation process where some FAM costs, such as fuel costs, are allocated to rate classes based on their shares in monthly energy requirements; some other FAM costs...

AI summary The text details a cost allocation process for FAM (Fixed Allocation Method) and non-FAM costs, distinguishing allocation methods based on energy requirements, load factors, and DSM impacts. It references the COSS (Cost of Service Study) for load factor calculations and describes adjustments for inflation from 2023–2035. Annual unit costs are derived by dividing total costs by energy requirements.

"COSS Var" tab "COSS Var" provides differentials between cell values in the "No DSM" and "With DSM" tabs. Please note that the data layouts in the "No DSM" and "With DSM" tabs are identical with the exception for the treatment of DSM costs...

AI summary The 'COSS Var' tab compares data between 'No DSM' and 'With DSM' scenarios in a Cost of Service Study. The layouts are identical except for DSM cost exclusions in the 'No DSM' case, highlighting differences in cost calculations under varying demand-side management approaches.

"COSS Outputs" tab The "COSS Outputs" tab provides two sets of bar graphs of percentage change in class rates due to DSM over the period 2011–2035 calculated as either arithmetic or load-weighted rate changes. The graphs within each set ar...

AI summary The 'COSS Outputs' tab presents bar graphs analyzing percentage changes in class rates due to Demand Side Management (DSM) from 2011–2035, using arithmetic or load-weighted methods. It breaks down effects on unit base cost revenues and includes a control panel to test inflation and avoided cost scenarios on unit costs and revenues.

"NSPI Inputs into RBIA" tab "NSPI Inputs into RBIA" provides pricing inputs requested by E1. It includes the following annual class data in years 201-2035 broken out by "With DSM" and "No DSM" scenarios: - Forecast Unit Revenues Before DSM...

AI summary NSPI provides pricing inputs for the RBIA, including annual data from 2021-2035 under 'With DSM' and 'No DSM' scenarios. Data includes revenues, program charges, sales forecasts, demand, and customer counts. Filed 31 October 2022.

2022 Rate and Bill Analysis

AI summary Analysis of 2022 rate and bill data for Nova Scotia, involving regulatory considerations for demand-side management, cost of service studies, and efficiency programs. Key entities include Nova Scotia Power Inc., Efficiency Nova Scotia Corporation, and related regulatory frameworks.

2022 RBIA Report The RBIA assesses how Demand Side management (DSM) affects NS Power's rates and its customers' bills. The model was designed by EOne and its consultant, Elenchus Research Associates, on a framework provided by Board Counse...

AI summary The 2022 RBIA Report evaluates the impact of DSM programs on NS Power's rates and customer bills. It shows that DSM participation leads to reduced energy consumption and bill savings for participants, while non-participants face higher bills. The report estimates over $2.5 billion in savings for customers, with significant rate changes observed across different customer classes.

Table 1 Results for 2011-2039[1](#page-2-0) Customer Class DSM Participant Bill Impact DSM Non-participant Bill Impact Energy Rate Impact Difference between DSM and no-DSM ₵/kWh Proportion Residential - 5.0% 1.6% 0.318 2.08% Small General...

AI summary The table presents the bill impact of demand-side management (DSM) participation across various customer classes from 2011 to 2039. DSM participants experience lower bill impacts compared to non-participants, with the largest differences seen in small general and residential classes. A sensitivity analysis was conducted on avoided costs, with a greater impact observed on commercial customer bills, though no detailed analysis was provided in the report.

Participant Comments Synapse noted three primary changes to the 2022 RBIA: the incorporation of the avoided costs of carbon; the inclusion of demand response activities; and the use of enhanced measure of life assumptions. Synapse consider...

AI summary Synapse highlights updates to the 2022 RBIA, including carbon cost incorporation and demand response, noting lower rate increases due to carbon savings. They recommend enhancing DSM modeling transparency and integrating green energy plans. The Consumer Advocate supports reducing RBIA frequency, citing limited impact on program design.

EOne Response In response to Synapse's comments about the rate classes with higher rate increases, EOne stated that it seeks to maximize participation to provide bill savings from DSM to offset rate impacts and that it will work towards th...

