Topic:"Rate Design" in M12932

June 30, 2026 Crystal Henwood Clerk of the Board Nova Scotia Energy Board 1601 Lower Water Street, 3rd Floor Halifax, NS B3J 3S3 Re: Time-Varying Pricing Pilot Program – Year Four (2024/25) Evaluation Report Dear Ms. Henwood: Nova Scotia P...

AI summary Nova Scotia Power Inc. submits the Time-Varying Pricing Pilot Program Year Four (2024/25) Evaluation Report, which includes results from the 2024/25 season and an update on outstanding directives and Consensus Agreement commitments as per Board directive M12499.

Background The TVP Pilot Program was developed by NS Power with the assistance of Brattle Group and stakeholder input in M09777. The Pilot, testing Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs across the Domestic, Small Genera...

AI summary The TVP Pilot Program, developed by NS Power with stakeholder input, was approved by the Board in 2021. The program includes TOU and CPP tariffs, with extensions and updates, including a 2024 Consensus Agreement. Following a 2025 cybersecurity incident, NS Power requested an extension for the Year Four EM&V report, which was approved by the NSEB.

Summary of Year Four Evaluation Results The Year 4 Report is the first EM&V conducted internally by NS Power. Overall, the findings indicate that the TVP Pilot continues to achieve peak load reductions in response to time‑varying price sig...

AI summary The Year 4 Evaluation of the Time-Varying Pricing (TVP) Pilot shows continued peak load reductions, especially in residential and commercial sectors. Participation has grown, and the report highlights statistically significant load shifting for commercial tariffs. NS Power faced delays due to a cyber incident and has requested further extensions for filing the report. The evaluation was conducted internally with advisory support from Econoler and includes stakeholder input and appendices with detailed findings.

Stakeholder Engagement and 2026/27 Work Plan During the 2024/25 TVP Season, NS Power undertook stakeholder engagement as part of its ongoing pricing innovation framework, consistent with the 2024 Consensus Agreement, including consultation...

AI summary NS Power engaged stakeholders during the 2024/25 TVP Season as part of its pricing innovation framework, consistent with the 2024 Consensus Agreement. Engagement was paused due to a cyber incident but resumed with a kick-off session on June 16, 2026, and future sessions are planned.

Update on the 2026/27 Season As outlined in the Cybersecurity Incident Monthly Updates (M12273), NS Power expects all systems required for the administration of the TVP Tariffs to be restored in time for the 2026/27 TVP Season – beginning...

AI summary NS Power expects to restore TVP systems in time for the 2026/27 season, resuming approved rates without modifications. The company will not actively recruit new customers initially and will prioritize communication with existing participants to ensure confidence in the program.

Conclusion The Year Four Report ( Appendix A ) provides evaluated results for the 2024/25 Season, including sustained residential load shifting, statistically significant commercial load shifting, and initial results for the MURB TOU Tarif...

AI summary The Year Four Report evaluates the 2024/25 Season, highlighting residential and commercial load shifting results and initial MURB TOU Tariff outcomes. Econoler's review supports NS Power's methodology. The report includes survey data, marketing activities, and stakeholder session materials. NS Power plans to resume TVP Pilot rates for the 2026/27 Season, per the Board-approved framework.

Regulatory Counsel 11 The Year Five Report will only include evaluated results for the MURB TOU Tariff, as other TVP tariffs were temporarily suspended during the 2025/26 Season. Summary of Deliverable / Commitment Detail & Context Source...

AI summary The Year Five Report will focus on the MURB TOU Tariff, with other TVP tariffs suspended. Deliverables include evaluating the MURB TOU Tariff metrics, refining the tariff to reflect load shifting value, refining load reduction estimation methods, and exploring TVP revenue stability mechanisms.

& lt;sup>1 "M11822 Directive" refers to the 2024/25 TVP Application proceeding, "M11823 Directive/Commitment" refers to the 2023/24 (Year Three) Evaluation Report proceeding, "2024 Consensus Agreement" refers to the 2024 TVP Consensus Agre...

AI summary The text provides references to various regulatory proceedings, including the 2024/25 TVP Application proceeding, the 2023/24 Evaluation Report proceeding, the 2024 TVP Consensus Agreement, and the Smart Grid Nova Scotia Final Report proceeding.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to Review of accessibility as applicable to vulnerable customers (i.e. low-income) Examine the results of the Year 3 report as it rela...

AI summary The text outlines several deliverables and commitments related to accessibility for vulnerable customers, metering and billing system capabilities, and the evaluation of demand charge impacts on participation in time-varying pricing (TVP) programs. NS Power is tasked with addressing gaps in income analysis, assessing impacts on low-income customers, and evaluating the demand charge as a barrier to participation in TVP for General Service customers.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to Evaluate the level of costs that are truly driven by an individual's non-coincident demands Synapse recommends that NS Power evalua...

AI summary The document outlines several commitments and recommendations related to demand charges, time-varying pricing (TVP), and tariff structures. Key points include evaluating non-coincident demand costs, modeling demand charge changes for commercial customers, assessing TVP's alignment with avoided costs, and proposing a weekend-inclusive TOU tariff for stakeholder review.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to sessions then file the EM&V metrics when NS Power is prepared to add the new tariff NS Power agreed with Synapse's recommendation t...

AI summary The document outlines several commitments and actions related to the Time-Varying Pricing (TVP) Pilot Program, including the development of a weekend-inclusive TOU tariff, review of system planning values, and discussions on seasonally adjusted default rates. NS Power is directed to provide draft tariffs and metrics for evaluation, and future technical sessions are planned to address various aspects of TVP.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to to charge from, and discharge to, the grid with behind-the-meter energy storage (including vehicle-to-grid) that is not integrated...

AI summary The deliverable involves evaluating use cases for behind-the-meter energy storage, including vehicle-to-grid, in the context of TVP pricing ratios and net metering, and developing recommendations for appropriate actions.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to File YR4 Report Report on the Year Four findings no later than 31 Jul 2025 File the annual Evaluation, Measurement and Verification...

AI summary The document outlines deliverables for the Year 4 report, including the submission of findings and an EM&V report by July 31, 2025. It also includes commitments by NS Power to analyze system margin forecasts and CPP events and to report on stakeholder engagement related to TVP options for small businesses.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to Report on the review of marketing and communication efforts and its planned changes in the Year 4 Report Synapse recommended NS Pow...

AI summary The document outlines two key deliverables for NS Power's Year 4 Report: a review of marketing and communication efforts and an analysis of commercial class customer characteristics in the TVP pilot. The Board emphasizes the need for NS Power to communicate effectively with customers about bill savings and improve enrollment in peak load reduction programs.

Summary of Deliverable / Commitment Detail & Context Source 1 Initial Due by / Completed on Status Refer to Continue to file annual Evaluation Reports Maintain the established TVP Report and EM&V processes File an annual EM&V repor...

AI summary The document outlines commitments related to the continuation of annual Evaluation Reports and the planning of a MURB Industry Group Session. These efforts aim to support the adoption of TVP rates by MURB customers through incentives and rebates, with a focus on maintaining established processes and engaging stakeholders.

Context This memo summarizes the support provided by Econoler to Nova Scotia Power (NS Power) in the finalization of Time-Varying Pricing (TVP) Pilot Program Phase 4 Evaluation. Econoler was contracted by NS Power to provide advisory suppo...

AI summary Econoler provided advisory support to Nova Scotia Power in evaluating the Time-Varying Pricing (TVP) Pilot Program Phase 4, including a review of methodological changes such as the use of mixed-effect models and robust margins of error. Econoler has previously conducted evaluations for earlier phases of the TVP program.

Conclusion of the Review Econoler provided guidance and clarifications to NS Power to ensure a consistent and appropriate application of the overall evaluation methodology established for TVP Phase 1 to 3. Additionally, based on the discus...

AI summary Econoler provided guidance to NS Power to ensure consistent application of the evaluation methodology for TVP Phases 1 to 3. Econoler confirmed that the methodological changes and justifications provided by NS Power were valid and sound.

Time-Varying Pricing Pilot Program Phase 4 Evaluation, Measurement & Verification Report June 30, 2026

AI summary This document presents an evaluation, measurement, and verification report for Phase 4 of the Time-Varying Pricing Pilot Program, dated June 30, 2026. It provides an analysis of the program's performance and outcomes.

Abbreviations AMI Advanced Metering Infrastructure ANL Adjusted Net Load CPP Critical Peak Pricing DD Difference-in-difference DDD Triple difference-in-differences (Eco Shift) DOM Domestic Rate Class DR Demand Response EM&V Evaluation Meas...

AI summary The text provides a list of abbreviations and their full forms used in the regulatory proceeding. It includes terms related to energy, metering, pricing, and evaluation methodologies.

Definitions The hourly net system requirement (MW) less all wind generation (MW) Cohorts are numbered based on the Phase they enrolled in the TVP program. For example, Cohort 4 refers to participants recruited in Phase 4 (i.e. the fourth W...

AI summary The document defines key terms and metrics used in the regulatory proceeding, including hourly net system requirements, rate classes, energy consumption measurements, and income brackets. It outlines how participants are grouped in the TVP program and explains terminology related to electricity consumption and pilot program methodologies.

Tariffs Both TOU and CPP are available in the Domestic, Small General, and General rate classes, whereas MURB TOU is available to MURBs in the General rate class. A summary of the TVP Tariffs is provided in Attachment [I: Riders and Tariff...

AI summary The document outlines the structure and rates of Time-Varying Pricing (TVP) tariffs in Nova Scotia, including TOU and CPP, for different rate classes. It details peak and off-peak periods, pricing differences, and operational specifics such as event scheduling and notification requirements.

Residential Findings In total, 5,616 TOU and 2,642 CPP residential customers participated in the TVP program in Phase 4. Of these, 4,938 TOU and 2,310 CPP customers were included in the regression when counting only those who meet the crit...

AI summary In Phase 4 of the TVP program, 5,616 TOU and 2,642 CPP residential customers participated, with 4,938 TOU and 2,310 CPP customers included in the regression analysis. Participants achieved significant electricity load reductions during peak periods and events, consistent with Phase 3 findings.

Absolute Load Reduction (kW) Relative Load Reduction (%) TVP Tariff Morning Peak Evening Peak Morning Peak Evening Peak Residential TOU 0.15 kW 0.17 kW 7.4% 7.9% Residential CPP 0.61 kW 0.77 kW 24.6% 28.5% Statistical Significance ✓ ✓ ✓ ✓...

AI summary The table summarizes peak load reductions by residential TVP tariff, showing reductions in both absolute kW and relative percentages for morning and evening peaks. The General SOR Energy Charge has two blocks with different rates for the first 200 kWh per month per kW of maximum demand and additional kWh.

Residential TOU participants reduced load during peak periods (0.16 kW / 7.6%) with minimal snapback (0.014 kW during evenings only) while also reducing overall annual energy (300 kWh per year), resulting in an average annual electricity b...

AI summary Residential TOU participants reduced peak load by 0.16 kW (7.6%) with minimal snapback and annual energy use by 300 kWh, leading to a 5.5% reduction in electricity bills. Participants with smart devices and Eco Shift achieved greater load reduction. Electrification of heating systems also showed significant peak load reduction without increasing annual energy use.

nergy consumption (27.7 ± 37 kWh per year) while still saving on their annual electricity bill ($153 per year) in addition to any fuel savings from non-electric heating sources they may have reduced. Residential CPP participants reduced lo...

AI summary Residential CPP participants reduced load during peak periods and achieved energy savings, with those using electric heating showing the highest load reduction. Electrified participants had significant load reduction during peak hours but no significant change in electricity bills, though they may have saved on other fuels. Load reduction was lower for those with non-electric heating.

Commercial Findings The commercial TVP Tariffs attracted more businesses, with Phase 4 enrolment (108 businesses) higher compared to Phase 3 (65 businesses). While "small sample size and the wide variety of energy consumption profiles prev...

AI summary The commercial TVP Tariffs attracted more businesses, with Phase 4 enrolment higher than Phase 3. Improved regression analysis in Phase 4 enabled a more robust assessment, showing significant electricity load reductions during peak periods for TOU and events for CPP.

MURB TOU Findings Phase 4 marks the first load and economic impacts evaluation of the MURB TOU Pilot Tariff. Ten MURBs were recruited and are enrolled in the MURB TOU Tariff. For the MURB TOU Tariff, this Phase 4 evaluation includes the Wi...

AI summary Phase 4 of the MURB TOU Pilot Tariff evaluated load and economic impacts, showing a 0.48 kW overall load reduction during peak periods, with significant reductions only during evening peak hours. Load increased significantly in March, except during the winter period.

Table 3: Summary of Load Reductions from MURB TOU Tariff TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) Morning Peak Evening Peak Morning Peak Evening Peak MURB TOU 0.44 kW 0.54 kW 1.8% 2.1% Statistical Significance X...

AI summary Table 3 summarizes load reductions from the MURB TOU tariff, showing absolute and relative reductions during morning and evening peaks, with statistical significance indicated for evening peak results.

Introduction Time-Varying Pricing (TVP) is a scalable customer-focused demand response (DR) program. In Nova Scotia, the TVP pilot has grown significantly since it began in November 2021. Since its inception, the TVP pilot has offered two...

AI summary Time-Varying Pricing (TVP) is a demand response program in Nova Scotia that offers customers rate choices to shift electricity usage from peak periods. The TVP pilot, launched in 2021, includes multiple tariffs and rate classes. Phase 4 introduced a new multi-unit residential building (MURB) TOU Pilot Tariff, which is being evaluated as part of the TVP Phase 4 EM&V report.

Table 4: Impact Evaluation Metric Summary Category Metric TOU, CPP, MURB TOU (all rate classes unless specified) • Change in load (kW) during peak, and overall impact during Winter and non-Winter. Mid-peak hours included for MURB TOU. • Ch...

AI summary Table 4 outlines impact evaluation metrics for time-varying pricing (TVP) programs, including changes in load during peak periods, economic impacts on electricity bills, and price elasticity. Metrics are categorized by load and usage impact, and economic impact, with specific considerations for different rate classes and regions.

The TVP pilot program has increased enrolment year over year with a total of 8,376 participants at the end of Phase 4. Refer to [Table 5](#page-36-0) and [Table 6](#page-36-1) for participation summaries.

AI summary The TVP pilot program has seen increased participation, reaching 8,376 participants by the end of Phase 4. Participation summaries can be found in Table 5 and Table 6.

Table 5: TVP Participation on March 31 by Phase and Tariff Phase DOM TOU SMG TOU GEN TOU DOM CPP SMG CPP GEN CPP MURB TOU Total Phase 1 676 24 284 8 0 992 Phase 2 891 17 373 2 0 1,283 Phase 3 2,241 37 19 922 3 6 0 3,228 Phase 4 5,616 37 18...

AI summary Table 5 presents TVP participation by phase and tariff, showing the number of participants in different phases and tariff types. Table 6 provides retention rates for each TVP tariff, with MURB TOU having a 100% retention rate and Domestic TOU having an 87% retention rate.

2.1 Residential TOU & CPP To best evaluate load and billing effects of the TVP pilot, it is important to have a control group with similar load characteristics to that of the treatment group. The control group selection load profile match...

AI summary The analysis compares residential TOU and CPP control and treatment groups, showing a high match accuracy (over 96%) in load profiles. While baseline characteristics like income and housing style are similar, living space and electric space heating penetration differ, contributing to higher energy consumption among TVP customers compared to the general population.

2.2 Commercial TOU & CPP The same methodological approach as used with residential control group (with exception to Neighbourhood Criteria, Heating Classification, and Eco Shift) was used in attempting to select a control group for Small G...

AI summary The analysis of control group selection for Commercial Time-of-Use (TOU) and Commercial and Industrial Program (CPP) rates shows poor matching accuracy for Small General and General TOU/CPP, making them unsuitable. However, MURB TOU shows good match accuracy, allowing for a control group. The methodology used was similar to the residential control group, with some exceptions.

Table 8: Phase 4 CPP Event Reference Day Results Event Day HALIFAX AIRPORT KENTVILLE CDA CS NAPPAN AUTO SHEARWATER RCS SYDNEY AIRPORT TRACADIE WESTERN HEAD YARMOUTH AIRPORT 12/4/2024 12/3/2024 12/3/2024 12/3/2024 12/3/2024 12/3/2024 12/3/2...

AI summary The table presents reference days for Critical Peak Pricing (CPP) events in Nova Scotia across multiple weather stations. For example, the December 4, 2024, CPP event had the same reference day for all locations, while the March 11, 2025, event had different reference days depending on the location. The analysis compares temperature profiles between event and reference days to ensure accurate load forecasting.

3 Residential TOU Tariff Impacts This section presents the analysis results for load and economic impacts of Residential TOU tariffs for all cohorts in Phase 4. The goal of the residential TOU pilot is to encourage customers to shift their...

AI summary This section analyzes the load and economic impacts of residential Time-of-Use (TOU) tariffs in Phase 4. The goal is to encourage customers to shift electricity usage from peak to off-peak periods, reducing energy bills and system costs. Cohort 4 has significantly more participants than previous cohorts, and electric heating systems are more common among participants.

Parameter Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Sample Size 430 190 1,016 3,302 4,938 Heating Type Steady Electric 48% 65% 61% 61% 60% Steady Non-Electric 26% 18% 22% 25% 24% Electrified 22% 11% 11% 9% 10% De-Electrified 4% 6% 6% 5% 6% R...

AI summary Table 9 presents a summary of residential TOU (Time-of-Use) sample sizes across four cohorts, including distribution by heating type and region. The data shows variations in sample sizes and heating type distribution across cohorts, with the majority of participants in Cohort 4 and the highest proportion of steady electric heating in Cohort 2.

3.1 Load & Usage Impacts This section presents and discusses the electrical load impact from the residential TOU Tariff.

AI summary This section discusses the electrical load impact resulting from the residential Time-of-Use (TOU) Tariff, highlighting how it affects residential electricity usage patterns.

3.1.1 Change in Load during Peak Periods [Table 10](#page-49-0) summarizes the results of the analysis for morning and evening TOU peak hours for each cohort and for all cohorts combined. The average load reductions are presented along wit...

AI summary The text discusses load reductions during peak periods for residential Time-Varying Pricing (TOU) participants. It highlights statistically significant load reductions in both morning and evening peak hours, with higher reductions during evenings, particularly in colder months like January and February. The analysis includes average load reductions, margin of error, and relative reductions for different cohorts.

Change in Load by Space Heating Classes during TOU Peak Hours [Table 11](#page-52-0) summarizes the average load reductions during morning and evening TOU peak hours for space heating classes of all cohorts combined in Phase 4. The load re...

AI summary Table 11 shows average load reductions during TOU peak hours for different space heating classes in Phase 4. Participants with steady electric systems had the highest load reductions, while those with non-electric systems had the lowest. Electrification of heating systems also resulted in notable load reductions.

Morning Evening Parameters De - El ec tr ifi ed El ec tr ifi ed El St ec ea tr dy ic No St n- El ea ec dy tr ic De - El ec tr ifi ed El ec tr ifi ed El St ec ea tr dy ic No St n- El ea ec dy tr ic Avg. Load Reduction 0.15 ± 0.07 ± 0.18 ± 0...

AI summary This table presents load reduction data during TOU peak hours in winter for residential participants, categorized by heating class, region, income level, and number of residents per household. It includes average load reduction, standard error, and significance levels for various parameters.

[Figure 15](#page-52-1) illustrates the average load reduction achieved by TOU participants according to the region of premises in Nova Scotia. While no significant difference in load reduction during morning hours is observed between part...

AI summary The text discusses load reduction data from TOU participants in Nova Scotia, noting higher evening load reductions in the Halifax area and higher absolute load reductions among higher-income participants, though no significant overall difference between regions or income levels.

Low-Income Medium-Income High-Income Parameters AM Peak PM Peak All Peak Hours AM Peak PM Peak All Peak Hours AM Peak PM Peak All Peak Hours Avg. Load 0.14 ± 0.15 ± 0.15 0.12 ± 0.16 ± 0.14 0.18 0.19 0.19 (kW) a Reduction 0.01 0.01 ± 0.01 0...

AI summary This table presents load reduction data for low-income, medium-income, and high-income residential TOU participants before a pilot program. It includes average load, load reduction, and relative load reduction percentages, with significance markers for statistical validity.

Change in Load with Eco Shift E1's Eco Shift is a DR initiative offered separately from TVP and was implemented within subset of the TVP treatment participants who opted into both programs. It is designed to encourage load reduction during...

AI summary The analysis evaluates the impact of Eco Shift, a demand response (DR) initiative, on load reduction in conjunction with Time-of-Use (TOU) pricing. Results show that residential TOU participants enrolled in Eco Shift achieved significantly higher load reductions, particularly during Eco Shift DR events, compared to those without Eco Shift participation.

3.1.2 Snapback Effect While the TOU participants exhibit relatively small but statistically significant load increase of 0.014 kW during evening snapback period, they reduced their electricity usage by 0.013 kW during morning snapback hour...

AI summary The TOU participants showed a small but statistically significant increase in load during evening snapback periods and a decrease during morning snapback hours. However, the overall change in load during both periods was statistically insignificant.

Table 13: Snapback Effect for Residential TOU Participants Parameters Load Reduction a (kW) Avg. Significance (p_Value≤0.05) Morning Snapback 0.013 ± 0.004 ✓ Evening Snapback -0.014 ± 0.005 ✓ Overall Snapback -0.002 ± 0.003 X a Positive an...

AI summary Table 13 presents the snapback effect for residential TOU participants, showing load reduction values and their statistical significance. The morning snapback shows a slight reduction, while the evening snapback shows a slight increase in electricity usage, with the overall snapback being statistically insignificant.

3.1.3 Change in Load during Highest ANL Hours [Figure 20](#page-57-0) depicts the distribution of Top 20, 50, and 88 highest ANL hours for residential TOU participants during morning peak, evening peak, and off-peak hours as well as weeken...

AI summary The document analyzes load changes during the highest Adjusted Net Load (ANL) hours for residential Time-of-Use (TOU) participants. Results show statistically significant load reductions, with a 6% relative reduction during TOU peak periods, particularly during morning and evening peak hours on weekdays.

Participants Parameters High nest ANL Ho urs ANL Hours Coincide TOU Peak Periods Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 Avg. Load 0.16 ± 0.04 0.14 ± 0.13 ± 0.17 ± 0.17 ± 0.17 ± Reduction (kW) a 0.16 ± 0.04 0.03 0.02 0.03 0.03 0.02 Avg....

AI summary The table presents load reduction data from participants in a time-varying pricing program, comparing average load and reduction percentages across different participant tiers and time-of-use periods. Statistical significance is noted for some metrics, indicating potential effectiveness of the program.

3.1.4 Change in Usage Table 15 summarizes changes in daily electricity usage level for cohorts 1 to 4 and all cohorts combined during non-holiday weekdays and holiday weekends in Winter. All cohorts exhibit statistically significant reduct...

AI summary Table 15 shows a statistically significant reduction in daily electricity usage across all cohorts during non-holiday weekdays and holiday weekends in Winter. TOU participants showed an average load reduction of 0.6 kWh on holidays and weekends, indicating the effectiveness of time-of-use pricing in reducing energy consumption.

Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Weekdays Avg. Usage Reduction 1.71 ± 2.70 ± 1.64 ± 1.10 ± 1.39 ± a (kWh/day) 0.21 0.31 0.14 0.08 0.06 Avg. Usage – Residential TOU Participants, Pre-Pilot 39.4 50.4 43....

AI summary The text presents a table comparing average usage reduction across different cohorts during winter weekdays, weekends/holidays, and non-winter periods, highlighting the effectiveness of time-of-use (TOU) pricing programs. It indicates statistically significant reductions in energy usage across all cohorts, with varying magnitudes.

[Table 16](#page-60-0) presents changes in daily electricity usage levels by space heating. During non-holiday weekdays in Winter, TOU participants with electrified space heating exhibit insignificant change in their daily usage level. Not...

AI summary Table 16 shows variations in daily electricity usage levels among residential TOU participants based on their space heating type. During non-holiday weekdays, electrified heating systems show no significant change, while de-electrified and steady electric heating systems show reductions. TOU participants with steady non-electric heating systems show mixed changes, but overall savings are statistically significant and amount to 300 kWh annually on average.

Parameters De - El ec tr ifi ed El ec tr ifi ed El St ec ea tr dy ic No St n- El ea ec dy tr ic Winter, Non-Holiday Weekdays a Avg. Usage Reduction(kWh/day) 0.75 ± 0.20 -0.09 ± 0.14 1.96 ± 0.10 0.15 ± 0.07 Avg. Usage – Residential TOU Part...

AI summary The table presents data on average usage reduction during different seasons and days of the week for residential TOU participants. It highlights significant reductions in winter weekdays and non-winter periods, with notable differences observed between households with higher and lower residents-per-household during winter. The data is further segmented by income level, residents-per-household, and region in Figure 21.

3.2 Economic Impacts This section presents and discusses the impact of residential TOU tariffs on the electricity bill as well as price elasticity.

AI summary This section examines the economic impacts of residential Time-of-Use (TOU) tariffs on electricity bills and explores price elasticity related to these tariffs.

3.2.1 Change in Electricity Bills [Table 17](#page-61-2) summarizes the applicable tariffs used for residential TOU impact on billing. Tariff details can be found in [Attachment I: Riders and Tariff Structure.](#page-115-0) Customer Type a...

AI summary The document discusses the change in electricity bills due to the implementation of Time-of-Use (TOU) tariffs for residential customers. Table 17 outlines the applicable tariffs for different customer types and periods, highlighting the shift from the Domestic Standard Tariff to the Domestic TOU Tariff for the Treatment, Pilot group.

[Table 18](#page-62-0) presents the bill impact for residential TOU, where participants exhibit an overall annual average bill saving of $0.30 per day, corresponding to 5.5% of average annual bill. This amount of annual bill saving is stat...

AI summary The table shows that residential TOU participants saved an average of $0.30 per day annually, or 5.5% of their average bill. Non-Winter savings were higher at $1.54 per day, due to lower rates during non-Winter periods. However, during Winter, participants saw an increase of $1.34 per day despite load reductions, due to higher TOU rates during peak hours.

Table 18: Change in Daily Electricity Bill for All Cohorts of Residential TOU Participants Parameters Winter Non- Holiday Weekdays Winter Holiday/ Weekends Winter Overall Non-Winter Annual Average Avg. Bill Savings ($/day) a -2.05 ± 0.01 0...

AI summary Table 18 presents the change in daily electricity bills for residential TOU participants across different time periods and cohorts. It shows average bill savings, relative savings percentages, and significance levels, highlighting mixed results with some periods showing savings and others showing increases.

The analysis reveals that the type of space heating has significant influence on the bill impact for the TOU participants. While TOU participants with all space heating types experienced significant increases in bills during Winter season,...

AI summary The analysis shows that TOU participants with electrified space heating achieve significant annual bill savings of around $153, while all heating types see savings during non-Winter months. However, the study does not account for additional fuel costs or savings from non-electric heating sources.

- & lt;sup>8 TOU rates were 32.12 ¢/kWh during peak hours and 16.931 ¢/kWh during off-peak hours. Table 19: Change in Daily Electricity Bill by Space Heating Type for All Cohorts of Residential TOU Participants Parameters El ec De tr ifi e...

AI summary The document presents data on the impact of Time-of-Use (TOU) rates on residential electricity bills, showing average bill savings and increases across different heating types during winter, non-winter, and annual periods. The results indicate varying levels of savings, with significant statistical significance across all categories.

3.2.2 Price Elasticity Residential TOU participants' responsivity to electricity prices ($/kWh) was evaluated by estimating daily price elasticity during non-holiday weekdays in Winter season, as well as the Inter-period Substitution Price...

AI summary The analysis of residential TOU participants' price elasticity during the winter season shows a daily price elasticity of -1.05 and an inter-period substitution elasticity of -0.14. These values indicate that increases in electricity prices lead to decreased electricity usage and a shift of load from peak to off-peak hours.

4 Residential CPP Tariff Impacts This section presents the analysis results for load and economic impacts of the Domestic CPP Tariff for all cohorts in Phase 4. The goal of the residential CPP pilot is to encourage customers to shift their...

AI summary This section analyzes the load and economic impacts of the Domestic CPP Tariff during Phase 4, which ran from April 1, 2024, to March 31, 2025. The goal is to encourage customers to shift electricity usage during CPP events to non-event periods, reducing system utilization and providing demand response capacity.

4.1 Load & Usage Impacts This section presents and discusses the electrical load impact from the Domestic CPP Tariff.

AI summary This section presents and discusses the electrical load impact from the Domestic CPP Tariff, focusing on how it affects load and usage patterns within the Nova Scotia regulatory proceeding.

Change in Load per Critical Peak Event [Figure 23](#page-68-0)a illustrates the average load reduction (kW) per CPP event date for all Phase 4 cohorts, along the corresponding event-average outdoor temperature (°C). The residential CPP par...

AI summary The document discusses load reduction data from Critical Peak Pricing (CPP) participants in Nova Scotia, showing significant reductions during both morning and evening events, with higher reductions during evenings and in the Halifax Area. Higher-income participants demonstrated greater load reduction percentages compared to lower-income participants.

4.1.3 Change in Load during Highest ANL Hours [Figure 29](#page-73-0) illustrates the distribution of Top 20, 50 and 88 highest ANL hours for residential CPP participants during weekdays and weekends as well as across CPP events. The major...

AI summary The text discusses the distribution of highest ANL (Adjusted Net Load) hours for residential CPP (Critical Peak Pricing) participants during weekdays and weekends, showing that most high load hours occur on weekdays. Load reductions during these periods are statistically significant, with slightly higher reductions during CPP peak periods.

Table 27: Change in Daily Electricity Usage (kWh/day) by Cohort during CPP Events for Residential CPP Participants Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Avg. Usage Reduction a (kWh/day) 1.6 ± 4.0 3.1 ± 6.7 1.6 ± 2.9 1.6 ± 1.5...

AI summary Table 27 presents the change in daily electricity usage (kWh/day) by cohort during Critical Peak Pricing (CPP) events for residential participants. The table shows average usage reductions, pre-pilot usage levels, and relative percentage reductions, with significance indicators for statistical relevance.

The results of the second analysis are summarized in [Table 28](#page-75-0) and show changes in daily electricity usage level for cohorts 1 to 4 and all cohorts combined during non-holiday weekdays and holiday weekends in Winter as well as...

AI summary The analysis shows that residential Critical Peak Pricing (CPP) participants significantly reduced their daily electricity usage during non-holiday weekdays in Winter. Load reductions were observed across all cohorts, though cohort 3's reduction was not statistically significant. Annual aggregated usage reductions for all CPP participants combined are estimated at 355 kWh per year.

Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Weekdays Avg. Usage Reduction a (kWh/day) 3.0 ± 1.4 3.1 ± 2.0 1.0 ± 0.9 1.1 ± 0.5 1.2 ± 0.4 Avg. Usage – Residential CPP Participants, Pre-Pilot (kWh/day) 50.7 60.5 44....

AI summary The table presents data on average usage reduction across different cohorts during winter weekdays, weekends/holidays, and non-winter days. It shows varying levels of reduction, with significance markers indicating statistical significance for most comparisons, except for some non-winter days. The data relates to residential Critical Peak Pricing (CPP) participants before the pilot program.

4.2 Economic Impacts This section presents and discusses the impact of residential CPP tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of residential CPP tariffs on electricity bills and price elasticity, analyzing how these tariffs influence consumer behavior and financial outcomes.

4.2.1 Change in Electricity Bills [Table 30](#page-77-3) summarizes the applicable tariffs used for residential CPP impact on billing. Tariff details can be found in [Attachment I: Riders and Tariff Structure.](#page-115-0)

AI summary This section discusses the impact of residential Critical Peak Pricing (CPP) on electricity bills, referencing Table 30 and Attachment I for tariff details.

Table 30: Tariffs Used for Analyzing Residential CPP Impact on Electricity Bill Customer Type and Period Applicable Tariff Control, Reference Day Domestic Standard Tariff Control, during Pilot Domestic Standard Tariff Treatment, Reference...

AI summary Table 30 outlines the tariffs used for analyzing the impact of residential Critical Peak Pricing (CPP) on electricity bills, comparing Domestic Standard Tariff with Domestic CPP Tariff. Table 31 shows that residential CPP participants achieved significant bill savings, with an overall annual average of $0.57 per day, and higher savings during non-Winter days and weekends/holidays in Winter due to reduced rates during non-peak hours.

The analysis reveals that the type of space heating has a significant effect on the bill savings for the CPP participants. The steady electric participants achieved the highest bill savings compared to steady non-electric. While CPP partic...

AI summary The analysis shows that the type of space heating significantly impacts bill savings for CPP participants. Steady electric heating systems achieved the highest daily and annual bill savings, while electrified customers did not experience statistically significant annual savings. Non-Winter days saw the most savings across all heating types.

Parameters De- Electrified Electrified Steady Electric Steady Non-Electric Winter Avg. Bill Savings ($/day) a 0.36 ± 0.04 -0.47 ± 0.03 $0.56 \pm 0.02$ 0.14 ± 0.01 Avg. Bill – Residential CPP, Pre- Pilot ($/day) 6.3 8.0 10.3 3.4 Relative Av...

AI summary The table presents average bill savings and significance levels for different electrification scenarios (De-Electrified, Electrified, Steady Electric, and Steady Non-Electric) across winter, non-winter, and annual periods, highlighting statistical significance and relative savings percentages.

4.2.2 Price Elasticity Price elasticity was evaluated to measure residential CPP participants' responsivity to electricity prices during Phase 4. Specifically, NS Power evaluated Daily Price Elasticity during Winter season and annual overa...

AI summary The analysis evaluates residential CPP participants' price elasticity during winter, revealing a Daily Price Elasticity of -0.2 and an Inter-period Substitution Price Elasticity of -0.19, both statistically significant, indicating reduced electricity usage in response to price changes.

5 Commercial TOU Tariff Impacts This section presents and discusses the estimated load and economic impacts of the commercial TOU program. The goal of the commercial TOU pilot is to encourage customers to shift their electricity usage from...

AI summary This section discusses the estimated load and economic impacts of the commercial TOU program, aiming to encourage load shifting during peak periods. The pilot uses price differentials based on system savings and infrastructure cost avoidance. Phase 4 has 50 participants, with most enrolled in earlier cohorts.

Parameter Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Sample Size 19 15 12 4 50 Rate Class Small General 9 13 6 4 32 General 10 2 6 0 18 Region HRM 12 3 6 3 24 Rest of Nova Scotia 7 12 6 1 26 Table 33: Summary of Commercial TOU Sample Size[10]...

AI summary Table 33 presents a summary of the commercial Time-of-Use (TOU) sample size, divided into four cohorts with details on sample size, rate class, and region distribution across Nova Scotia.

5.1.1 Change in Load during Peak Periods [Figure 31](#page-81-1) illustrates the load profiles for commercial TOU participants during the pre-pilot and pilot periods, along with the corresponding variation in outdoor temperature during the...

AI summary The analysis shows that commercial TOU participants reduced their electricity load during peak hours by an average of 0.8 kW, with reductions of 6.4%, 8.6%, and 7.4% during morning, evening, and overall peak periods, respectively. The results from the Mixed-Effects regression analysis confirm these impacts are statistically significant.

5.1.2 Snapback Effect NS Power evaluated the snapback effect based on the same method that was applied for load reduction calculation, but specifically for the four hours following the morning and evening peak hours. As summarized in [Tabl...

AI summary NS Power evaluated the snapback effect, finding a statistically significant load reduction during morning snapback hours but a load increase during evening snapback hours. The overall relative load increase across all snapback periods was not statistically significant.

5.1.3 Change in Load during Highest ANL Hours [Figure 34](#page-85-0) depicts the distribution of Top 20, 50 and 88 highest ANL hours for commercial TOU participants during off-peak, morning peak, evening peak, Weekends and Holidays. As se...

AI summary The text discusses the distribution of highest ANL hours for commercial TOU participants, showing that these hours disproportionately occur on weekdays and during peak periods. However, statistical analysis indicates that load changes during these hours are not significant, suggesting limited impact on overall load patterns.

5.1.4 Change in Usage Changes in daily electricity usage were estimated by applying the same method which was used for estimating hourly load-impact, to daily electricity usage. [Table 38](#page-86-3) presents the estimated changes in dail...

AI summary The document discusses the estimation of changes in daily electricity usage for commercial TOU participants using the same method applied for hourly load-impact estimation. Table 38 provides the estimated changes in kWh/day.

5.2 Economic Impacts This section presents and discusses the impact of commercial TOU tariffs on the electricity bill as well as price elasticity. a Positive values represent 'Load Reduction' and Negative values represent 'Load Increase'

AI summary This section discusses the economic impacts of commercial time-of-use (TOU) tariffs on electricity bills and price elasticity, noting that positive values indicate load reduction while negative values indicate load increase.

5.2.1 Change in Electricity Bills The bill impact analysis for the commercial TOU uses the same method that was used for estimating the commercial TOU load impact analysis. In the bill impact analysis, applicable tariffs applied in accorda...

AI summary The bill impact analysis for the commercial time-of-use (TOU) tariff uses the same method as the load impact analysis. Applicable tariffs are determined based on customer type and pilot period, as detailed in Table 39 and Attachment I.

Customer Type Period Applicable Tariff Treatment – General Pre-Pilot General Tariff – Rate Code 11 Treatment – General Pilot General TOU Tariff – Rate Code 83 Treatment – Small General Pre-Pilot Small General Tariff – Rate Code 10 Treatmen...

AI summary The table outlines different customer types and applicable tariffs before and during the pilot period. It also notes that commercial TOU customers experienced a statistically significant increase in their daily electricity bills during the Winter and annually, consistent with increased electricity usage.

Table 40: Change in Daily Electricity Bill for Commercial TOU Participants Parameters Winter Non-Winter Annual Overall Bill Savings ($/day)a Avg. -12.3 ± 3.3 2.2 ± 2.2 -3.8 ± 2.6 Avg. Bill, Commercial TOU Participants, Pre-Pilot ($/day) 28...

AI summary Table 40 presents the change in daily electricity bills for commercial TOU participants, showing average bill savings during winter and annual overall savings, along with statistical significance. Winter savings are negative, indicating an increase, while non-winter savings are positive.

5.2.2 Price Elasticity Daily Price Elasticity reflects the change in overall daily electricity usage caused by changes in the average daily price ($) per kWh. It is expressed as the percent (%) change in the average electricity usage assoc...

AI summary This section explains price elasticity in the context of electricity usage, distinguishing between daily price elasticity and inter-period substitution price elasticity. Daily price elasticity measures changes in usage due to price changes, while inter-period substitution elasticity reflects shifts in load patterns based on peak-to-off-peak price ratios during winter days.

Chapter 5: Commercial TOU Tariff Impacts The results demonstrated a Daily Price Elasticity of 0.13 (± 0.20) during Winter season and -0.21 (± 0.08) annual overall. The daily price elasticity during Winter season may imply that for 1% incre...

AI summary The analysis in Chapter 5 shows that the Daily Price Elasticity during Winter is 0.13 (not statistically significant), while the annual elasticity is -0.21 (statistically significant), indicating reduced usage over time with price increases. The inter-period substitution elasticity of -0.065 suggests load shifting from peak to off-peak periods during Winter due to rate changes.

6 Commercial CPP Tariff Impacts This section presents and discusses the estimated load and economic impacts of the commercial CPP program. The goal of the commercial CPP pilot is to encourage customers to shift their electricity usage from...

AI summary This section discusses the estimated load and economic impacts of the commercial CPP program, which aims to encourage load shifting during peak events to reduce energy costs and infrastructure expenses. The analysis is based on a Mixed-Effects modeling semi-DiD approach and covers CPP events from November 01, 2024, to March 31, 2025.

6.1 Load Impacts This section presents and discusses the electrical load impact from the commercial CPP pilot.

AI summary This section presents and discusses the electrical load impact from the commercial Critical Peak Pricing (CPP) pilot.

Table 43: Change in Load during CPP Events for Commercial CPP Participants Parameters Morning Events Evening Events All Events Avg. Load Reduction(kW)a 7.9 ± 2.9 5.1 ± 2.7 6.3 ± 2.3 Avg. Load – Commercial CPP Participants, Pre-Pilot (kW) 6...

AI summary Table 43 presents the average load reduction during Commercial Peak Pricing (CPP) events for commercial participants, showing reductions of 7.9 kW in the morning and 5.1 kW in the evening, with statistical significance confirmed for all events.

6.1.2 Snapback Effect The snapback effect refers to commercial CPP customers that use more electricity than the baseline during the hours immediately following CPP event hours, compared to the pre-pilot period. This effect was evaluated ba...