AI summary EOne responds to Synapse's comments by supporting the inclusion of a 'no-DSM' case in the 2020 IRP Update and engaging DSMAG. It emphasizes DSM's role in offsetting rate increases through participation and program design, agrees to refine the RBIA model, and cites NS Power's IRP modeling practices comparing DSM with other clean energy resources.

Conclusion The Board accepts the 2022 RBIA report as filed and acknowledges improvements in the model that were achieved through collaborative work by stakeholders who participated in the DSMAG. The avoided cost of carbon is a new stream o...

AI summary The Board accepts the 2022 RBIA report, acknowledging stakeholder collaboration and improvements like incorporating avoided carbon costs, leading to lower rate increases and higher bill savings. Synapse requested a no-DSM scenario and DSM integration with clean energy planning, which EOne and NS Power partially addressed. The Board directed NS Power to enhance IRP scenarios and model transparency, with EOne committing to continuous model improvements and a change log.

James R. Gogan Direct +1 (902) 563 5920 [[email protected]](mailto:[email protected]) 292 Charlotte Street Suite 300 Sydney NS Canada B1P 1C7 Tel +1 (902) 563 1000 Fax +1 (902) 563 1113 Our File: 217200 October 31,...

AI summary EfficiencyOne submits its 2022 Rate and Bill Impact Analysis (RBIA) to the Nova Scotia Utility and Review Board, requesting electronic filing of Excel models. It also proposes altering future RBIA filings as part of its 2023-2025 DSM Resource Plan application.

RBIA Filings In its application for approval of the 2023-2025 DSM Resource Plan, E1 proposed to alter its annual filing of the historical RBIA. EfficiencyOne stated in its Application 1 : Currently, E1 files a historical RBIA on, or before...

AI summary EfficiencyOne (E1) proposes altering its annual historical RBIA filing as part of its 2023-2025 DSM Resource Plan application. The historical RBIA estimates long-term rate impacts of DSM activities and is a Performance Indicator (PI) under the Supply Agreements. A forward-looking RBIA accompanies DSM Plan Applications to assess future rate impacts.

e 2 217200 October 31, 2022 The Supply Agreement defines them as: …….. management tools that provide information to allow an organization to take action to help it deliver on performance targets. The preparation and development of the hist...

AI summary EfficiencyOne (E1) proposes eliminating annual historical Rate and Bill Impact Analysis (RBIA) filings except during Demand Side Management (DSM) Plan Application years, citing cost savings and limited stakeholder utility. The Board approved the 2023-2025 DSM Plan, which includes filing a historical-looking RBIA as part of the 2026-2028 DSM Plan Application. Intervenors did not oppose this change.

December 15, 2022 Crystal Henwood Regulatory Affairs Officer/Clerk of the Board Nova Scotia Utility and Review Board 3rd Floor 1601 Lower Water Street Halifax, Nova Scotia B3J 3S3 RE: M10830 – EfficiencyOne - 2022 Rate and Bill Impact Anal...

AI summary Synapse Energy Economics comments on EfficiencyOne's 2022 Rate and Bill Impact Analysis (R&BIA), noting lower rate increases due to avoided carbon costs and higher bill savings. They highlight discrepancies between rate class impacts and advocate for maximizing participation in high-impact classes. The R&BIA will be filed less frequently, focusing on forward-looking analyses.

Avoided costs We continue to assert that a "no DSM" case is necessary for accurate R&BIA modeling. NSPI is in the process of updating the 2020 IRP to reflect the impacts of recently adopted legislation and other changes. As part of the upd...

AI summary The document asserts the necessity of a 'no DSM' case for accurate R&BIA modeling. NSPI is updating the 2020 IRP to reflect new legislation and requests a 'no DSM' scenario excluding energy efficiency and demand response. It also seeks DSMAG's involvement in IRP updates and future development.

Cost of carbon We emphasize the need for discussion and analysis of the impacts of the adoption of Act 57 on DSM and other clean energy investment planning. We also note that DSM planning needs to be integrated with the planning for other...