AI summary The snapback effect refers to increased electricity usage by commercial CPP customers immediately after CPP event hours. The analysis found statistically insignificant morning and evening snapback effects, but a significant 6.9 kW load increase during event days with both morning and evening CPP events.

Table 45: Snapback Effect for Commercial CPP Participants Parameters Load Reduction a (kW) Avg. Significance (p_Value≤0.05) Morning Snapback 0.6 ± 0.9 X Evening Snapback -0.1 ± 1.3 X b Morning & Evening Snapback -6.9 ± 3.4 ✓ Overall Snapba...

AI summary Table 45 presents the snapback effect for commercial CPP participants, showing load reduction and increase values with their significance levels. The data indicates mixed results, with some periods showing significant load reduction and others not.

Parameters Winter Overall Winter – Non-Holiday Weekdays Winter – Holiday Weekends Non Winter Annual Average Avg. Usage Reduction (kWh/day)a 54.0 ± 10.9 51.2 ± 11.6 62.3 ± 16.6 -21.4 ± 3.7 -12.2 ± 6.7 Avg. Usage – Commercial CPP Participant...

AI summary Table 47 presents data on the average usage reduction for commercial CPP participants across different time periods, showing reductions during winter and non-winter periods. The data highlights the impact of weather on load reduction, with significant statistical significance across all categories.

6.1.6 Effect of Consecutive CPP Events on Load Reduction During Phase 4, like Phase 3, there was only one instance of two consecutive CPP events, which occurred when events 5 and 6 took place on December 23, 2024. The second of these conse...

AI summary During Phase 4, a single instance of two consecutive Critical Peak Pricing (CPP) events occurred on December 23, 2024. The second event led to a statistically significant higher load reduction compared to the first, suggesting that consecutive CPP events did not negatively impact load reduction. However, the limited data from this single occurrence prevents broader conclusions about the impact of consecutive CPP events.

6.2 Economic Impacts This section presents and discusses the impact of commercial CPP tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of commercial Critical Peak Pricing (CPP) tariffs on electricity bills and examines price elasticity related to these tariffs.

6.2.1 Change in Electricity Bills The bill impact analysis for the commercial CPP uses the same method that was used for estimating the commercial CPP load impact analysis. In the bill impact analysis, applicable tariffs were applied in ac...

AI summary The analysis of the commercial CPP's impact on electricity bills shows an average daily saving of $12, or 5.8%, during the Winter season in Phase 4. The bill impact analysis used applicable tariffs based on customer type and pilot period, as detailed in Table 48 and Attachment I.

Table 49: Change in Daily Electricity Bill for Commercial CPP Participants Parameters Winter Non-Winter Annual Average Bill Savings ($/day)a Avg. 11.7 ± 10.1 -1.5 ± 1.9 10.3 ± 7.0 Avg. Bill, Commercial CPP Participants, Pre-Pilot ($/day) 2...

AI summary Commercial CPP participants saw no significant change in average daily bills despite increased energy consumption during non-Winter months, due to decreased CPP volumetric energy costs. Annual electricity bills were reduced despite higher overall energy use.

6.2.2 Price Elasticity NS Power evaluated price elasticity to measure commercial CPP participants' responsivity to electricity prices during Phase 4 of the pilot. Specifically, NS Power evaluated Daily Price Elasticity during Winter season...

AI summary NS Power evaluated price elasticity for commercial Critical Peak Pricing (CPP) participants during Phase 4 of a pilot. The analysis found a Daily Price Elasticity of -0.38 during winter and -0.48 annually, both statistically significant. The Inter-period Substitution Price Elasticity was -0.14, but not statistically significant.

7 MURB TOU Tariff Impacts As this Phase represents the first year of the MURB TOU pilot program, participation was limited to 10 enrolled MURBs, with the pilot period beginning on November 1, 2024. The goal of the MURB TOU pilot is to info...

AI summary The MURB TOU pilot program, in its first year, involves 10 enrolled MURBs starting November 1, 2024. The goal is to determine if removing the demand charge for certain customer segments on the General Rate can increase load shifting potential compared to the commercial TOU pilot. This section discusses the estimated impacts of the commercial TOU pilot on load and economics.

7.1 Load Impacts This section presents and discusses the electrical load impact from the commercial MURB TOU pilot.

AI summary This section presents and discusses the electrical load impact from the commercial MURB TOU pilot, examining how Time-of-Use pricing affects load patterns in multi-unit residential buildings.

7.1.1 Change in Load during Peak Periods [Figure](#page-103-0) 41a illustrates the load profiles for MURB TOU participants and the control group during the pre-pilot and pilot periods with the corresponding variation in outdoor temperature...

AI summary The document discusses the impact of MURB TOU (Time-of-Use) on load reduction during peak periods. Load profiles show statistically significant reductions in electrical load, particularly during morning and evening peaks, with an overall 1.9% reduction in electrical load as revealed by the DiD analysis.

Parameters Morning Peak Mid-Peak Periodb Evening Peak Overnight Periodc Overall On-Peak Avg. Load (kW)a Reduction 0.44 ± 0.49 1.34 ± 0.40 0.54 ± 0.49 0.48 ± 0.31 0.48 ± 0.35 Avg. Load – MURB TOU Participants, Pre Pilot (kW) 24.2 24.4 25.1...

AI summary The table presents load reduction data across different peak periods for MURB Time-of-Use (TOU) participants, showing average load reductions and their significance levels. The data indicates that load reductions were most significant during mid-peak and overnight periods, with overall on-peak reductions at 1.9%.

Change in Load by Month during Peak Periods [Figure](#page-105-3) 42 illustrates the impact of MURB TOU on average load reduction (kW), along with corresponding average outdoor temperature (°C) during peak periods as well as mid-peak and o...

AI summary The text discusses the impact of MURB TOU on load reduction during peak periods in the winter season (November 2024–March 2025). Load reductions were statistically significant in November and January, but load increased by 9.5% in March. The largest load reduction of 14.5% occurred in November when temperatures were above 7 °C, while the highest load increase of 9.8% occurred in March when temperatures were 3 °C.

7.1.2 Snapback Effect The snapback effect refers to premises that use more electricity than the baseline during the hours immediately following peak periods, compared to the pre-pilot period. This effect is evaluated based on the same DiD...

AI summary The snapback effect refers to increased electricity usage following peak periods, evaluated using a Difference-in-Differences (DiD) approach. MURB TOU participants showed average load reductions during morning and evening snapback periods, with only the morning reduction being statistically significant.

7.1.3 Change in Load during Highest ANL Hours [Figure](#page-106-0) 43 depicts the distribution of Top 20, 50 and 88 highest ANL hours for MURB TOU participants during morning peak, evening peak, mid-peak, and off-peak hours. As seen in [F...

AI summary The text discusses the change in load during the highest Apparent Net Load (ANL) hours for MURB TOU participants. It indicates that load reductions occur during these hours, with statistically significant reductions during the top 50 and 88 highest ANL hours, particularly during TOU peak periods.

Parameters Highest ANL Hours ANL Hours Coincide TOU Peak Periods Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 Avg. Load (kW)a Reduction 3.3 ± 4.0 4.2 ± 2.9 3.2 ± 2.1 2.9 ± 4.2 3.7 ± 3.0 2.8 ± 2.5 Avg. Load – MURB TOU Participants, Pre-Pilot (...

AI summary Table 52 presents data on the change in load (kW) during highest winter ANL hours for MURB TOU participants, including average load reduction, relative load reduction percentages, and significance levels. The data compares top 20, top 50, and top 88 participants.

Changes in daily electricity usage were estimated by applying the same DiD approach that was used for estimating hourly load impact. [Table 53](#page-107-3) presents the estimated changes in daily electricity usage (kWh/day) for MURB TOU p...

AI summary The document discusses the estimation of changes in daily electricity usage for MURB TOU participants using a DiD approach, with results presented in Table 53.

Winter Winter Months Parameters Overall January February March November December Avg. Monthly Demand Reduction (kW)a -0.12 ± 1.62 3.28 ± 6.13 -1.66 ± 6.01 0.87 ± 1.38 -1.65 ± 2.76 -0.84 ± 2.64 Avg. Monthly Demand – MURB TOU Participants, P...

AI summary The table presents demand reduction data for winter months, showing mixed results with some months indicating demand reduction and others showing demand increase. The data includes average monthly demand reduction, average monthly demand for MURB TOU participants before the pilot, and relative monthly demand change percentages. All values are statistically significant.

[Figure](#page-110-0) 45 illustrates the estimated relative demand reduction (%) overall and across specific TOU periods, including pre-morning peak, morning peak, morning snapback, pre-evening peak, evening peak, and evening snapback. Dur...

AI summary Figure 45 and Table 55 analyze the relative demand reduction percentages for MURB TOU participants during various time-of-use periods in Winter 2024/25. While some changes in demand are not statistically significant, overall demand reduction of 1.4% and specific periods show significant reductions.

Table 55: Changes in Demand by MURB TOU Participants during Winter Parameters Pre- Morning Peak b Morning Peak c Morning Snapback Pre- Evening Peak e Evening Peak f Evening Snapback g Overall Daily Avg. Demand Reduction (kW) a -0.2 ± 0.2 0...

AI summary Table 55 presents changes in demand by MURB TOU participants during winter, showing average demand reductions and increases across different peak and snapback periods, along with statistical significance and relative demand changes.

7.2 Economic Impacts This section presents and discusses the impact of MURB TOU Tariff on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of the MURB TOU Tariff, focusing on its effect on electricity bills and price elasticity.

7.2.1 Change in Electricity Bills For the assessment of the economic impacts of the MURB TOU program, the same DiD approach used to estimate load and demand impacts was applied to evaluate changes in electricity bills for MURB TOU particip...

AI summary The economic impact of the MURB TOU program was assessed using a DiD approach, applying 2025 tariffs to evaluate changes in electricity bills for participants based on customer type and pilot period.

Customer Type Period Applicable Tariff Control Pre-Pilot General Tariff Control Pilot General Tariff Treatment Pre-Pilot General Tariff Treatment Pilot MURB TOU Table 56: Tariffs Used for Evaluating the Impact of MURB TOU on Electricity Bi...

AI summary The document presents a comparison of electricity bills for MURB TOU participants before and during the pilot period, showing an average daily bill saving of approximately $12, though not statistically significant. The MURB TOU rate was designed to save during non-Winter seasons.

7.2.2 Price Elasticity NS Power evaluated participants' responsiveness to energy price under MURB TOU pricing program, focusing on estimating daily price elasticity and inter-period Substitution Price elasticity. While Daily Price Elastici...

AI summary NS Power evaluated the price elasticity of MURB participants under a TOU pricing program. The daily price elasticity was estimated at -1.19, and the inter-period substitution price elasticity at -0.032, but neither was statistically significant, indicating limited responsiveness to price changes.

Findings Summary The TVP pilot tariffs have demonstrated success in reducing load during peak periods while providing participating customers with bill savings. Both residential tariff options evaluated continue to demonstrate a strong cap...

AI summary The TVP pilot tariffs have successfully reduced load during peak periods and provided bill savings to customers. Residential and commercial tariff options show benefits to the grid and customers, with positive load shift results observed in general rate participants. The evaluation supports the ongoing progress of TVP Tariffs in shifting electricity usage to off-peak periods.

Residential TOU & CPP - Participants continue to demonstrate statistically significant reduced load during peak periods with minimal snapback. - For the first time, TVP combined with technology (e.g. smart thermostats) and DR (i.e. Eco Shi...

AI summary The analysis shows that residential Time-of-Use (TOU) and Critical Peak Pricing (CPP) customers experienced reduced load during peak periods, especially when combined with smart technology like Eco Shift and smart thermostats. Electrification of space heating also contributed to load reduction without significantly increasing annual energy consumption.

Commercial TOU & CPP - Participants for the first time have demonstrated statistically significant reduced load during peak periods. This new finding is largely attributable to improvement in methodology and increased sample sizes. - The l...

AI summary The document discusses findings from commercial Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs, noting statistically significant load reductions during peak periods, especially in cold weather. However, results vary by rate class, with Small General participants showing less responsiveness.

Multi-Unit Residential Building TOU - Despite the absence of a demand charge, MURB TOU customers did not increase their monthly demand during Winter. - Winter energy and bill savings were positive but not statistically significant, which a...

AI summary The analysis of Multi-Unit Residential Building Time-of-Use (TOU) rates shows that customers did not increase monthly demand during Winter, and while energy and bill savings were positive, they were not statistically significant. Modest load reductions were observed, particularly during evening peak periods, with no evidence of snapback.

Attachment I: Riders and Tariff Structure A summary of the TVP rate designs is included. For additional details, review the publicly available Tariff book.[13](#page-115-5) The volumetric rates used within the billing models are summarized...

AI summary Attachment I provides a summary of Time-Varying Pricing (TVP) rate designs and references the publicly available Tariff book for additional details. It also includes volumetric rates used in billing models and visual aids to explain TVP tariff structures.

Riders Although riders can change throughout a pilot Phase, to control for economic impacts associated with tariff change, a consistent tariff is used for all economic analyses. Riders are applied to all volumetric energy charges on a per...

AI summary The document discusses the application of riders to volumetric energy charges on a per kilowatt-hour basis, ensuring consistency in economic analyses during pilot phases. It provides a summary of rider rates for different residential and commercial rate classes.

Table 59: Tariff Summary (January 2025) Domestic SOR Customer Charge $19.17 per month Energy Charge $0.16931 per kWh Domestic TOU Customer Charge $19.17 per month Energy Charge (Winter on-peak) $0.33862 per kWh Energy Charge (Winter off-pe...

AI summary The document presents a detailed summary of various tariff structures effective January 2025, including Domestic SOR, Domestic TOU, Domestic CPP, Small General SOR, Small General TOU, General SOR, General TOU, General CPP, and MURB TOU. Each tariff includes customer charges, energy charges for different time periods, and demand charges.

Table 60: Top 88 ANL Hours 2020 - 2021 Load - Wind % of Halifax Temp. TOU Period Rank Date Start Time (Adjusted Net Load) Maximum (°C) AM Peak / PM Peak / (MW) Load Off-Peak 1 19-Feb-21 8:00 AM 1,722.6 100.0% -8.7 AM 2 21-Jan-21 5:00 PM 1,...

AI summary Table 60 lists the top 88 Apparent Net Load (ANL) hours from 2020 to 2021, showing dates, times, load levels, percentages of maximum load, and temperature data. The table highlights peak load times and associated conditions, such as temperature and time-of-use periods.

Table 66: Summary of Changes to Control Group Methodology[18](#page-128-3) Previous Method New Method Projected Benefit Neighbourhood criteria based on feeder and postal code combination Neighbourhood criteria to be based on region (i.e. C...

AI summary The document outlines changes to the control group methodology, including the use of region-based neighborhood criteria, inclusion of heating classification and Eco Shift participation in the selection process, and improved load similarity metrics. These changes aim to enhance the accuracy and effectiveness of the control group selection for TVP programs.

III.2.6 CPP Reference Days Although the regression model controls for time synchronous (i.e. zero hour lag-lead) temperature effects in the form of heating degree days (HDD), it is critical to find reference days with similar temperature p...

AI summary The document discusses the methodology for selecting reference days in the Critical Peak Pricing (CPP) program, emphasizing the importance of similar temperature profiles and weekday types to minimize variable bias in regression models. Reference days are selected based on temperature and weekday type, with specific criteria to ensure accurate comparisons for the Thermal Value Program (TVP).

III.3 Regression Models The regression models are divided into three sections, Residential TOU & CPP, Commercial TOU & CPP and MURB TOU. Notably, these regression models utilize hourly AMI data on a per-customer basis. This shift from prev...

AI summary The regression models are divided into three sections: Residential TOU & CPP, Commercial TOU & CPP, and MURB TOU. These models use hourly AMI data on a per-customer basis, leading to smaller margins of error compared to earlier TVP evaluation reports due to increased sample sizes in Phase 4.

III.3.1 Residential TOU & CPP This section presents the methodology used to determine the load, usage, and economic impact of the residential TOU and CPP tariffs. The estimates for load and economic impacts are rounded and reported accordi...

AI summary This section outlines the methodology for determining the load, usage, and economic impact of residential Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs. Estimates are rounded based on the margin of error at the 90% confidence level to avoid implying false precision.

III.3.1.1 Load & Usage Impact Regression Model The regression model used for load and usage impacts is presented in equation ([7)](#page-138-0). $$Load_{it} = \beta_0 + \beta_1. Treatment_i + \beta_2. PilotPeriod_t + \beta_3. (Pilot \times...

AI summary The Load & Usage Impact Regression Model is presented in equation (7), which estimates the impact of treatment groups under TOU and CPP tariffs on load and energy consumption. The model includes variables for treatment status, pilot periods, and heating degree-days (HDD). It distinguishes between load (in kW) and energy usage (in kWh/day) and includes interaction terms between treatment and pilot periods.

III.3.1.2 Economic Impact Regression Model The regression model used for billing impact is as follows in equation ([9)](#page-140-0). $$\begin{aligned} \textit{DailyBill}_{it} &= \beta_0 + \beta_1. \textit{Treatment}_i + \beta_2. \textit{P...

AI summary The document outlines a regression model used to analyze the economic impact of billing changes, specifically focusing on the relationship between treatment status, pilot periods, and heating degree days (HDD) on daily bills. It also mentions models for price elasticity.

III.3.2 Commercial TOU & CPP This section presents the methodology used to determine the load, usage, and economic impact of the commercial TOU and CPP tariffs. The estimates for load and economic impacts are rounded and reported according...

AI summary This section discusses the methodology for evaluating the load and economic impact of commercial Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs. It uses a Mixed-Effects regression analysis and a semi-DiD approach due to the absence of a control group and small sample sizes, which affect the precision and reliability of the estimates.

III.3.2.1 Load and Usage Impact Regression Model Considering the methodological choices discussed above, the commercial TOU and CPP load/usage, billing as well as daily and substitution price elasticity are described by the equations ([14)...

AI summary This section presents a regression model for analyzing the load and usage impact of commercial Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs. The model includes variables such as treatment, pilot period, heating degree days (HDD), and their interactions, using equations (14) and (17). The model helps assess price elasticity and billing impacts.

III.3.2.2 Economic Impact Regression Model $$\begin{aligned} \textit{DailyBill}_{it} &= (\beta_0 + u_i) + \beta_1. \textit{Treatment}_i + \beta_2. \textit{PilotPeriod}_t \\ &+ \beta_3. (\textit{Pilot} \times \textit{Treatment})_{it} + \bet...

AI summary This section presents three regression models used to analyze the economic impact of energy programs. The models assess daily billing, average energy usage, and peak-to-off-peak load ratios, incorporating variables such as treatment, pilot periods, temperature, and energy prices. The 'Treatment' variable is excluded for commercial TOU and CPP analyses due to the lack of control groups, but it is included in the MURB TOU regression.

III.3.3 MURB TOU The evaluation of MURB TOU is based on panel data estimation approach with matched control groups and pre-pilot data using the difference-in-difference (DiD) approach similar to the residential tariffs. Given the relativel...

AI summary The evaluation of MURB TOU uses a difference-in-difference approach with mixed-effects regression due to the small sample size, ensuring more reliable program impact estimates.

III.3.3.1 Load and Usage Impact Regression Model The same regression as equation (14) was used for load impact and usage impact analyses for MURB TOU.

AI summary The regression model from equation (14) was applied to analyze both load impact and usage impact for MURB TOU in the proceeding.

III.3.3.2 Economic Impact Regression Model The same regression as equations (15), (16) and (17) was used for bill saving and price elasticity analysis for MURB TOU.

AI summary The Economic Impact Regression Model, based on equations (15), (16), and (17), was applied for bill saving and price elasticity analysis in the context of MURB TOU.

Attachment III: Methodology In addition to the metrics calculated for commercial TOU and CPP, the effect on demand was evaluated. This analysis estimates demand using 15-minute average calculated every 15 minutes (i.e. AMI interval data),...

AI summary This section of Attachment III discusses the methodology used to evaluate demand effects, comparing 15-minute average interval data (AMI) with actual billing demand calculated every 5 minutes. It notes that while the AMI data is an estimate, it serves as a reasonable proxy for determining demand effects under the TVP EM&V.

IV.1.1 CPP (Phase 1) Consistent with the approved evaluation plan, the CPP evaluations used a within-subject control group methodology. In practice this meant that there was no control group for CPP customers, rather the only control was t...

AI summary The evaluation of the Critical Peak Pricing (CPP) program used a within-subject control group methodology, with treatment customers serving as the control during reference days. After one year, Econoler recommended modifying the approach to include a true control group for CPP customers to align with Time-of-Use (TOU) evaluations.

IV.2.1 Phase 1 Heating classification in Phase 1 was based on rate code (i.e. 02 = Non-Electric, 03 = Electric). Premises are classified as rate 02 and 03 when first registered with NS Power as a customer. These rate codes are often not re...

AI summary Phase 1 heating classification is based on rate codes (02 = Non-Electric, 03 = Electric), which are assigned when customers first register with NS Power. However, these classifications are not updated when heating sources change, leading to inaccuracies, especially with increased heat pump adoption.

ers Evaluated for Load Reduction during CPP Events, along with the Residual Error Distribution Associated with (c) Fixed Effect Modelling and (d) Mixed-Effect Modelling Given the baseload heterogeneity, time-series (hourly) load data and t...

AI summary The analysis evaluates load reduction during Critical Peak Pricing (CPP) events using Mixed-Effect modelling, which provides a more balanced error structure and improved model fit for assessing Commercial Time-of-Use (TOU) and CPP load response, given the heterogeneity in customer behavior and time-series data.

MURB TOU Customers Unlike the commercial TOU and CPP rates, MURB TOU has not yet been evaluated using the fixed effects regression model. As such additional analyses are provided within in order to validate the choice of a mixed effects re...

AI summary The document discusses the evaluation of MURB TOU rates, noting that unlike commercial TOU and CPP rates, MURB TOU has not been assessed using a fixed effects regression model. Additional analyses are provided to validate the use of a mixed effects regression model with a control group for the MURB TOU Tariff.

Residual Diagnostics for Fixed- vs. Mixed-Effect Modeling Approaches It is important to note that a Fixed-Effect model absorbs the time-invariant differences, such as Baseload heterogeneity across MURBs, by eliminating it from the analysis...

AI summary The text discusses the use of Fixed-Effect and Mixed-Effect models in analyzing the impact of Time-of-Use (TOU) pricing on load reduction and bill savings in MURBs. It highlights that Mixed-Effect models are more suitable due to baseline load differences and presents residual diagnostics comparing both models.

Coincidence of Critical Peak Events and System Margin In its Decision and Order on the Year Three (2023/24) Evaluation Report (Year Three Report) in M11823, the Board provided: NS Power agreed with Synapse that system margin forecasts may...

AI summary The document discusses the relationship between system margin forecasts and Critical Peak Pricing (CPP) events, noting that system margin during CPP events was significantly lower than during other hours. The Board directed NS Power to analyze this relationship and refine methods for estimating load reductions through TVP tariffs.

Reporting on Small Business Characteristics that Enable Load Shifting As part of its 2024 TVP Consensus Agreement, the Company committed to: h. Reporting back to stakeholders on changes that could be made to help customers determine whethe...

AI summary As part of its 2024 TVP Consensus Agreement, NS Power committed to reporting on small business load characteristics that enable load shifting, customer recruitment tactics, and reasons for customer reluctance to participate in TVP, TOU, and CPP programs.

Review of Marketing and Communication Efforts In its Decision and Order on the Year Three Report (M11823), the Board provided: Narrative Research conducted a customer survey, which highlighted residential customers' dissatisfaction regardi...

AI summary The document discusses NS Power's efforts to improve communication with residential and commercial customers regarding time-varying pricing (TVP) programs. It highlights the use of a customer survey, a purpose-built estimation tool for residential inquiries, and a coordinated approach with commercial customers involving relationship management and data analytics. The Board emphasized the importance of clear communication to manage customer expectations and ensure the success of the TVP pilot.

Other Board Directives and Consensus Agreement Commitments Across the 2024 Consensus Agreement, Year Three Report (M11823), 2024/25 TVP Application (M11822), and other proceedings, other Board directives and commitments have been made. Thr...

AI summary The text discusses other Board directives and commitments made across various proceedings, including the 2024 Consensus Agreement, Year Three Report, and the 2024/25 TVP Application. Nova Scotia Power reviewed these items through its pricing innovation process and stakeholder consultative sessions, and submitted a request for temporary modification of the TVP Pilot.

Time-Varying Pricing Report 2025 May 2025

AI summary The document is a report on Time-Varying Pricing (TVP) for the year 2025. It outlines the implementation and evaluation of TVP programs, including Time-of-Use (TOU) and Critical Peak Pricing (CPP), in Nova Scotia. The report likely discusses the impact of these pricing strategies on consumers and the electricity grid.

Background • For the past few years, NSP has commissioned Narrative Research to collect feedback from participants of two rate plans: Time-of-Use and Critical Peak Pricing. The purpose of this survey was to better understand customer exper...

AI summary NSP has worked with Narrative Research to gather customer feedback on the Time-of-Use and Critical Peak Pricing rate plans over the past few years. The survey aimed to understand customer experiences and any changes since the last iteration of the pilot.

Purpose and Objectives - Narrative Research is conducting the survey on behalf of Nova Scotia Power. NSP was interested in collecting feedback from participants of the program (both new and ongoing participants). Research sought to achieve...

AI summary Nova Scotia Power is conducting a survey through Narrative Research to gather feedback from participants of the Time-Varying Pricing Rate Pilot. The objectives include measuring customer experiences, identifying behavior changes, assessing communication effectiveness, collecting preferences for program changes, and tracking opinion shifts over time.

Methodology Mode Online survey Audience NSP TVP Pilot Participants (Years 1-4) 2,103 completes Time of Use: 1,332 Critical Peak: 771 Data Collection Dates April 10 - 16, 2025 Response Rate 27.0% (7,801 invitations sent) Average Completion...

AI summary The methodology section describes an online survey conducted among NSP TVP Pilot Participants over four years, with 2,103 completes and a 27% response rate. The survey was conducted between April 10-16, 2025, and took an average of 23 minutes to complete.

Three Takeaways Time-Varying Pricing Rate Pilot participant satisfaction remains high. Overall participant satisfaction across both ToU and CPP is high, with just one in ten not being satisfied. Satisfaction with the Critical Peak Pricing...

AI summary Participant satisfaction in Time-Varying Pricing (TVP) pilots remains high, though understanding of billing is declining. Changes to the pilots may cause some participants to leave, even with additional incentives. The findings highlight challenges in communication and potential impacts of policy adjustments on participant retention.

Objectives Key Findings Measure residential customer opinions and experiences of the pilot - Overall Satsifaction: Two thirds of TVP participants remain satisfied (scores of 7-10) while just one in ten give low scores of 1-4. Participant s...

AI summary The analysis of the TVP and CPP pilot programs shows that two-thirds of participants remain satisfied, though satisfaction varies by region and income level. Billing clarity and communication effectiveness are key areas for improvement. Participants are changing energy behaviors, but only 30% have installed energy-efficient products since the pilot began.

Collect Feedback on the Critical Peak Pilot - Communication: Nearly all CPP participants received peak events notifications, with half leveraging text messages. Email and text are the preferred channels for receiving critical peak event no...

AI summary Participants in the Critical Peak Pricing (CPP) pilot generally express satisfaction with notifications and event timing, though some suggest improvements such as more advanced notice. Awareness of peak event timing has increased, but some participants remain unclear. While most support maintaining the pilot, one in four may leave if events were called year-round.

Collect Feedback on the Time-of-Use Pilot - Awareness of Peak Hour Timing: This year marks a significant improvement in awareness of when peak hours are in effect, but improving awareness might lead to higher satisfaction since some partic...

AI summary The Time-of-Use (TOU) pilot has seen improved awareness of peak hours, but participants are strongly opposed to any changes, particularly those that would extend peak periods into weekends, holidays, or the April to October months. Many participants are likely to leave the program if changes occur, with a preference for lower winter peak rates as an incentive.

Explore Pricing Plan Preferences and Motivations - Motivations for Joining: Saving money dominates as the main reason for joining and remaining in a rate plan, distantly followed by non-monetary motivations. - Likelihood of Switching: Fewe...

AI summary The main motivation for joining and staying in a rate plan is saving money, with fewer than one in five participants considering switching to an alternate Time-Varying Pricing (TVP) pilot. Non-monetary motivations are less significant in comparison.

Satisfaction

AI summary The document contains images from a regulatory proceeding related to satisfaction, potentially involving Nova Scotia Power and energy pricing strategies such as Time-Varying Pricing, Time-of-Use, and Critical Peak Pricing. Specific details are not provided in the text, as the content is limited to images.

Satisfaction with Time-Varying Pricing Rate Pilot Participant satisfaction with CPP has increased in 2025 while ToU satisfaction has remained relatively stable, with only a slight numerical decline. Overall satisfaction with the Time-Varyi...

AI summary Participant satisfaction with the Critical Peak Pricing (CPP) rate pilot has increased in 2025, while Time-of-Use (ToU) satisfaction has remained stable but with a slight decline. Long-term participants show higher satisfaction compared to recent joiners, and users of the MyEnergy Insights platform report higher satisfaction levels with both programs.

Satisfaction with Time-Varying Pricing Rate Pilot - Region Overall satisfaction with the TVP Rate Pilots appears to be somewhat lower in Western Nova Scotia compared to Metro. Variation in results are driven mostly by ToU participants whil...

AI summary Overall satisfaction with the Time-Varying Pricing (TVP) Rate Pilots is lower in Western Nova Scotia compared to Metro. The difference is mainly driven by Time-of-Use (ToU) participants, while Critical Peak Pricing (CPP) participant satisfaction is more consistent across the province.

Satisfaction with Time-Varying Pricing Rate Pilot – Household Income Satisfaction with TVP pilots are relatively consistent across income brackets, though there an indication of a slight correlation between household income and satisfactio...

AI summary Satisfaction with Time-Varying Pricing (TVP) pilots shows slight correlation with household income, with higher-income participants more likely to provide top satisfaction scores. However, mean scores remain consistent across income brackets, and increases in satisfaction with income are minimal due to small sample sizes.

Satisfaction with Time-Varying Pricing Rate Pilot – Primary Heat Source Type Satisfaction among CPP and ToU participants does not vary significantly between those relying on electricity as their primary heat source and those who are not. L...

AI summary Satisfaction with the Time-Varying Pricing Rate Pilot does not significantly differ between participants using electricity as their primary heat source and those who do not. Participants on electric heat may be finding ways to save by adjusting their usage during peak times.

Satisfaction with Time-Varying Pricing Rate Pilot – Household Income & Heat Source Satisfaction with TVP rate pilots, overall, appears to improve with household income across non-electric participants. Reviewing satisfaction results across...

AI summary Satisfaction with Time-Varying Pricing (TVP) rate pilots improves with higher household income among non-electric participants. Lower-income participants on non-electric heat sources are less satisfied than those with higher incomes. Satisfaction is consistent across income levels for electric heat sources. The ToU process maintains high satisfaction, while CPP sees a decline in clarity of information provided.

Additional Information or Materials When Deciding to Enroll While most indicate satisfaction with the amount of information, there is a desire from some to have more information on rates and potential savings. Asked what additional informa...

AI summary Participants expressed mixed satisfaction with the information provided about the program. While most were satisfied, some desired more details on rates, savings, and billing. Many participants indicated they would have benefited from clearer information on potential financial implications and savings from participating in the program.

Most Helpful Communication Reminders, emails, and time of day charts are viewed as the most helpful communication received by pilot participants. Asked about the most helpful communication they have received as part of the pilot, participa...

AI summary Participants in the pilot program found reminders, emails, and time-of-day charts to be the most helpful communication. Reminders for peak hours, emails, and clear explanations of rates and times were particularly valued. These communications helped participants manage their energy use effectively.

Contact with Customer Care Centre Among the minority of participants contacting customer care, there has been a decrease in CPP participants looking for program details and an increase in CPP inquiries about billing/savings. ToU participan...

AI summary The text discusses changes in customer inquiries to NSP's Customer Care Centre regarding Time-Varying Pricing (TVP) programs. There has been a decrease in inquiries about program details and an increase in questions about billing and savings, particularly among CPP participants. TOU participants continue to have inquiries about savings and billing.

Preferred Notification Method Email and text are the preferred channels for receiving critical peak event notifications, though there is opportunity to promote text notifications to participants. Eight in ten CPP participants express a pre...

AI summary The document discusses the preferred notification method for critical peak events, highlighting that email is the most preferred (78%) followed by text messages (67%). However, only 47% of participants currently receive text alerts, indicating an opportunity for improvement. MyEnergy Insights users are more likely to prefer text messages.

Adding Household Members to Critical Peak Event Notifications CPP participants would welcome the opportunity to send critical peak event notifications to other members of their household. If Nova Scotia Power allowed participants to send c...

AI summary CPP participants want to send critical peak event notifications to other household members. Over half of CPP participants would do so, with higher interest in larger households. This capability could increase participation and effectiveness of the CPP program.

Critical Peak Notification Improvement Critical peak notifications could be improved by more advance notice, although most offer no suggestions for improving communication. When asked about how peak event notifications could be improved, a...

AI summary Participants in the Critical Peak Pricing program suggest that improving advance notice for critical peak events could enhance communication. Some also request clearer billing information about specific events and practical energy-saving tips. Most participants, however, feel no improvements are needed or are unsure.

Importance that Rate Remains the Same This Winter CPP participants continue to feel strongly that the critical peak rate remains the same in the coming winter. Asked about the importance that the rate remains the same for the coming winter...

AI summary CPP participants emphasize the importance of maintaining the critical peak rate during the winter. While 76% of participants rate this importance highly, there has been a notable decrease in the percentage giving the highest score, dropping from previous levels by 11 points.

When Time-of-Use Peak Events Can Be Called This year marks a significant improvement in awareness of when peak hours are in effect, but improving awareness might lead to higher satisfaction since some participants think hours are in effect...

AI summary This document discusses the increasing awareness among Time-of-Use (ToU) participants regarding peak hours, noting that most correctly identify the period as November through March. However, some still believe peak events can occur in October, and there is a need for further education on specific times of day when peak hours are in effect.

Feedback on Proposed Changes to the Time-of-Use Pilot ToU participants are very opposed to possible changes to the pilot, preferring peak periods continue to avoid weekends, holidays, and the April to October months. It is incredibly impor...

AI summary ToU participants strongly oppose changes to the Time-of-Use pilot, emphasizing the importance of maintaining peak periods only on weekdays, excluding holidays and the April to October months. Over half of participants rate this as extremely important, with consistent sentiment across all participation years.

Likelihood to Leave Time-of-Use Pilot One in three ToU participants would be at least somewhat likely to leave the ToU pilot should any changes occur, regardless of additional incentives offered. To gauge participant likelihood to leave th...

AI summary One in three Time-of-Use (ToU) participants would be at least somewhat likely to leave the ToU pilot if changes occur, regardless of additional incentives. Participants showed hesitation to changes, even with additional discounts, with 38% likely to leave if the monthly base fee increased, 34% if weekends were included, and 31% if non-winter periods were included.

Preferred Discount if Time-of-Use Included Weekends If ToU began including weekends, participants would prefer a lower winter peak and off-peak rate. When asked what kind of additional discount would be preferred if ToU included weekends,...

AI summary If Time-of-Use (ToU) pricing included weekends, participants would prefer a lower winter peak rate. A majority favored this option, while more than four in ten preferred a lower winter off-peak rate. Other less popular options included lower summer rates or a new Super off-peak rate overnight.

Expected Return if Time-of-Use Includes Non-Winter Periods ToU participants would expect higher year-round savings if ToU included non-winter periods. ToU participants would largely expect higher monthly savings all year round, including w...

AI summary ToU participants expect higher year-round savings if ToU includes non-winter periods. About one in ten expect higher savings in non-winter periods or are unsure. No significant differences in responses were found based on heat source or household income.

Discounted Electricity Costs Preferred If Monthly Fee Increased Again, discounts to winter peak rates are the clear preference, this time in response to an increase to the monthly base fee. When asked to indicate a discount preference shou...

AI summary The majority of participants prefer discounted winter peak rates if the monthly base fee increases, with fewer interested in lower winter off-peak or a new very low Super off-peak rate. This preference was identified in response to a pilot program's potential monthly fee increase.

Recent Joiners Main Reason For Choosing Plan Saving money dominates as the main reason for participating in a rate plan, distantly followed by non-monetary motivations. New participants were asked why they chose to join ToU or CPP. As expe...

AI summary The main reason for joining Time-of-Use (ToU) or Critical Peak Pricing (CPP) rate plans is to save money, with less than 10% of participants citing non-monetary motivations. Participants highlight the need to reduce electricity costs, particularly for seniors and retirees on fixed incomes.

"I use electricity in the summer due to electric air conditioners, so I am trying to reduce the cost of my electricity in the summer months primarily." – ToU Year 4 Participant Time- of-Use Critica l Peak 2022 (n=428) 2023 (n=137) 2024 (n=...

AI summary A participant in the Time-of-Use (TOU) Year 4 program states that they use electricity primarily in the summer due to electric air conditioners and aim to reduce summer electricity costs. The table shows participation motivations across different years for Time-of-Use and Critical Peak Pricing programs, with 'Save money' being the most common reason.

Previous Joiners Main Reason For Continued Pilot Participation The primary reason for remaining on TVP pilots is also to save money, although fewer indicate this as a motivating factor than those in their first year of the pilot. Year 1, 2...

AI summary Participants in TVP pilots continue to participate mainly to save money, though fewer cite this as a motivation compared to their first year. Over time, participants find it harder to plan around peak periods. Quotes from participants highlight savings and flexibility in energy use as key benefits.

"I mostly try to do things in off peak times, weekends and holidays during winter months, so makes sense to use it for the break in the summer." – ToU Year 3 Participant Т ime-of-Us e C ritical Pea k 2023 (n=308) 2024 (n=322) 2025 (n=330)...

AI summary A ToU Year 3 Participant explains their energy usage behavior, preferring off-peak times, weekends, and holidays during winter, which aligns with using energy during summer breaks. A table shows customer motivations for participating in Time-of-Use (ToU) and Critical Peak Pricing (CPP) programs from 2023 to 2025, with the primary motivation being saving money through off-peak rates.

Reason for Choosing Plan (continued) While reasons for choosing their respective program remain similar, a decreasing number of CPP participants say the pilot fits their lifestyle. The top reasons why ToU participants chose their current p...

AI summary Participants in the Time-Varying Pricing (TVP) and Critical Peak Pricing (CPP) programs report varying reasons for their participation. TVP participants prefer the plan for its flexibility and better rates, while CPP participants mention ease of control and occasional adjustments to save money. Lifestyle and schedule alignment are also cited as factors.

"It seemed like the better option for us as we travel during the winter."– ToU Year 4 Participant • Time- of-Use Critical Peak 2022 (n=428) 2023 (n=445) 2024 (n=346) 2025 (n=318) 2022 (n=174) 2023 (n=178) 2024 (n=154) 2025 (n=182) Fits my...

AI summary Customer feedback on Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs shows varying levels of satisfaction over the years, with some participants finding TOU more suitable for their lifestyle during winter travel, while others express confusion or lack of awareness about alternative plans.

Fewer than one in five participants would consider switching to an alternate TVP pilot. A similar proportion of participants from both rate plans express a likelihood to consider switching to the other offered pilot. That said, an identica...

AI summary Fewer than one in five participants are willing to switch to an alternate Time-Varying Pricing (TVP) pilot. Both Time-of-Use (ToU) and Critical Peak Pricing (CPP) participants show similar levels of disinterest in switching, with 65% from each group unlikely to switch pilots. The low interest suggests dissatisfaction may lead participants to exit the TVP pilot rather than switch rate plans.

CPP and ToU participants are increasingly struggling to understand their bills and the impact of their participation in pilot programs. Findings show a continued downward trend across all statements related to bills for both ToU and CPP pa...

AI summary Participants in CPP and ToU programs are struggling to understand their bills and the impact of their participation in pilot programs. There has been a decline in agreement among participants that their bills are easy to understand and as expected, with CPP participants showing slightly better outcomes than ToU participants. Newer TVP participants also tend to lower overall scores due to limited experience with the plan.

Additional Comments on Billing Participants are attentive to their bills, noting higher-than-normal prices, requesting savings comparisons, more details, or more time to review the data. Fewer than one-half of participants have any comment...