AI summary The text emphasizes the need to analyze Act 57's impact on Demand Side Management (DSM) and clean energy planning, advocating for integration between DSM and other clean energy resources. It requests Nova Scotia Power Inc. (NSPI) to provide data comparing DSM costs with other clean energy resources to the DSM Advisory Group (DSMAG).

Demand response Synapse reviewed the analysis of impacts of demand response. While we did not find specific issues based on this review, we are not aware of other jurisdictions addressing demand response in an R&BIA or of any best practice...

AI summary Synapse reviewed demand response impacts and found no specific issues but noted a lack of other jurisdictions' practices in R&BIA. They recommend E1 monitor methodologies elsewhere.

Model transparency We did not find any calculation or formula errors in our review of the R&BIA model. Synapse appreciates the improvements made over last year's model and recommends E1 continue to increase the model's transparency in the...

AI summary Synapse found no errors in the R&BIA model but recommends improving transparency. Two key recommendations include clarifying energy savings in the Total Savings tab and documenting formula changes. The current model's base case (full DSM) causes counterintuitive results in the demand response scenario, which should be addressed by adjusting the base case or displaying savings as negative. Documentation of model updates is also emphasized for stakeholder clarity.

December 15, 2022 VIA EMAIL 30924 Ms. Crystal Henwood Regulatory Affairs Officer/Clerk Nova Scotia Utility and Review Board 1601 Lower Water Street, 3rd Floor Halifax NS B3J 3S3 Dear Ms. Henwood: Re: M10830 – EfficiencyOne – 2022 Rate and...

AI summary The Consumer Advocate, with Green Energy Economics, supports EfficiencyOne's proposal to provide RBIA reports only when filing new DSM plans, arguing annual reports have limited value for program design or budgets.

2. E1 REPLY TO STAKEHOLDER WRITTEN COMMENTS - E1's reply to the Stakeholder Comments is separated into the issues noted by participants in this - matter as follows: - 2022 RBIA changes and results - Future RBIA reporting - Avoided costs -...

AI summary E1 addresses stakeholder comments on 2022 RBIA changes, future reporting, avoided costs, carbon cost modeling, and demand response. An error in Appendix A's Excel file was corrected, leading to revised demand response rate impacts.

3. 2022 RBIA CHANGES AND RESULTS - Synapse noted that E1 made three changes to the 2022 historical RBIA which were first included - in the forward-looking RBIA for the 2023-2025 DSM Plan. The changes were: DATE FILED: January 19, 2023 Page...

AI summary In 2022, E1 updated the RBIA by including avoided carbon costs, demand response, and precise measure life assumptions. Synapse noted lower rate increases compared to 2021 due to carbon cost inclusion, citing reasonable increases and higher bill savings. E1 emphasizes maximizing participation to offset rate impacts through DSM initiatives.

4. FUTURE RBIA REPORTING Both Synapse and the CA acknowledged E1's stated intention to file the next historical RBIA in conjunction with future DSM Plans. Synapse commented, "It is important to note that this is the last historical R&BIA t...

AI summary Synapse and the Consumer Advocate (CA) acknowledge EfficiencyOne's (E1) plan to file future historical RBIA reports only with new DSM Plans, reducing annual filings. Synapse emphasizes this is the last historical report for several years, while the CA supports less frequent reporting, citing limited impact on program design. E1 endorses this approach and seeks stakeholder input on RBIA reporting frameworks.

5. AVOIDED COSTS - Synapse asserted that, "a "no DSM" case is necessary for accurate R&BIA modeling. NSPI is in the - process of updating the 2020 IRP to reflect the impacts of recently adopted legislation and other - changes. As part of t...

AI summary Synapse argues a 'no DSM' case is essential for accurate R&BIA modeling, requesting NSPI updates to the 2020 IRP and DSMAG involvement. NS Power states it will analyze DSM scenarios and calculate avoided costs post-Evergreen IRP, not within its scope. E1 supports Synapse's request for a 'no-DSM' case and DSMAG engagement.

6. COST OF CARBON - Synapse stated, "We emphasize the need for discussion and analysis of the impacts of the - adoption of Act 57 on DSM and other clean energy investment planning. We also note that DSM - planning needs to be integrated wi...