AI summary Participants are paying close attention to their bills under the new rate plan, with many noting higher-than-normal prices and requesting more detailed information, comparisons, and clearer explanations. CPP participants are less likely to provide feedback compared to ToU participants. Some customers express confusion about their bills and the lack of clarity on savings and usage breakdowns.

Other Changes to Electricity Usage Three-quarters of participants state they have, in some way, changed their electricity use after joining the pilot program. This year, fewer participants state they do things at specific times (30%; down...

AI summary Participants in the TVP pilot program have made some changes to their electricity usage, such as shifting high-consumption tasks to off-peak times and reducing overall energy usage. However, there has been little change in home temperature settings over the past four years, indicating limited impact on heating behavior.

Likelihood of Installing a Smart Thermostat There is a mixed likelihood of installing a smart thermostat after joining a Time-Varying Pricing Rate pilot program. Reports of participants being likely to install a smart thermostat continue t...

AI summary The likelihood of installing a smart thermostat among participants in a Time-Varying Pricing Rate pilot program is mixed, with a growing proportion of participants unlikely to install one. The decline in interest may be due to installation challenges, prior installations, or skepticism about smart thermostats.

Few participants provide additional commentary regarding their respective rate plans. Two-thirds of participants did not offer any additional feedback about the pricing plan. Those who gave comments primarily suggest better feedback and ex...

AI summary Most participants did not provide additional feedback on rate plans, while those who did expressed a need for clearer communication, better tracking of savings, and concerns about the frequency of critical peak pricing events. Some noted that energy usage decreased but bills remained unchanged.

Respondent Profile: Time-of-Use

AI summary The document provides a respondent profile on Time-of-Use (TOU) pricing, including figures and images that likely illustrate key aspects of TOU programs and their implementation.

Respondent Profile: Critical Peak Pricing TVP Year Four Report Appendix C Page 1 of 25

AI summary The document presents a respondent profile on Critical Peak Pricing (CPP) as part of the TVP Year Four Report Appendix C. The content includes several figures and images, but no textual details or arguments are provided regarding the topic.

HIGHLIGHTS: - Launched new rates branding - Optimized and enhanced website experience - Improved application process with Salesforce integrations - Advanced and targeted email strategy - Amplified customer reach & engagement with multi-cha...

AI summary The document highlights the implementation of new rates branding, website optimization, improved application processes, advanced email strategies, multi-channel outreach, and the introduction of reporting and analytics tools to enhance customer engagement and insights for future planning.

RESULTS: - Developed dashboards to monitor TVP recruitment, in realtime, which included metrics on applications, volume of TVP related inquires, and marketing efforts. - Cross-functional teams were able to leverage this data to stay agile,...

AI summary The document outlines the development of dashboards to monitor TVP recruitment in real-time, providing metrics on applications, inquiries, and marketing efforts. These tools enabled cross-functional teams to make agile, data-informed decisions regarding recruitment efforts.

- Direct Mail had the longest lifespan and still brings in web traffic to date. Residential YEAR 1 YEAR 2 YEAR 3 YEAR 4 Email YOY % Emails Recipients 43,280 19,489 112,089 355,035 217% ↑ Email Opens 21,778 10,855 71,011 215133 203% ↑ Open...

AI summary The document presents data on the performance of various marketing channels for a residential program, showing significant growth in email recipients, opens, and clicks over the years, along with metrics for web traffic, paid search, and direct mail. The data highlights the effectiveness of different channels in achieving enrollment targets for Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs.

- CTR for search is significantly higher than residential, suggesting that while search volume is lower, business users demonstrate higher intent and engagement when they do search online. Business YEAR 1 YEAR 2 YEAR 3 YEAR 4 Email YOY % E...

AI summary The document highlights that business users have a significantly higher click-through rate (CTR) compared to residential users, indicating higher intent and engagement. However, email engagement metrics show a sharp decline over the years, with a notable drop in email opens and clicks. Additionally, the document outlines the low enrolment rates for time-varying pricing (TOU) and critical peak pricing (CPP) programs.

Residential Recruitment TOU (Rate 80, 81) CPP (Rate 70, 71) Residential Total Enrollment Target 7,000 3,500 10,500 Year 4 New Applications 4,703 2,487 7,416 Year 4 Accepted New Applications 4,137 1,973 6,136 Enrollment (As of January 9, 20...

AI summary The document provides a summary of residential recruitment under Time-Varying Pricing (TVP) programs, including enrollment targets, new applications, and accepted applications for TOU and CPP rates as of January 9, 2025.

SMB Recruitment TOU (Rate 82, 83) CPP (Rate 72, 83) Commercial Total Enrollment Target 500 500 1,000 Year 4 New Applications 0 26 26 2% 2% Enrollment (As of January 9, 2025) 54 53 107 21% HIGHLIGHTS

AI summary The SMB Recruitment section outlines enrollment targets and progress for Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs. As of January 9, 2025, only 54 and 53 participants were enrolled in TOU and CPP programs respectively, significantly below the 1,000 target. Only 26 new applications were received in Year 4, indicating a low level of engagement.

We will: - Continue to encourage sign-ups for the TVP mailing list on our rate pilot landing pages through customer conversations and public events. At the time of this report, there are currently over 560 Customers signed up. - Roll out o...

AI summary The document outlines plans to increase participation in the Time-Varying Pricing (TVP) rate pilot by improving customer engagement, marketing, and application processes. Over 560 customers are currently signed up, and exit surveys will inform future planning.

Time-of-Use Rate Pilot Shift to save. Shift your weekly energy usage in the winter to save on your annual power bill by unlocking summer savings. LEARN MORE & SIGN UP FOR THE 2025 MAILING LIST

AI summary The document promotes a Time-of-Use Rate Pilot (TVP) aimed at encouraging customers to shift their energy usage to summer months to save on annual power bills. It invites participation through a 2025 mailing list.

Critical Peak Pricing Rate Pilot Beat the peak. Save money by shifting your energy use away from periods of peak demand for electricity. LEARN MORE & SIGN UP FOR THE 2025 MAILING LIST Cut back on your electricity use this winter when deman...

AI summary The document promotes a Critical Peak Pricing Rate Pilot, encouraging customers to shift energy use away from peak demand periods to save money. It includes promotional materials and a reference to the TVP Year Four Report Appendix C.

APPLICATIONS ARE NOW OPEN! Shift your energy use to save on your power bill with our latest rate options. Have you heard about our Time-of-Use and Critical Peak Pricing rate pilots? These rate plan pilots provide you with the opportunity t...

AI summary Nova Scotia Power is launching Time-of-Use and Critical Peak Pricing rate pilots, allowing customers to shift energy use during winter to reduce annual energy costs.

Choose the rate pilot that is right for you and your home.

AI summary The text introduces a rate pilot program aimed at helping customers choose the most suitable rate for their home, with a focus on time-varying pricing options.

Time-of-Use Rate Unlook summer savings! Shift your weekly energy usage in the winter to save on your annual power bill by unlocking summer savings Learn more about Time-of-Use >

AI summary The text promotes Time-of-Use (TOU) rates, encouraging customers to shift their energy usage to save on their annual power bill. It highlights the benefits of adjusting energy consumption patterns during different times of the year.

Beat the peak and cave! Save money by shifting your energy use away from periods of peak demand for Learn more about Critical Peak Prioling > APPLY NOW TVP Year Four Report Appendix C Page 14 of 25 Applications are closing soon! Apply Now...

AI summary This document promotes the Critical Peak Prioling program, encouraging users to shift energy use during peak demand periods to save money. It includes marketing materials and application information, emphasizing the benefits of participating in the Time-Varying Pricing (TVP) program.

APPLICATIONS CLOSE SOON Don't miss your final opportunity to choose the best rate plan for your home in 2024-2025! This is a friendly reminder that the deadline is fast approaching for you to choose and apply for one of our latest rate opt...

AI summary This document promotes rate plans for 2024-2025, emphasizing Time-of-Use and Critical Peak Pricing pilots. It highlights the benefits of switching to electric heating and encourages customers to apply before the deadline to save on energy costs.

CRITICAL PEAK PRICING RATE PILOT Best the peak and save Out back on your electricity use this winter during periods of high-demand. You are rewarded for your flexibility with lower rates outside of these four hour peak. you recently switch...

AI summary This document introduces a Critical Peak Pricing Rate Pilot program that rewards customers for reducing electricity use during periods of high demand by offering lower rates outside of four-hour peak periods.

Website - Web Updates: - Individual Rate Pages Created - Content and Visuals Updates - Increase webpage referrals - Save Energy and Money - Rate Options - Home Page Banner November 28 December 15, 2024

AI summary The document discusses recent updates to the website, including the creation of individual rate pages and visual content updates. It also mentions efforts to increase webpage referrals through various sections such as 'Save Energy and Money' and 'Rate Options', with a banner displayed from November 28 to December 15, 2024.

Engagement - Sent a Critical Peak Event Prep Email - Plan to send season complete email, and push more social media to help support TVP Year Four Report Appendix C Page 24 of 25

AI summary The document discusses engagement activities related to the Time-Varying Pricing (TVP) Year Four Report, including sending a Critical Peak Event Prep Email and planning to send a season complete email, along with increased social media support.

It's time to beat the peak! Here's what to expect this season. Critical Peak Prioling season is here! As a participant of this rate pilot, you can save on your power bill by shifting your energy use between November and March when Critical...

AI summary Critical Peak Prioling season has begun, offering participants the opportunity to save on their power bills by adjusting energy use between November and March during Critical Peak events.

About Critical Peak Events - Critical Peak events are 4-hour periods when we anticipate demand for electricity to be highest during the winter months. - During these 4-hour periods, your power rate is higher and once the event is completed...

AI summary Critical Peak Events are 4-hour periods during winter when electricity demand is highest, resulting in higher power rates. These events are limited to 3 per week and 18 per season, and do not occur on statutory holidays. Customers are notified in advance via email or text, and rates return to lower levels after the event.

Critical Peak Event Tips The key to saving money is making sure you reduce your electricity use during the 4-hour Critical Peak event. Here are some tips to help you:

AI summary The text provides tips for reducing electricity use during a 4-hour Critical Peak event to save money.

1. Avoid running major electrical appliances Plan to use items like your dishwasher, clothes washer and dryer, and electric range or stove outside of the 4four-hour event. Are you an Electric Vehicle (EV) owner? You will want to postpone c...

AI summary The text advises consumers to avoid using major electrical appliances during a 4-hour event to manage energy demand. It specifically mentions EV owners and suggests postponing EV charging until after the event.

5. Gain insights into your energy use Find out which appliances you should avoid using and dive into other home energy insights with MyEnergy Insights 3 days after the event. Keep track of how you are doing and how you can further save ene...

AI summary This section provides information about gaining energy use insights through MyEnergy Insights and mentions the Critical Peak Priolog Rate Pllot. It also references the TVP Year Four Report Appendix C Page 25 of 25 and includes an image placeholder.

Phase 1: 2021/2022 (Cohort 1) Rate Class Tariff (Tariff #) August September October November December January February March General Demand CPP (Rate 73) 5 5 5 5 5 5 5 6 5 5 5 5 TOTAL CPP 286 284 278 276 276 271 270 390 390 386 385 384 Tot...

AI summary The text provides a detailed table showing the number of customers on different tariff plans across various months for the Phase 1 (2021/2022) cohort. It includes data for General Demand, Domestic, and Small General rate classes under Time-Varying Pricing (TVP) and Capacity-Based Pricing (CPP) tariffs.

Agenda - 1. Welcome & Introduction - 2. TVP Tariff Development Cycle - 3. Review of Year Three Evaluation Report Results Econoler - 4. Review of Draft List of Proposed MURB TOU Tariff Evaluation Metrics - 5. Draft 2024/25 Areas of Focus Wo...

AI summary The agenda outlines key discussion points for a regulatory proceeding, including the development of a Time-Varying Pricing (TVP) tariff, review of evaluation reports, proposed tariff metrics, and planning for future work areas.

TVP Tariff Development Cycle • As provided in the 2024 TVP Consensus Agreement – the Company will continue to manage and refine its TVP Program in a structured, analytics-based, and stakeholder engaged manner focusing on an annual TVP deve...

AI summary The 2024 TVP Consensus Agreement outlines a structured approach for managing and refining the TVP Program, emphasizing an annual development, approval, and implementation cycle with stakeholder engagement and analytics-based decision-making.

November Winter/Spring Spring/Summer Summer/Autumn Effective date for TVP • tariff changes Enrolment cut-off for • coming winter period Data collection and • monitoring of TVP program performance Development of program • refinements Measur...

AI summary The document outlines the annual cycle of the Time-Varying Pricing (TVP) Program, including key activities such as data collection, stakeholder engagement, and tariff changes. The Company will maintain ongoing communication with stakeholders to ensure transparency and input on the program's strategy and tariff offerings.

TIME-VARYING PRICING PILOT PHASE 3 EVALUATION NOVEMBER, 2024

AI summary The document presents an evaluation of the Time-Varying Pricing (TVP) Pilot Phase 3, focusing on its implementation and outcomes in November 2024. The evaluation includes data and analysis to assess the effectiveness of TVP in managing energy demand and promoting energy efficiency.

PRESENTATION OBJECTIVE Explain key methodological changes in TVP Year 3 results and updated findings.

AI summary The presentation objective is to explain key methodological changes in TVP Year 3 results and updated findings, focusing on the analysis of Time-Varying Pricing (TVP) strategies and their impact.

Overview of Methodology - TOU Comparing participants' electricity consumption during TVP to their own consumption before TVP , and using a control group to subtract any changes in consumption that is not due to the TVP pilot (e.g. differen...

AI summary The methodology compares electricity consumption of TVP participants before and after implementation, using a control group of non-TVP participants with similar consumption, location, and program participation to account for external factors like weather and economic changes.

Overview of Methodology - CPP General idea: Same as TOU, except that event days are compared to reference days (days with similar weather when no events were called)

AI summary The methodology for Critical Peak Pricing (CPP) is similar to Time-Varying Pricing (TVP), with event days compared to reference days that have similar weather but no events. This approach helps assess the impact of pricing events on energy consumption.

Pilot Enrollment Active Participants Tariff End of Phase 2 Winter Beginning of Phase 3 Winter End of Phase 3 Winter Participants Who Completed Year 3 Residential TOU 891 2,396 2,241 93.5% Residential CPP 373 950 922 97.1% The percentage of...

AI summary The pilot enrollment data shows that the percentage of participants exiting the Residential CPP tariff is slightly lower compared to the Residential TOU tariff, with 97.1% of Residential CPP participants completing Year 3 versus 93.5% for Residential TOU.

TOU Impacts – Load During Peak Morning Peak Evening Peak Parameters Year 1 Year 2 Year 3 All Year 1 Year 2 Year 3 All Average Load Reduction During Peak Hours (kW) 0.218 ± 0.071 0.193 ± 0.109 0.078 ± 0.038 0.154 ± 0.033 0.253 ± 0.055 0.167...

AI summary The table shows load reduction during peak hours for TOU participants across different years. Participants enrolled in Year 3 have significantly less savings compared to those in Year 1 and 2. The average load reduction and relative savings are presented for both morning and evening peak hours.

TOU Impacts – Load During Peak De-electrified

AI summary The document section 'TOU Impacts – Load During Peak' includes figures related to de-electrified load during peak times. It appears to focus on the impact of Time-Varying Pricing (TVP) strategies on load management during peak periods.

TOU Impacts – Energy Usage Parameters Steady Electric Electrified De-electrified Steady Non-electric All Winter Non-Holiday Weekdays Average Daily Electricity Savings (kWh/day) 1.653 ± 0.304 5.702 ± 2.664 -4.795 ± 2.886 -2.456 ± 0.865 1.48...

AI summary The document presents data on the impact of Time-of-Use (TOU) pricing on energy usage for different participant categories. It shows average daily electricity savings and consumption levels during winter non-holiday weekdays and summer days, with statistically significant annual savings of 359 kWh across all TOU participants.

Bill impacts compare participant's old energy consumption patterns with their standard residential tariff to their new energy consumption patterns and TVP tariff. Parameters Winter Non- Holiday Weekdays Winter Weekends and Holidays Winter...

AI summary The document compares the energy consumption patterns and bill impacts of participants under a standard residential tariff versus a Time-Varying Pricing (TVP) tariff. On average, TOU participants saved approximately $87 annually, with varying savings across different seasons and days of the week.

TOU Bill Impacts Parameters Steady Electric Electrified De-electrified Steady non electric Average Bill Savings per Day ($/day) 0.186 ± 0.112 0.539 ± 0.225 -0.189 ± 0.334 0.107 ± 0.100 Average Bill per Day– TOU Participants, Pre-Pilot ($/d...

AI summary The table compares average daily bill savings for different heating scenarios under TOU pricing. Electrified scenarios show the highest savings, while de-electrified scenarios show negative savings. The data highlights the impact of TOU pricing on bill savings for different customer types.

Morning Events Evening Events Parameters Steady Electric Electrified De electrified Steady Non Electric Steady Electric Electrified De electrified Steady Non Electri c Average Load Reduction During CPP Events (kW) 0.871 ± 0.258 0.490 ± 0.5...

AI summary The table compares load reduction during Capacity-Based Pricing (CPP) events for different scenarios, showing that electrified and de-electrified scenarios have varying impacts on average load reduction. The analysis suggests that space heating scenarios have a more limited impact in CPP due to both reference and event days being in the post period.

CPP (n=10) For each participant-event, a regression is used to adjust the reference day consumption to correspond to the weather of the event day.

AI summary The document discusses the use of regression analysis to adjust reference day consumption based on the weather of the event day for each participant-event in the CPP (Critical Peak Pricing) program.

Commercial TVP Yields Inconclusive Results - › Savings are not statistically significant for load during peak, energy savings nor billing impacts. - › TOU participants appear to have made small changes to their energy consumption patterns...

AI summary The analysis of Commercial Time-Varying Pricing (TVP) shows that savings during peak periods, energy savings, and billing impacts are not statistically significant. Participants adjusted consumption slightly during morning and evening peaks, but not enough to achieve significant load reductions, and no correlation was found between CPP peak events and electricity usage changes.

TOU Impacts Savings seem to increase during the peak periods, but are not statistically significant Winter Non-holiday Weekday Load Shapes, Comm. TOU

AI summary The analysis of Time-of-Use (TOU) pricing indicates that savings increase during peak periods, although these increases are not statistically significant, as observed in winter non-holiday weekday load shapes for commercial TOU.

CPP Impacts › No correlation between the timing of the event and the times at which hourly savings are positive CPP Event and Reference Days Load Shapes, Days with AM Event Only CPP Event and Reference Days Load Shapes, Days with AM and PM...

AI summary The text discusses the lack of correlation between the timing of the Critical Peak Pricing (CPP) event and the times when hourly savings are positive. It references load shapes for days with AM events only and days with both AM and PM events, supported by figures.

TOU and CPP Bill Impacts › Commercial TOU participants saw their bill increase by 8% while CPP participants' bills decreased by 11%. These changes were not statistically significant.

AI summary Commercial Time-Varying Pricing (TVP) participants experienced an 8% increase in their bills, while Critical Peak Pricing (CPP) participants saw a decrease of 11%. However, these changes were not statistically significant.

Draft List of Proposed MURB TOU Tariff Evaluation Metrics • In its Decision on the 2024/25 Application, the Board directed NS Power: - Slides 32 and 33 provide an overview of NS Power's evaluation metrics approach and proposed MURB TOU Pil...

AI summary The Board directed NS Power to provide an overview of its evaluation metrics approach and proposed MURB TOU Pilot Tariff metrics. NS Power is seeking stakeholder input and will file its list of proposed metrics by December 31, 2024.

MURB TOU Tariff Evaluation Metrics Approach - Evaluation, measurement and verification (EM&V) plans are roadmaps for maximizing the learnings from pilot or program deployments - o EM&V plans aim to clearly articulate the goals of the progr...

AI summary NS Power plans to file a single EM&V report by July 31, 2025, including the existing TVP Tariffs and the new MURB TOU Pilot Tariff. The report will use metrics from prior evaluations and include new metrics like revenue impact and demand charge impact to meet Board directives and Consensus Agreement commitments.

Proposed MURB Pilot Tariff Evaluation Metrics Category Measurement Metric Definition Change in load during peak periods (kW) The average load reduction determined by the regression for winter morning peak, winter evening peak, winter mid-p...

AI summary The document outlines proposed evaluation metrics for a MURB pilot tariff, focusing on load impact, billing impact, and elasticity measures. It includes metrics such as load reduction during peak periods, average electricity savings, bill savings, demand charge comparisons, and elasticity measurements to assess the effectiveness of the tariff.

- NS Power will distribute a revised proposed 2024/25 Areas of Focus Work Plan in January, following stakeholder input, which will include anticipated Technical Sessions and Timelines Session & Timeline Summary of 2024/25 Areas of Focus &...

AI summary NS Power plans to distribute a revised 2024/25 Areas of Focus Work Plan in January after stakeholder input. The plan includes technical sessions and timelines, such as the annual TVP development cycle and the filing of MURB TOU Pilot Tariff evaluation metrics by December 31, 2024.

TBD following stakeholder feedback & input (revised work plan will be distributed in January 2025) 1.0 – Demand Charges (1.1) evaluate the extent to which the demand charge may act as a barrier to • General class TOU participation and cont...

AI summary The draft 2024/25 Areas of Focus Work Plan outlines the evaluation of demand charges as a potential barrier to Time-Varying Pricing (TVP) participation, including assessments of their impact on General Service customers and evaluations of modifications or alternatives for TVP offerings.

Draft 2024/25 Areas of Focus Work Plan (3/5) Session & Timeline Summary of 2024/25 Areas of Focus & Board Directives Type Items to be Discussed/Reviewed 2.0 – Potential Tariff Changes / Introductions (2.1) identify potential tariff changes...

AI summary The document outlines a 2024/25 work plan focusing on potential tariff changes, particularly exploring improvements to the Time-Varying Pricing (TVP) program to enhance customer participation, load shifting, and alignment with peak system hours.

Draft 2024/25 Areas of Focus Work Plan (5/5) Session & Timeline Summary of 2024/25 Areas of Focus & Board Directives Type Items to be Discussed/Reviewed TBD following stakeholder 6.0 – Review of System Planning Related Values • (6.1) revie...

AI summary The 2024/25 Areas of Focus Work Plan includes a review of system planning related values, such as avoided costs and Effective Load Carrying Capability (ELCC), as they apply to Time-Varying Pricing (TVP). The plan also involves assessing the alignment of TVP pricing with avoided costs and analyzing the correspondence between system margin forecasts and CPP events.

Other Board Directives for 2024/25 As part of the Board's Decision in M11822 (2024/25 TVP Application), NS Power will also: • Report on the Year Four findings and file the annual EM&V Report no later than 31 Jul 2025 As part of the Board's...

AI summary NS Power is required to report on Year Four findings and file an annual EM&V Report by July 31, 2025, as per the Board's Decision in M11822. Additionally, NS Power must analyze system margin forecasts and CPP events, review marketing efforts, assess performance of General Service Class customers, and potentially revise incentive structures for commercial TVP tariffs based on stakeholder feedback.

As part of its Year Four Report, NS Power will: - Following the completion of the Year 4 pilot, NS Power will develop and provide to stakeholders an examination of the commercial class customer characteristics (load shape, magnitude, busin...

AI summary NS Power will analyze the characteristics of commercial customers in the TVP pilot to improve outreach to small businesses, maintain TVP reporting processes, file annual EM&V reports, and engage with MURB stakeholders on incentives and rebates to support TVP adoption.

Near Term Next Steps - Fri, 22 Nov NS Power circulated slides - Today (Wed, 27 Nov) Kick-off TVP Development Cycle (2024/25) Session - Thu, 12 Dec stakeholders provide comments on draft 2024/25 Areas of Focus Work Plan and the proposed lis...

AI summary The document outlines near-term next steps in the development of Time-Varying Pricing (TVP) for the 2024/25 cycle, including stakeholder engagement, submission of evaluation metrics, and planning for technical sessions.

Rate Design Scorecard Rubric Item Objective 0 - Does Not Meet Objectives 1 - Meets Some Objectives 2 - Meets Most Objectives 3 - Meets All Objectives Customer Orientation The Tariff should be oriented to customers, maintaining simplicity w...

AI summary The Rate Design Scorecard Rubric evaluates tariffs based on customer orientation, focusing on simplicity, pricing differentials, and rate choice. It uses a scoring system from 0 to 3 to assess how well a tariff meets these criteria.

Introduction - On November 27, 2024, NS Power held a TVP session to formally kick off the 2024/25 TVP engagements - Included on the agenda were a review of the Year Three Evaluation Report results, the proposed list of multi-unit residenti...

AI summary NS Power initiated the 2024/25 Time-Varying Pricing (TVP) engagements with a session in November 2024. The agenda included reviewing the Year Three Evaluation Report, discussing proposed metrics for a MURB Time-of-Use (TOU) Pilot Tariff, and presenting the draft 2024/25 Areas of Focus Work Plan. Comments from the Consumer Advocate and Energy Storage Canada were received in December 2024 and incorporated into revisions of the work plan. NS Power plans to hold three Technical Sessions in early 2025.

Technical Session 1 – to be scheduled (week of 24 February 2025) Summary of 2024/25 Areas of Focus & Board Directives Type Items to be Discussed/Reviewed 1.0 – Accessibility of TVP (1.1) Review of accessibility as applicable to • vulnerabl...

AI summary The document outlines the focus areas and directives for Technical Session 1, which will be scheduled for the week of 24 February 2025. Key topics include reviewing the accessibility of Time-Varying Pricing (TVP) for vulnerable customers, exploring mechanisms for TVP revenue stability, refining MURB TOU Pilot Tariff, and assessing metering and billing system capabilities.

3.0 – Demand Charges • (3.1) evaluate the extent to which the demand charge may act as a barrier to General class TOU participation and continue to evaluate non-demand TVP designs for General Service customers • (3.2) assessment of demand...

AI summary The text discusses the evaluation of demand charges as a potential barrier to TOU participation for General Service customers, the impact of demand charges on customer bills, and the need to recover only specific demand-related costs through non-coincident demand charges. It also mentions assessing whether demand charges increase bills for customers shifting load to off-peak hours.

Technical Session 2 (continued) – anticipated mid-March Summary of 2024/25 Areas of Focus & Board Directives Type Items to be Discussed/Reviewed 4.0 – Reporting on Small Business Customer Items • (4.1) report to stakeholders on changes tha...

AI summary The session focuses on reporting to stakeholders about changes to help small business customers determine if they will benefit from time-varying pricing (TVP). Topics include analyzing load characteristics, customer recruitment, classification by business sector, and addressing customer reluctance to participate in TVP.

Technical Session 3 – anticipated late-April Summary of 2024/25 Areas of Focus & Board Directives Type Items to be Discussed/Reviewed 5.0 – Potential Tariff Changes / Introductions • (5.1) identify potential tariff changes which could impr...

AI summary The document outlines potential tariff changes for 2024/25, including adjustments to Time-Varying Pricing (TVP) to improve customer participation, examination of new tariffs for behind-the-meter energy storage, and the development of weekend-inclusive TOU tariffs. These changes aim to align customer behavior with system peak hours and evaluate the impact of various rate structures on energy storage use cases.

Technical Session 3 (continued) – anticipated late-April Summary of 2024/25 Areas of Focus & Board Directives Type Items to be Discussed/Reviewed 6.0 – Review of System Planning Related Values • (6.1) review of system planning related valu...

AI summary The document outlines the 2024/25 focus areas for the Board, including a review of system planning values related to Time-Varying Pricing (TVP), such as avoided costs and Effective Load Carrying Capability (ELCC). It discusses the alignment of TVP pricing with avoided costs and the implications of system margin forecasts and CPP events in the Year 4 report.

Comments Received December 2024 Responses Circulated January 30, 2025 Stakeholder Comment NS Power Response Consumer Advocate (CA) Results Reported for Year Three • suggests that in future evaluation reports NSP restate the initial objecti...

AI summary The Consumer Advocate suggests that NS Power should restate initial objectives in future evaluation reports and provide summary comments on whether the TVP program is meeting its goals. NS Power agrees and will include this information in the Year Four Evaluation Report. The CA also requests that participant numbers be included in results summaries, which NS Power notes are available in the TVP Year Three Report (M11823).

& lt;sup>2 For an example of such a jurisdictional scan see Appendix F to BC Hydro's 2024 Rate Design Application, doc 77681 b-1-1-bch-2024-ratedesign-appendices.pdf

AI summary The text references an example of a jurisdictional scan from BC Hydro's 2024 Rate Design Application, found in Appendix F of the document.

Stakeholder Comment NS Power Response jurisdictional scan (in Appendix F of BC Hydro's 2024 Rate Design Application) lists NS Power in its review of residential TVP tariff offerings by utility. Further, it provides a recent (February 2024)...

AI summary The document discusses NS Power's response to a jurisdictional scan included in BC Hydro's 2024 Rate Design Application, which reviews residential TVP tariff offerings. NS Power finds the report informative but has not planned a similar scan as part of its 2024/25 work plan.

Stakeholder Comment NS Power Response Consumer Advocate (CA) • The Company recognizes that some renters may encounter unique challenges, in part due to having less control over items such heating sources, or appliance selection, which may...

AI summary The Consumer Advocate highlights that renters may face unique challenges in controlling energy usage, leading to higher electricity bills. Time-Varying Pricing (TVP) is noted as a mechanism that provides renters flexibility to reduce their electricity costs.

Consumer Advocate (CA) 2024/25 Areas of Focus Work Plan – Reporting on Small Business Customer Items • Has NS Power looked at the general load characteristics of residential customers that may shift load in response to TVP? Could similar w...

AI summary The Consumer Advocate is inquiring whether NS Power has analyzed residential load characteristics in response to Time-Varying Pricing (TVP) and whether similar studies could be conducted for residential customers as planned for small businesses. NS Power notes that certain residential segments, such as TOU and electrified customers, have shown load shift, while small business groups have not demonstrated significant load shift.

Objectives and Methodology The following report provides the results of the first phase of research for the 2021 Time Variable Pricing Study conducted on behalf of Nova Scotia Power. Specifically, this version of the report includes only t...

AI summary This report outlines the first phase of research for the 2021 Time Variable Pricing Study conducted by Nova Scotia Power. It focuses on business customer perceptions of Time of Use (TOU) and Critical Peak Pricing (CPP) rate plans. A total of 400 responses were collected from 7,643 invited business customers, with a 5% response rate. The findings will inform the development of a pilot program and subsequent research phases.

Summary of Key Findings

AI summary The summary of key findings highlights the analysis of the impact of Time-Varying Pricing (TVP) on electricity demand and the effectiveness of Conservation Program Providers (CPP) in reducing energy consumption, particularly in Multi-Unit Residential Buildings (MURB). The findings also discuss the role of Effective Load Carrying Capability (ELCC) in grid reliability and the potential benefits of Time-of-Use (TOU) pricing models.

Summary of Key Findings The following highlights are derived from the business customer results from Phase 1 of the 2021 Time Variable Pricing Study: Of note, a significant minority of customers are unsure how they are currently being bill...

AI summary A significant minority of business customers are unsure about their current billing methods, and many are not familiar with their rate plans. While over one-third know about Time of Use, nearly half are interested in Time Variable Pricing programs, particularly for potential cost savings. However, they are concerned about higher costs during peak times.

Rate Information and Time Variable Pricing As noted, four in ten customers express being unsure what rate they are currently on, and overall, customers express a low level of familiarity with their current rate structure. Moreover, two in...

AI summary The document highlights customer confusion regarding current rate structures, with many customers unsure of their rate and some misidentifying their rate. Only a third of business customers are familiar with Time of Use Rate Plans, though nearly half show interest in Time Variable Pricing programs.

Time of Use Looking at the Time of Use plan specifically, four in ten business customers express a high likelihood of participating in such a plan if it became available. On average, customers would be looking to save 24% of their annual p...

AI summary The Time of Use plan has potential with 40% of business customers likely to participate, requiring average savings of 24% on their annual power bill. Customers appreciate cheaper rates and environmental benefits, but concerns include higher costs during peak times and the need to change business practices.

Critical Peak Pricing Looking at the Critical Peak Pricing plan specifically, just fewer that four in ten business customers express a high likelihood of participating in such a plan if it became available. Once again, customers would be l...

AI summary The Critical Peak Pricing plan has mixed customer reactions, with fewer than 40% of business customers likely to participate. While some value the potential for savings and environmental benefits, others dislike increased costs during peak times and the need to change business practices.

Preferred Rate Plan Of the two concepts evaluated, Time of Use garners greater preference among customers. Overall, one-quarter indicate a preference for Time of Use when asked to choose, while one in ten prefer the Critical Peak Pricing o...

AI summary The Preferred Rate Plan analysis shows that Time of Use is more preferred by customers compared to Critical Peak Pricing. One-quarter of customers prefer Time of Use, while one in ten prefer Critical Peak Pricing. A similar proportion are indifferent, not interested, or want more information before deciding.

Preferred Rate Plan (Continued) Among those who prefer the Time of Use plan, the predominant reason is because it will provide more benefits and savings . Meanwhile, those who prefer the Critical Peak Pricing concept most commonly mention...

AI summary The text discusses customer preferences for Time of Use and Critical Peak Pricing rate plans, highlighting reasons for preference such as cost savings and flexibility. It also notes communication preferences, with email being the most preferred method, and mentions other channels like the NSP website and bill attachments.

More than one-half of customers use electric heat as their primary heat source in their business, while two in ten use oil. Electric heat is greater among customers with fewer employees, and customers in buildings under 2,500 square feet....

AI summary More than half of customers use electric heat as their primary heat source in their business, while two in ten use oil. Electric heat is more common among customers with fewer employees, smaller buildings, e-billing customers, newer buildings, businesses in the Western region, and certain business types and rate classes.

Likelihood of Installing Smart Thermostat Among customers without automated heating, one-third express a high likelihood of installing a smart thermostat in the next three years. Although a minority, this result suggests that smart thermos...

AI summary Among customers without automated heating, one-third are likely to install a smart thermostat within three years. Higher likelihood is seen in non-B2B businesses, small businesses, newer buildings, and those on rate code 11. However, small sample sizes in some subgroups require caution in interpreting these differences.

Confirming assumptions, many customers are unsure what rate plan they are on. Approximately three in ten each report being on Small General billing (Rate 10) , and General Demand billing (Rate 11). Comparatively, only one percent report be...

AI summary The text highlights that many customers are unsure of their rate plan, with a significant portion on Small General (Rate 10) and General Demand (Rate 11) billing. A large percentage of business customers are uncertain, and there are notable discrepancies in self-reported rate codes. Uncertainty is higher in certain customer segments, such as those on electric heat, smaller businesses, and newer buildings.

Overall, business customers express limited familiarity with their current rate. Notably, only two in ten indicate that they are highly familiar with their current standard rate, while customers overall provide a mean score of four on a te...

AI summary Business customers show limited familiarity with their current rate, with only 20% indicating high familiarity and over 50% expressing unfamiliarity. Familiarity varies based on factors like billing method, business size, industry type, and geographic location.

Overall, more than one-third of customers express a high level of familiarity with the Time of Use rate plan concept. Customers express a varying degree of familiarity with the Time of Use plan with more than one-third of customers indicat...

AI summary More than one-third of customers are highly familiar with the Time of Use rate plan, while 45% have a low level of familiarity. Familiarity is lowest among B2B customers and highest among those with larger homes and newer buildings.

Interest in Time Variable Pricing Following a brief description, there is a relatively high level of interest in the general concept of Time Variable Pricing, with just under one-half expressing interest. Customers were provided with a bri...

AI summary The text discusses customer interest in Time Variable Pricing (TVP), with 47% expressing high interest. Interest is higher among Cape Breton customers, service-based businesses, larger buildings, and newer buildings. The analysis includes data from Table 21 and associated figures.

Likelihood of Participating in Time of Use Plan Customers were then provided a description of the proposed Time of Use Plan, overall four in ten express likelihood of participating in the new plan. Overall, there is a relatively high level...

AI summary A survey indicates that 40% of customers are likely to participate in a proposed Time of Use Plan. Interest is highest among businesses and newer buildings. Customers were presented with Time of Use and Critical Peak Pricing options in random order to avoid bias. Participation likelihood in Time of Use is lower for Critical Peak Pricing.

Savings Required (Time of Use) Customers would need to save 24%, on average, on their bill each year to make the Time of Use plan worthwhile to them. Business customers were next asked the proportion of their electrical bill they would nee...

AI summary The analysis shows that, on average, customers would need to save 24% on their annual bill to find the Time of Use plan worthwhile. A third of customers would require savings between 0-15%, nearly half would need 16-30%, and 18% would need 31% or more. These savings requirements are consistent across customer demographics.

Likes and Dislikes of Time of Use Customers most like the chance to save money on the Time of Use rate plan, while a variety of dislikes are mentioned by a small proportion each. Unaided, customers most frequently mention liking the chance...

AI summary Customers appreciate the opportunity to save money through Time of Use rate plans, but some dislike the lack of flexibility and the need to adjust their energy use. A small proportion also mention issues such as peak times aligning with their highest usage and insufficient information on peak hours.

Likes and Dislikes of Time of Use (Continued) Customers were once again asked what they liked and disliked about the Time of Use concept, this time prompted with options to choose from. Most commonly, customers like that they could save mo...

AI summary Customers were surveyed on their likes and dislikes of Time of Use (ToU) pricing. Most appreciate the potential to save money and reduce environmental impact, while many dislike higher costs during peak times and the difficulty of adjusting usage habits.

Critical Peak Pricing

AI summary The document discusses the implementation and evaluation of Critical Peak Pricing (CPP) as a demand response strategy. It includes visual representations of data and analysis related to the effectiveness and impact of CPP on energy consumption and cost management.

Customers were provided a description of the proposed Critical Peak Pricing rate plan. Overall, more than one-third express a high likelihood of participating. There is near identical likelihood that business customers would participate in...

AI summary Customers were provided with descriptions of the proposed Critical Peak Pricing rate plan and Time of Use plan. More than one-third of customers expressed a high likelihood of participating in the Critical Peak Pricing plan, with similar participation likelihoods observed between business customers for both plans. Interest was higher among non-MURB businesses and those in newer buildings.

Savings Required (Critical Peak Pricing) Customers would need to save 25%, on average, on their bill each year to make the Critical Peak Pricing plan worthwhile. Business customers were next asked the proportion of their electrical bill th...

AI summary The Critical Peak Pricing plan requires customers to save 25% on average annually for it to be worthwhile. Business customers' savings expectations vary, with one-third needing to save 0-15% and 19% expecting to save 31% or more. Smaller businesses (fewer than 40 employees) require a higher proportion of savings.

Likes and Dislikes of Critical Peak Pricing Unaided, customers most like the chance to save money on their electricity bill, while most dislike the perception that peak rates are too high. Most commonly, one-third of customers note liking...

AI summary Customers most like the opportunity to save money through Critical Peak Pricing, but many dislike the perception that peak rates are too high. One-third of customers prefer cheaper rates, while three in ten dislike the concept entirely. These findings are consistent with residential results and are based on coded verbatim customer comments.

Likes and Dislikes of Critical Peak Pricing (Continued) Customers were once again asked what they liked and disliked about the Critical Peak Pricing concept, this time prompted with options to choose from. Most commonly, customers like tha...

AI summary Customers were surveyed on their opinions about Critical Peak Pricing. Two-thirds liked the potential to save money, while others expressed concerns about higher costs during peak times and the need to change their behavior. Over half disliked the increased costs during peak hours and the lack of flexibility in adjusting power usage.

Preferred Rate Plan

AI summary The document discusses the Preferred Rate Plan, which involves the development and implementation of a rate structure that aligns with regulatory guidelines and stakeholder interests. It includes discussions on rate design, cost recovery, and affordability considerations.

Preferred Rate Plan Between the two rate plans proposed, customers express greater interest in the Time of Use plan overall, though two in ten are equally interested in both. More specifically, one-quarter of customers select the Time of U...

AI summary Customer interest in the Time of Use plan is higher than in the Critical Peak Pricing plan, with one-quarter of customers selecting Time of Use as most of interest. Preferences are similar across demographics, but some groups, such as electrically heated customers and those in newer buildings, are more likely to need additional information.

Reasons for Greater Interest in Time of Use Of those most interested in Time of Use, the main reason is because the plan will provide more benefits and savings, followed by mentions that it would be easier to implement and fit their schedu...

AI summary The main reasons customers are interested in Time of Use plans include potential benefits and savings, ease of implementation, greater control over energy consumption, and perceived superiority over Critical Peak Pricing. However, caution is advised when interpreting demographic subgroups due to small sample sizes.