AI summary Synapse emphasizes the need to integrate DSM planning with other clean energy resources and requests data from NSPI. NS Power responds that their IRP process already integrates DSM, citing the 2020 IRP and Evergreen modeling. E1 supports the integration approach. The discussion centers on clean energy resource planning and data transparency.

7. MODELING OF DEMAND RESPONSE RESOURCES - Synapse commented, "While we did not find specific issues based on this review, we are not - aware of other jurisdictions addressing demand response in an R&BIA or of any best practices in - that...

AI summary Synapse noted a lack of best practices for incorporating demand response into R&BIA, urging E1 to monitor methodologies. E1 collaborated with Elenchus to include demand response in the 2023-2025 DSM Plan and plans to refine approaches in future reports.

8. MODEL TRANSPARENCY - Synapse stated, "Synapse appreciates the improvements made over last year's model and - recommends E1 continue to increase the model's transparency in the years to come. We have - two specific recommendations toward...

AI summary Synapse recommends improving model transparency by clarifying energy savings in the Total Savings tab and documenting formula changes. E1 responds that the model is accurate, scenarios can be compared in the RBIA model, and will explore adding a change log. The NS Power rate model serves as an intermediary for scenario comparisons.

2022 RBIA Report The RBIA assesses how Demand Side management (DSM) affects NS Power's rates and its customers' bills. The model was designed by EOne and its consultant, Elenchus Research Associates, on a framework provided by Board Counse...

AI summary The 2022 RBIA Report evaluates how Demand Side Management (DSM) affects NS Power's rates and customer bills. It highlights the model's revision based on feedback from the DSMAG and includes avoided carbon costs and demand response activities. The analysis shows that DSM participants experience bill reductions, while non-participants face increases, with the Small General class seeing the largest changes.

Table 1 Results for 2011-2039[1](#page-2-0) Customer Class DSM Participant Bill Impact DSM Non-participant Bill Impact Energy Rate Impact Difference between DSM and no-DSM ₵/kWh Proportion Residential - 5.0% 1.6% 0.318 2.08% Small General...

AI summary The table shows the bill impact of DSM participation across different customer classes, with residential and small general classes showing the largest negative impacts. A sensitivity analysis was conducted on avoided costs, showing greater effects on commercial customers. No detailed analysis was provided in the report.

Participant Comments Synapse noted three primary changes to the 2022 RBIA: the incorporation of the avoided costs of carbon; the inclusion of demand response activities; and the use of enhanced measure of life assumptions. Synapse consider...

AI summary Synapse highlights three changes to the 2022 RBIA: carbon avoided costs, demand response inclusion, and improved life assumptions. They note lower rate increases due to carbon costs and recommend improving participation in high-rate classes. Synapse advocates for a no-DSM scenario, DSM integration with clean energy, and model transparency. The CA supports reducing RBIA frequency and finds the report useful for DSM spending evaluation.

EOne Response In response to Synapse's comments about the rate classes with higher rate increases, EOne stated that it seeks to maximize participation to provide bill savings from DSM to offset rate impacts and that it will work towards th...

AI summary EOne supports Synapse's requests to include a 'no-DSM' case in the 2020 IRP Update and engage DSMAG on IRP development. It emphasizes DSM's role in offsetting rate increases through customer engagement and program design. EOne agrees to refine the RBIA model, clarify scenarios, and align with NS Power on DSM comparisons with clean energy resources. It also aligns with Synapse and the CA on reducing historical RBIA filings.

Conclusion The Board accepts the 2022 RBIA report as filed and acknowledges improvements in the model that were achieved through collaborative work by stakeholders who participated in the DSMAG. The avoided cost of carbon is a new stream o...

AI summary The Board accepts the 2022 RBIA report, noting improvements from stakeholder collaboration, including EOne's integration of avoided carbon costs leading to lower rate increases. Synapse requested a no-DSM scenario and clean energy integration, which EOne supported. The Board directed NS Power to enhance IRP scenarios and model transparency, with EOne committing to continuous improvements and a change log for models.