Reasons for Greater Interest in Critical Peak Pricing Of those most interested in Critical Peak Pricing, the main reasons are because of potential cost savings and providing more control over their usage. Most commonly, one-quarter indicat...

AI summary The text discusses the reasons why customers are interested in Critical Peak Pricing, highlighting potential cost savings, lower rates, and greater control over energy usage as the main factors. A quarter of respondents prefer this plan for these benefits, while a smaller proportion find it more suitable for their business needs.

Reasons for Disinterest in Either Plan Customers not interested in either program provide a variety of reasons as to why, with a perceived lack of flexibility most commonly mentioned. Most commonly, customers express being not interested i...

AI summary A significant percentage of customers are not interested in either pricing plan, citing a lack of flexibility as the primary concern. Other reasons include minimal benefits, higher bills, peak usage times, complexity, and distrust in NSP. Caution is advised when interpreting demographic subgroups due to small sample sizes.

Interest in Learning More Customers who express being interested in learning more before choosing between the two plans would most commonly like to see a cost breakdown of each option and better understand how each could save them money. O...

AI summary Customers interested in learning more about pricing programs want cost breakdowns, information on peak times and rates, impact assessments, side-by-side comparisons, and visual aids to help them make informed decisions. Caution is noted regarding the interpretation of some demographic subgroups due to small sample sizes.

PERS Operate Mon Tues Wed Thur Fri Prior to 7am 20% 20% 20% 20% 20% ľ 7am-9pm 87% 88% 89% 89% 88% After 9pm 17% 18% 18% 18% 17% Do not 5% 3% 1% 1% 2%

AI summary The document contains two figures, one showing operational percentages at different times of the day and another depicting an unspecified chart. The first figure outlines percentages for operations before 7am, between 7am and 9pm, and after 9pm, with varying values across days of the week. The second figure is not described in detail.

Temperature Control Systems One-half of customers have a regular thermostat for their main heating system, while three in ten have a programmable thermostat. Smart thermostats are uncommon among customers, only being mentioned by one in te...

AI summary The document discusses thermostat usage among customers, noting that programmable thermostats are more common than smart thermostats. Smart thermostats are particularly prevalent among customers with heat pumps. The data is relevant to TVP rate plans and shows similar trends to 2019, though the sample was limited to electric heat customers in 2021.

Reason for Interest in Installing Smart Thermostat Among customers expressing a high likelihood of installing a smart thermostat, interest is primarily related to electricity savings. Among customers interested in installing a smart thermo...

AI summary Customers interested in installing smart thermostats are primarily motivated by the potential for electricity savings, particularly those with electric heat. This interest is higher among older customers and those living in mobile homes, who may benefit more from reduced electricity costs.

Rate Type Not surprisingly, most customers indicate being billed using the standard rate, with Time of Use and Net Metering billing being much less common. Of note, one in six customers were unsure which type of billing they were currently...

AI summary Most customers are billed using the standard rate, while Time of Use and Net Metering billing are less common. One in six customers are unsure of their billing type, particularly younger customers, those in condos/apartments, and those unfamiliar with Time of Use programs.

Customers overall express a low level of familiarity with the existing Time of Use plan. Perhaps not surprising as few customers are on the Time of Use plan offered by Nova Scotia Power, customers overall express a relatively low level of...

AI summary Customers show low familiarity with Nova Scotia Power's Time of Use plan, with only 25% expressing high familiarity and an equal proportion being not at all familiar. Familiarity is higher among those using electricity for heating, higher income earners, and men.

Following a brief description, there is a relatively high level of interest in the general concept of Time Variable Pricing, with more than one-half expressing interest. Customers were provided with a brief description of the TVP concept a...

AI summary A significant portion of customers (over one-half) expressed high interest in Time Variable Pricing (TVP) after a brief description. Interest correlates with higher household income and familiarity with existing Time of Use (TOU) rate plans, while it is lowest among condo/apartment residents.

Following a more detailed description of the TVP program, customers express even greater interest. Following a more detailed description of the rate plan, including more information regarding potential savings if electricity consumption ha...

AI summary Following a more detailed description of the TVP program, customer interest increased significantly, with two-thirds expressing interest compared to 56% previously. Interest is higher among e-billing customers, high-income households, and those familiar with the Time of Use rate program.

Time of Use

AI summary The text discusses the implementation of Time of Use (TOU) and Critical Peak Pricing (CPP) programs, focusing on their impact on customer behavior and energy consumption patterns. The content includes visual representations of data related to these programs.

Customers were provided a description of the proposed Time of Use Plan, overall one-half express likelihood of participating in the new plan. Overall, there is a great deal of interest in participating in the proposed Time of Use plan, wit...

AI summary The proposed Time of Use (TOU) plan has generated significant interest, with half of customers expressing a high likelihood of participation. Customers familiar with the existing TOU plan and those living in townhouses show higher participation likelihood. The plan was presented as Option A and B, but in a randomized order to avoid bias.

Likes and Dislikes of Time of Use Customers most like the chance to save money on the Time of Use rate plan, while a variety of dislikes are mentioned by a small proportion each. Unaided, customers most frequently mention liking the chance...

AI summary Customers appreciate the potential to save money through Time of Use (TOU) rate plans, with some valuing control over electricity charges. Dislikes include high peak rates and the need to adjust energy consumption habits. These findings are based on customer feedback collected and categorized from open-ended responses.

Likes and Dislikes of Time of Use (Continued) Customers were once again asked what they liked and disliked about the Time of Use concept, this time prompted with options to choose from. Most commonly, customers like that they could save mo...

AI summary Customers were surveyed on their preferences regarding Time of Use (TOU) pricing. Two-thirds liked the potential to save money, while over half disliked higher costs during peak times. Many also appreciated environmental benefits and increased control over their bills, though some disliked the need to change behavior to save money.

Critical Peak Pricing

AI summary The document discusses Critical Peak Pricing (CPP), a time-based rate structure designed to manage electricity demand during peak periods. It includes visual elements such as images that may illustrate aspects of CPP implementation or its impact on consumers.

Customers were provided a description of the proposed Critical Peak Pricing rate plan. Overall, one-third express a high likelihood of participating. Overall, there is lesser interest in participating in the proposed Critical Peak Pricing...

AI summary Customers were presented with the proposed Critical Peak Pricing (CPP) rate plan, and one-third expressed a high likelihood of participation. Interest in CPP was lower compared to the Time of Use (TOU) plan, though participation likelihood was consistent across demographics.

Likes and Dislikes of Critical Peak Pricing Unaided, customers most like the chance to save money on their electricity bill, while most dislike the perception that peak rates are too high. Most commonly, one-third of customers note liking...

AI summary Customers like the potential to save money through Critical Peak Pricing (CPP), but many dislike the high peak rates. One-third of customers like cheaper rates, while one-third dislike the high rates. These findings are based on verbatim customer comments that were categorized.

Likes and Dislikes of Critical Peak Pricing (Continued) Customers were once again asked what they liked and disliked about the Critical Peak Pricing concept, this time prompted with options to choose from. Most commonly, customers like tha...

AI summary Customers were asked about their preferences regarding Critical Peak Pricing (CPP). Most appreciate the potential for savings and lower rates, while concerns include higher costs during peak times and the need to change behavior. Some customers feel they cannot adjust their usage, though few are unwilling to do so.

Preferred Rate Plan

AI summary The document discusses the Preferred Rate Plan, including visual elements such as images related to the topic. It appears to be part of a regulatory proceeding involving rate structures and customer programs.

Between the two rate plans proposed, customers express much greater interest in the Time of Use plan overall. More specifically, four in ten customers select the Time of Use plan as being most of interest to them, while only one in ten sel...

AI summary Customers show significantly higher interest in the Time of Use (TOU) plan compared to the Critical Peak Pricing (CPP) plan. Four in ten customers find the TOU plan most of interest, while only one in ten find the CPP plan most of interest. Interest in the TOU plan increases with income and among e-billing customers, and familiarity with the existing TOU plan correlates with higher interest.

Reasons for Greater Interest in Time of Use Of those most interested in Time of Use, the main reason is because it is easier to implement into their schedule. Most commonly, three in ten indicate their preference for the Time of Use plan b...

AI summary The main reason customers are interested in Time of Use (TOU) plans is that they are easier to implement into their schedule. Three in ten customers prefer TOU for this reason, while others cite more control over consumption, price, and better savings. Oil heat users are more likely to mention control over consumption.

Of those most interested in Critical Peak Pricing, the main reason is for the potential cost savings. Most commonly, one-third indicate their preference for the Critical Peak Pricing plan because of its potential cost savings and lower rat...

AI summary The text discusses customer preferences for Critical Peak Pricing, highlighting that one-third prefer it for potential cost savings and lower annual rates, while others cite factors like peak events occurring only during certain months and greater control over usage. Younger residents are more likely to prioritize cost savings and the limited duration of peak events.

Reasons for Disinterest in Either Plan Customers not interested in either program provide a variety of reasons as to why, with minimal savings being most common. Most commonly, customers express being not interested in either pricing plan...

AI summary Customers not interested in either pricing plan cite minimal savings as the most common reason, followed by concerns about higher bills, preference for current plans, distrust in NSP, peak usage times, and complexity of the plans.

Interest in Learning More Customers who express being interested in learning more before choosing between the two plans would most commonly like to see a cost breakdown of each option and better understand how each could save them money. O...

AI summary Customers interested in learning more about pricing programs want a cost breakdown and visual aids to understand how each plan could save them money. Nova Scotia Power plans to provide a savings calculator to help customers choose the right plan. These preferences are consistent across demographics, though some subgroups have small sample sizes.

Required Savings On average, customers are looking to save more than $300 per year to make the programs worthwhile to them, though a majority would take part in order to save less than $300. Regardless of a customer's interest in the progr...

AI summary The text discusses customer expectations for savings from energy programs, noting that on average, customers expect to save around $381 annually, with variations based on interest in specific programs and demographics. Customers with electric heat or heat pumps, and larger households, require higher savings to participate.

- Added footnote on CPP applications \ Please note: In some cases, one (1) application may have been submitted for multiple SMB accounts

AI summary A footnote was added regarding Critical Peak Pricing (CPP) applications, noting that in some cases, a single application may have been submitted for multiple SMB accounts.

- Updated Year 4 Results, see table below: Results (previously shared) Year 4 Year 4 Results (updated) Enrolment Target 500 TOU / 500 CPP 1,000 TOU / 1,000 CPP Applications Received 0 TOU / 26 CPP 0 TOU / 26 CPP Pilot Enrolment 54 TOU / 53...

AI summary The updated Year 4 results show that the enrolment target for the Time of Use (TOU) and Critical Peak Pricing (CPP) programs has doubled to 1,000 each, but the percentage of the target achieved has decreased from 11% to 5% for both programs. Applications received remain unchanged at 0 TOU and 26 CPP.

- Updated table with numbers, fixed error and updated now with the most recent data (as of March 4, 2025), see table below: (previously shared table) TOU (Rate 80, 81) CPP (Rate 70, 71) Residential Tota l Enrollment Target 7,000 3,500 10,5...

AI summary The table presents updated enrollment data for Time of Use (TOU) and Critical Peak Pricing (CPP) programs as of March 4, 2025. It includes enrollment targets, new applications, accepted applications, and current enrollment numbers for residential customers.

Ongoing Pricing Innovation Process - Analytics-based : using 15-minute cloud scale analytics data to model 1 - Tariff Optimization Model - Rate Design Scorecard - Collaboration-focused : collaboration with Regulatory Intervenors and Custom...

AI summary The Ongoing Pricing Innovation Process involves analytics-based modeling, stakeholder collaboration, and alignment with resource planning initiatives. It includes tariff optimization, stakeholder engagement, customer feedback integration, and a phased approach to implementation.

Summary of 2024/25 Areas of Focus & Board Directives Туре Items to be Discussed/Reviewed 1.0 – Accessibility of TVP • (1.1) Review of accessibility as applicable to vulnerable customers (i.e. low-income) CA Examine the results of the Year...

AI summary The document outlines key areas of focus for the 2024/25 regulatory proceeding, including the accessibility of Time-Varying Pricing (TVP) for vulnerable customers, the review of TVP revenue stability mechanisms, refinement of the MURB TOU Pilot Tariff, and improvements to load reduction methodologies and metering systems. These discussions aim to enhance equity, accuracy, and effectiveness in TVP implementation.

Source of Income Data: - Existing income data is based on average income at the postal code level (sourced from Environics). As a result, income data is only indicative in broad metrics, and results from more granular analysis may not resu...

AI summary The source of income data for the proceeding is based on average postal code-level income from Environics, which is only indicative and may not reflect granular analysis. Self-reported income data is not reliable due to lack of verification and incomplete collection by Nova Scotia Power, limiting its use for analysis.

Other Income-Related Learnings - Through Nova Scotia Power's work with our customers and the NSP/CA/AEC Low-Income Working Group, the following learnings on rate design as it relates to income should be considered where possible in future...

AI summary Nova Scotia Power highlights income-related rate design considerations based on collaboration with the NSP/CA/AEC Low-Income Working Group. Key learnings include expanding enrolment windows, offering rate choice, and ensuring appropriate rate options for customers, especially during the heating season.

Accessibility of TVP Tariffs for Renters - TVP tariffs have been designed to provide customers with choice and flexibility – there are no restrictions for renters to join a TVP Tariff - Current TVP Tariffs are also designed to be technolog...

AI summary TVP tariffs are accessible to renters and designed to be technology agnostic. Customer surveys indicate that most participants have not installed new equipment since enrolling, and there has been a significant increase in apartment dwellers applying for the program compared to previous years.

Model Commentary TOU volumetric rates effective November 1, 2024 Includes 2025 riders AMI data domain: January 1 – December 31, 2024 inclusive Structural bill change = -1.2 % note that technical sessions filed in 2024/2025 application repo...

AI summary The Model Commentary outlines the implementation of TOU volumetric rates starting November 1, 2024, including 2025 riders. The AMI data domain spans the entire year of 2024, and a structural bill change of -1.2% is noted, with a technical session from the 2024/2025 application reporting a 0% change.

Small General, TOU - TOU volumetric rates effective November 1, 2024 - Includes 2025 riders - AMI data domain: January 1 December 31, 2024 inclusive - Structural bill change = +2.4% note that technical sessions filed in 2024/2025 applicati...

AI summary The document outlines TOU volumetric rates effective November 1, 2024, including 2025 riders. It mentions an AMI data domain from January 1 to December 31, 2024, and notes a structural bill change of +2.4%, contrasting with a -2.6% change reported in technical sessions from the 2024/2025 application.

General, TOU - TOU volumetric rates effective November 1, 2024 - Includes 2025 riders - AMI data domain: January 1 December 31, 2024 inclusive - Structural bill change = -0.1% note that technical sessions filed in 2024/2025 application rep...

AI summary The document outlines Time-of-Use (TOU) volumetric rates effective November 1, 2024, including 2025 riders. The AMI data domain is set from January 1 to December 31, 2024. A structural bill change of -0.1% is noted, though technical sessions in the 2024/2025 application reported a -0.2% change.

MURB, TOU - TOU volumetric rates effective November 1, 2024 - Includes 2025 riders - AMI data domain: January 1 December 31, 2024 inclusive - Structural bill change = -1.1% note that technical sessions filed in 2024/2025 application report...

AI summary The document outlines the implementation of Time-of-Use (TOU) volumetric rates effective November 1, 2024, along with 2025 riders. It references a structural bill change of -1.1% and notes that technical sessions in the 2024/2025 application reported a -1.7% change. AMI data is collected from January 1 to December 31, 2024.

Projected Benefit Proposed change Existing method Neighbourhood criteria Increased pool of potential Neighbourhood criteria to be based based on feeder and postal Control:Treatment matches will on region (i.e. Northern, Eastern, code combi...

AI summary The document discusses proposed changes to the Neighbourhood criteria and Heating classification in the TVP process. The proposed changes aim to increase the pool of potential participants by using feeder and postal code combinations and apply heating classification to all hours in the pre and post periods of TVP, using overnight off-peak hours for more accurate load impact results.

- Although these changes are not fully aligned with existing TVP program winter peak periods they remain a useful tool in calculating avoided costs. Season definitions used in Updated season definitions June 12, 2024 analysis Winter On-Pea...

AI summary The text discusses updates to season definitions used in the Tariff Variation Process (TVP) program, including changes to winter on-peak and off-peak periods, as well as non-winter periods. These changes are not fully aligned with existing TVP program winter peak periods but are noted as a useful tool in calculating avoided costs.

MURB TOU Pilot Tariff Updates - In the 2024/25 Areas of Focus Work Plan, NS Power included: "Any MURB rate adjustments or refinements will be proposed to the stakeholder's group once sufficient data is available and analysis has been compl...

AI summary NS Power plans to propose MURB rate adjustments once sufficient data is available, with mid-year results from the MURB TOU Pilot Tariff included in the Year Four Evaluation Report. Full results will be available in Year Five. Currently, 10 MURBs with 941 units are participating in the pilot.

Current Metering & Systems Capabilities - Current systems are built around existing standard offer rates with alternative rates requiring programming and testing to implement. - More complex rates that vary from the framework of existing t...

AI summary The current metering and systems capabilities are based on existing standard offer rates. Implementing alternative rates requires programming and testing, with complexity and scale affecting the effort required. Current TVP rates include CPP and TOU rates, which have varying levels of automation, while the MURB rate requires more manual intervention and further automation for scalability.

Potential Tools to Monitor Revenue Impacts - During the 2023/24 (Year 3) stakeholder engagements, NS Power provided a draft rate design scorecard that was reviewed with stakeholders and modified to reflect feedback and learnings captured t...

AI summary NS Power developed a rate design scorecard during 2023/24 stakeholder engagements to evaluate tariff options based on metrics like customer orientation, revenue neutrality, and accessibility. The company also set enrolment targets for TVP rates to manage demand response and analyze revenue impacts from TVP participants compared to those on standard tariffs.

Potential Tools to Monitor Revenue Impacts – Rate Design Scorecard Rubric Item Objective 0 - Does Not Meet Objectives 1 - Meets Some Objectives 2 - Meets Most Objectives 3 - Meets All Objectives Customer Orientation The Tariff should be or...

AI summary The text outlines a rubric for assessing the customer orientation of a tariff, focusing on simplicity, pricing differentials, and customer rate choice. The rubric evaluates tariffs on a scale from 0 to 3 based on how well they meet these criteria.

Enrolment targets are based off of the annual Demand Response targets as provided in the 2024 Load Forecast Report Rate Load Reduction per Customer (kW) Winter 2024/25 Targets Total Effective on Peak Reduction (MW) Residential TOU 0.1925 7...

AI summary Enrolment targets for demand response programs are derived from the 2024 Load Forecast Report, outlining specific load reduction targets for residential and MURB customers, including TOU and CPP programs, with corresponding peak reduction figures.

Enrolment targets are based off the annual Demand Response targets as provided in the 2024 Load Forecast Report Year TVP Rate(MW) 2024 2 2025 4 2026 12 2027 22 2028 32 2029 36 2030 35 2031 35 2032 34 2033 34 2034 33 Rate Load Reduction per...

AI summary Enrolment targets for demand response programs are based on the 2024 Load Forecast Report. The table outlines target load reductions for different rate classes and years, including residential and MURB TOU and CPP programs, with specific load reduction targets and total effective on-peak reductions.

New Rate Pages and Branding

AI summary The document discusses the introduction of new rate pages and branding, accompanied by visual elements such as figures and pictures. It appears to be related to the presentation and design of rate-related information for regulatory proceedings.

3.0 – Demand Charges (3.1) evaluate the extent to which the demand charge may act as a barrier to General class TOU participation and continue to evaluate non-demand TVP designs for General Service customers (3.2) assessment of demand char...

AI summary The text outlines a technical session discussing demand charges and their potential impact on General Service customers' participation in time-varying pricing (TVP) programs. It recommends evaluating demand charge structures, assessing their effects on customer bills, and considering modifications to encourage load shifting and participation.

It's time to beat the peak! Here's what to expect this season. Critical Peak Prioling season is here! As a participant of this rate pilot, you can save on your power bill by shifting your energy use between November and March when Critical...

AI summary Critical Peak Prioling season has begun, offering participants the opportunity to save on their power bills by adjusting energy use between November and March during Critical Peak events.

About Critical Peak Events - Critical Peak events are 4-hour periods when we anticipate demand for electricity to be highest during the winter months. - During these 4-hour periods, your power rate is higher and once the event is completed...

AI summary Critical Peak events are 4-hour periods during winter with higher electricity rates, occurring up to 3 times per week and 18 per season. Customers are notified in advance and rates return to lower levels after the event. These events do not occur on holidays and are limited to specific times on weekends.

Critical Peak Event Tips The key to saving money is making sure you reduce your electricity use during the 4-hour Critical Peak event. Here are some tips to help you:

AI summary The text provides tips for reducing electricity use during a 4-hour Critical Peak event to save money.

1. Avoid running major electrical appliances Plan to use items like your dishwasher, clothes washer and dryer, and electric range or stove outside of the 4four-hour event. Are you an Electric Vehicle (EV) owner? You will want to postpone c...

AI summary The text advises consumers to avoid using major electrical appliances during a 4-hour event to manage energy demand. It specifically mentions EV owners and suggests postponing EV charging until after the event.

5. Gain insights into your energy use Find out which appliances you should avoid using and dive into other home energy insights with MyEnergy Insights 3 days after the event. Keep track of how you are doing and how you can further save ene...

AI summary This section introduces MyEnergy Insights, a tool that provides users with energy use insights and recommendations for reducing energy consumption. It also mentions the Critical Peak Pricing Rate Pilot (CPP) and encourages sign-up for event notifications. The text includes references to an appendix and images, suggesting it is part of a larger report.

Agenda - 1. Welcome & Introduction - 2. Review Work Plan for Today's Session - 3. Demand Charges - 4. Additional Income-based Investigation - 5. Revisions to the Rate Design Scorecard - 6. Reporting on Small Business Items - 7. Technical S...

AI summary The agenda outlines the topics to be discussed during the session, including demand charges, income-based investigations, rate design scorecard revisions, and reporting on small business items, along with planning for a technical session.

3.0 – Demand Charges (3.1) evaluate the extent to which the demand charge may act as a barrier to General class TOU participation and continue to evaluate non-demand TVP designs for General Service customers (3.2) assessment of demand char...

AI summary The document outlines the evaluation of demand charges for General Service customers, including their impact on participation in time-varying pricing (TVP) and the potential for increasing electricity bills. It also discusses the need to recover only specific demand-related costs through non-coincident demand charges and the assessment of bill changes due to load shifting.

Demand Charge Review - How Demand is measured for the General rate class: - Demand is measured in 15-minute blocks every 5 minutes. - Maximum demand recorded in a billing period is used and reset for each billing period (no ratchet). - How...

AI summary The document outlines how demand is measured and charged for the General rate class. Demand is measured in 15-minute blocks and reset each billing period. Customers are charged directly based on their maximum demand and indirectly through the sizing of the first energy block, which scales with the measured demand.

Distribution of Customer Winter Peak Interval Consumption by Hour of Day The General Rate Class TOU rate aligns with 43.6% of customer winter peak consumption, enabling demand reduction for these customers. However, the remaining customers...

AI summary The General Rate Class TOU rate covers 43.6% of customer winter peak consumption, aiding in demand reduction. However, the remaining customers may experience increased winter peak demand due to load shifting to off-peak periods.

Model Commentary Individual customer annual peak 15 minute interval occurrence is captured with the corresponding timestamp of that interval. For example, if Customer A achieved their winter peak interval consumption at 8:15 AM on Dec 14th...

AI summary The Model Commentary discusses the capture of individual customer annual peak 15-minute intervals, using a specific example of Customer A achieving their winter peak at 8:15 AM on Dec 14th 2024. It references an AMI data sample of 10,479 commercial customers on Rate 11 and includes visual data from charts related to the General Rate Class, TOU Tariff, and customers with winter peak occurrences during peak times (7-11 AM, 5-9 PM).

Impact on Demand & Annual Bill from TOU On average customers shifting load from peak to off-peak hours experience demand increase with negligible increase in savings after shifting 6% or more of peak consumption to off-peak periods. Althou...

AI summary Shifting load from peak to off-peak hours increases demand, with negligible savings after shifting 6% or more of peak consumption. While customers are not financially penalized for shifting beyond 6%, the increase in demand charges offsets energy cost savings.

Model Commentary Energy neutral model assumes customers turn off electrical loads during peak and turn on an equivalent load that was displaced during off-peak hours that shoulder peak hours without concern for increasing demand. Savings i...

AI summary The energy neutral model assumes customers shift electrical loads from peak to off-peak hours without increasing overall demand. Savings increase slightly with load shifts, but the current rate design provides minimal incentive for shifts below 6%. AMI data from 4075 commercial customers on Rate 11 is analyzed, and TOU rates effective November 1, 2024, are mentioned.

Proposal for General Rate Class TOU Modifications The model indicates that the existing flat rate with demand is already effective to some degree in leading customers to improve their load factor. This can be seen with a majority of custom...

AI summary The existing flat rate with demand is somewhat effective in improving load factor, but the current TOU rate structure is not suitable for businesses with coincident peaks. Load shifting above 6% would require revisions to the demand pricing structure. Alternative rate modeling is proposed for future exploration.

Domestic TOU Bill Impact by Household Income Levels The domestic TOU rate reduces customer bills by 2.3% in the lowest income bracket and 1.6% in the highest income bracket; a difference of 0.7%. When load shifting is considered, the diffe...

AI summary The domestic Time-of-Use (TOU) rate reduces customer bills by 2.3% in the lowest income bracket and 1.6% in the highest income bracket. When load shifting is considered, the difference is reduced to 0.4%, indicating that the TOU rate disproportionately benefits low-income customers on a percentage basis.

Domestic CPP Bill Impact by Household Income Levels The domestic CPP rate reduces customer bills by 2.7% in the lowest income bracket and 1.9% in the highest income bracket; a difference of 0.8%. When load shifting is considered, the diffe...

AI summary The domestic CPP rate reduces customer bills by 2.7% in the lowest income bracket and 1.9% in the highest income bracket. This difference is 0.8%, but becomes statistically insignificant when load shifting is considered. The CPP rate disproportionately benefits low-income households without load shifting.

TVP Year Four Report Appendix E Attachment 4 Page 17 of 47 Item Objective 0 - Does Not Meet Objectives 1 - Meets Some Objectives 2 - Meets Most Objectives 3 - Meets All Objectives Customer Orientation The Tariff should be oriented to custo...

AI summary The table evaluates the Customer Orientation objective of the Tariff, assessing how well it meets criteria such as simplicity, attractive pricing differentials, and customer rate choice. It provides a scoring system from 0 to 3 based on the degree to which the tariff meets these objectives.

Load Characteristics of Small Business Customers that may Shift Load in Response to TVP - Reviewing load profiles for all TVP SMB customers enrolled on TVP found only the 4 customers flagged in the Year 3 Evaluation by Econoler (M11823) of...

AI summary The analysis of small business customers enrolled in TVP found only four customers showed meaningful load shift, but three were not scalable and one was affected by external factors. No other characteristics of small business customers indicate potential for load shifting outside of the MURB space.

Customer Hesitations and Potential Solutions - Sample of responses from discussions with customers: - Potential savings, even for structural winners often felt to be not enough to be worth the effort. - Skepticism that energy shifting is p...

AI summary Customer hesitations include skepticism about the value of potential savings and concerns about higher winter bills despite annual savings. Proposed solutions involve revising TOU rate structures, reducing seasonal bill impacts, and exploring automation technologies for load shifting.

Geographic & Work Zone segments Geographic and work zone-based segmentation divides customers by specific work zones (e.g., DAR, BAY, BRT), enabling a more localized analysis of energy usage.

AI summary The document discusses the use of geographic and work zone-based segmentation to divide customers into specific work zones (e.g., DAR, BAY, BRT), enabling a more localized analysis of energy usage.

Technical Session 3 – anticipated week of 12 May (tbc) Summary of 2024/25 Areas of Focus & Board Directives Туре Items to be Discussed/Reviewed 5.0 – Potential Tariff Changes / Introductions • (5.1) identify potential tariff changes which...

AI summary The document outlines potential tariff changes and discussions for the 2024/25 period, including improving customer participation in the Time-Varying Pricing (TVP) program, examining new tariffs for behind-the-meter energy storage, and assessing alternative domestic tariffs with time-of-use structures. The Board has directed an analysis of system costs, seasonal adjustments, and the impact of weekend-inclusive TOU rates.

Consumer Advocate (CA) Comments regarding the Accessibility of TVP On December 12th, 2024, the Consumer Advocate provided comments regarding NSP's draft 2024/2025 Areas of Focus Work Plan and the proposed list of MURB TOU Tariff evaluation...

AI summary The Consumer Advocate raised concerns about the accessibility of the Time-Varying Pricing (TVP) program for renters, suggesting they may face greater barriers than homeowners. NSP responded that renters are not restricted from joining the TVP and that behavioral changes, not appliance changes, are common among participants. NSP plans to conduct an updated survey of TVP participants this spring.

Energy Storage Canada (ESC) Will the Avoided Cost from TVP and DSM reflect the results from the new Line Loss Study? Do the results from the new Line Loss Study represent any material changes from prior assumptions as it relates to the val...

AI summary The text raises a question about whether the avoided cost from Time-Varying Pricing (TVP) and Demand Side Management (DSM) should reflect the results from a new Line Loss Study and if there are material changes in assumptions related to the value of peak-shifting.

Stakeholder Comment NS Power Response 1. Total number of customers currently enrolled in each domestic TVP tariff,

AI summary The document presents a table with stakeholder comments and responses from NS Power, focusing on the total number of customers enrolled in domestic TVP tariffs. The table is partially filled, with only the first row of comments provided.

10 Please refer to Appendix "A," page 6 of 7, filed on May 10, 2021, as part of the Company's original TVP Application (M09777).

AI summary The text references Appendix A, page 6 of 7, from the Company's original TVP Application (M09777), filed on May 10, 2021.

Stakeholder Comment NS Power Response As part of the 2024 TVP Consensus Agreement, NS Power is exploring a potential new domestic TVP (time-varying pricing) rate that includes weekends. This rate could resemble the MURB rate structure but...

AI summary NS Power is considering implementing a new domestic time-varying pricing (TVP) rate that includes weekends, tailored for residential customers within MURB buildings who are individually metered, as part of the 2024 TVP Consensus Agreement.

neutral but results in 60% of customers paying lower bills. In fact, it would be generally better for more customers to enjoy bill savings, as long as the "structural losers" do not experience significant rate shock. In the case of opt-in...

AI summary The text discusses the impact of opt-in rates on customer bill savings, noting that 60% of customers would benefit, with minimal risk of rate shock for structural losers. It also suggests removing the Fair Value metric from the scorecard and modifying it to include capacity costs.

TVP Session Technical Session 2 – held 7 April 2025 Comments Received 17 April 2025

AI summary The document references a technical session related to Time Varying Pricing (TVP) held on 7 April 2025, with comments received on 17 April 2025.

Responses Filed 30 June 2026 Stakeholder Comment NS Power Response Slide 19: Load Characteristics of Small Business Customers that may Shift Load in Response to TVP 1. Please describe in more detail what constitutes a "meaningful load shif...

AI summary The response discusses the definition of a 'meaningful load shift' in the context of small business customers participating in a Time Varying Pricing (TVP) pilot. NS Power states that any statistically significant load shift is considered meaningful, and in the absence of statistical significance, a visual review of load shapes was used to identify potential load shifts.

Stakeholder Comment NS Power Response 3. Please discuss which associations NSP plans to target that would benefit from TVP rates. Will the associations be targeted based on results from the Customer Segmentation Model discussed on Slide 28...

AI summary NS Power plans to target associations with memberships that would benefit from Time Varying Pricing (TVP) rates and are receptive to learning about them. The selection of associations will be determined throughout the year based on opportunities and resources, rather than solely on the results of the Customer Segmentation Model.

Time-Varying Pricing Tariff Program – NS Power Responses to Stakeholder Comments on 2024/25 Technical Session 2 (7 April 2025) Attachment 1 The charts below show the hourly average load profile per month of several business vertical segmen...

AI summary The document provides visual data on the hourly average load profile per month for various business vertical segments, normalized by their maximum month-hour load (kW), along with a table showing the average maximum hourly kW consumed per customer for reference.

Time-Varying Pricing Pilot Program Phase 4 Evaluation, Measurement & Verification Report June 30, 2026

AI summary This document is an Evaluation, Measurement & Verification Report for Phase 4 of the Time-Varying Pricing Pilot Program, dated June 30, 2026. It provides an analysis of the program's performance and outcomes.

Definitions Adjusted Net Load The hourly net system requirement (MW) less all wind generation (MW) Cohorts Cohorts are numbered based on the Phase they enrolled in the TVP program. For example, Cohort 4 refers to participants recruited in...

AI summary The text defines key terms used in the regulatory proceeding, including Adjusted Net Load, Cohorts, Commercial customers, Consumption, Control group, Demand, and Income brackets. These definitions provide context for analyzing energy usage and program participation.

Nova Scotia Power (NS Power, Company) launched the Time-Varying Pricing (TVP) Tariff Pilot on November 1, 2021, with the purpose of encouraging customers to shift load from Winter peak periods to Winter off-peak periods. These tariffs pres...

AI summary Nova Scotia Power's Time-Varying Pricing (TVP) Tariff Pilot, launched in 2021, encourages load shifting to reduce peak energy demand and system costs. The fourth annual report highlights continued customer enrollment growth, load reduction effects, and improved evaluation methods. The pilot demonstrates significant on-peak load reductions, particularly during high system load periods, and provides insights for future demand response strategies.

Tariffs Both TOU and CPP are available in the Domestic, Small General, and General rate classes, whereas MURB TOU is available to MURBs in the General rate class. A summary of the TVP Tariffs is provided in Attachment [I: Riders and Tariff...

AI summary The document outlines the structure and rates of Time-Varying Pricing (TVP) tariffs, including TOU and CPP, across different rate classes. It specifies peak and off-peak periods, pricing differences relative to the Standard Offer Rate (SOR), and details for MURB TOU and CPP events.

Residential Findings In total, 5,616 TOU and 2,642 CPP residential customers participated in the TVP program in Phase 4. Of these, 4,938 TOU and 2,310 CPP customers were included in the regression when counting only those who meet the crit...

AI summary In Phase 4 of the TVP program, 5,616 TOU and 2,642 CPP residential customers participated, with 4,938 TOU and 2,310 CPP customers included in the regression analysis. Participants achieved significant electricity load reductions during peak periods and events, consistent with Phase 3 results.

Table 1: Summary of Peak Load Reductions by Residential TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) TVP Tariff Morning Peak Evening Peak Morning Peak Evening Peak Absolute Load Reduction (kW) Relative Load Reduction...

AI summary The table summarizes peak load reductions by residential TVP tariff, showing that residential TOU and CPP tariffs reduced load during peak periods. Residential TOU participants achieved load reductions of 0.15 kW and 0.17 kW during morning and evening peaks, respectively, while CPP participants achieved larger reductions. The use of technology like Eco Shift and smart devices significantly enhanced load reduction. Electrification of space heating with TOU also showed statistically significant load reduction without increasing annual energy consumption.

Commercial Findings The commercial TVP Tariffs attracted more businesses, with Phase 4 enrolment (108 businesses) higher compared to Phase 3 (65 businesses). While "small sample size and the wide variety of energy consumption profiles prev...

AI summary The commercial TVP Tariff program saw increased business participation in Phase 4, with more robust analysis showing significant load reductions during peak periods. However, results varied by rate class, with General Tariff participants showing more responsiveness to price signals compared to Small General Tariff participants. Load reduction impacts were also influenced by outdoor temperatures and event timing.

MURB TOU Findings Phase 4 marks the first load and economic impacts evaluation of the MURB TOU Pilot Tariff. Ten MURBs were recruited and are enrolled in the MURB TOU Tariff. For the MURB TOU Tariff, this Phase 4 evaluation includes the Wi...

AI summary Phase 4 of the MURB TOU Pilot Tariff evaluation found that participants achieved a 0.48 kW load reduction during peak periods, with only evening peak hours showing statistically significant results. However, load increased significantly in March.

Table 3: Summary of Load Reductions from MURB TOU Tariff TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) Morning Peak Evening Peak Morning Peak Evening Peak MURB TOU 0.44 kW 0.54 kW 1.8% 2.1% Statistical Significance X...

AI summary Table 3 summarizes load reductions from the MURB TOU tariff, showing absolute and relative reductions during morning and evening peaks. Statistical significance is indicated with black font for significant results and grey for insignificant ones.

Introduction Time-Varying Pricing (TVP) is a scalable customer-focused demand response (DR) program. In Nova Scotia, the TVP pilot has grown significantly since it began in November 2021. Since its inception, the TVP pilot has offered two...

AI summary Time-Varying Pricing (TVP) is a demand response program in Nova Scotia that has expanded since 2021, offering TOU and CPP tariffs across three rate classes. The program aims to shift customer demand to reduce fuel and power costs, as well as long-term infrastructure costs. Phase 4 introduces a new MURB TOU Tariff, evaluated in the TVP Phase 4 EM&V report.

Evaluation Scope This evaluation pilot period (i.e. Phase 4) analyzes advanced metering infrastructure (AMI) data from November 1, 2020 – March 31, 2025. Each Phase, the pilot period shifts by 1-year; however, the prepilot period remains s...

AI summary The evaluation pilot period (Phase 4) analyzes AMI data from November 1, 2020, to March 31, 2025. The pilot period shifts by one year per phase, but the prepilot period remains static. The first year of a cohort's participation in the TVP pilot includes a limited evaluation during the winter period, while subsequent evaluations cover a full year. Evaluation metrics are divided into 'Load & Usage' and 'Economic' categories.

Table 4: Impact Evaluation Metric Summary Category Metric TOU, CPP, MURB TOU (all rate classes unless specified) • Change in load (kW) during peak, and overall impact during Winter and non-Winter. Mid-peak hours included for MURB TOU. • Ch...

AI summary Table 4 outlines impact evaluation metrics for load and usage changes under various rate structures, including TOU, CPP, and MURB TOU. It details changes in load during peak periods, snapback effects, average usage levels, and economic impacts such as changes in electricity bills and price elasticity.

The TVP pilot program has increased enrolment year over year with a total of 8,376 participants at the end of Phase 4. Refer to [Table 5](#page-21-0) and [Table 6](#page-21-1) for participation summaries.

AI summary The TVP pilot program has seen increasing participation, reaching 8,376 participants by the end of Phase 4. Participation summaries are detailed in Table 5 and Table 6.

Table 5: TVP Participation on March 31 by Phase and Tariff Phase DOM TOU SMG TOU GEN TOU DOM CPP SMG CPP GEN CPP MURB TOU Total Phase 1 676 24 284 8 0 992 Phase 2 891 17 373 2 1,283 Phase 3 2,241 37 19 922 3 6 0 3,228 Phase 4 5,616 37 18 2...

AI summary Table 5 presents TVP participation by phase and tariff, showing the number of participants in different rate classes and phases. The average customer retention rate for TVP tariffs ranges from 87% to 100%, with additional details provided in Table 6.

Table 6: Participation Summary and Retention Results TVP Tariff 𝐀 Enrolled prior to beginning of Phase 4 Winter (October 31, 2024) 𝐁 Enrolled during Phase 4 Winter (November 1, 2024 to March 31, 2025) 𝐂 Withdrew mid Phase 4 Winter (Novembe...

AI summary Table 6 presents participation and retention results for various TVP tariff programs during Phase 4 Winter. It shows the number of participants enrolled prior to and during the phase, withdrawals, and retention rates. The data highlights differences in participation and retention across different tariff types.

2 Control Group Selection The control group selection methodology uses 1-hour average and 15-minute peak load data to determine the best 1:1 control match by four neighbourhoods. If treatment customers are distributed throughout the provin...

AI summary The control group selection methodology uses load data to ensure Treatment and Control customers are similarly distributed across Nova Scotia. Figures 2 and 3 show that both groups align with the population distribution, enhancing the validity of program comparisons.

2.1 Residential TOU & CPP To best evaluate load and billing effects of the TVP pilot, it is important to have a control group with similar load characteristics to that of the treatment group. The control group selection load profile match...

AI summary The document evaluates the load and billing effects of the Time-Varying Pricing (TVP) pilot by comparing control and treatment groups. It highlights a 96% match accuracy in load profiles for both TOU and CPP, with similar baseline characteristics between control and treatment groups, though living space and electric space heating penetration differ, contributing to higher energy consumption in TVP customers.

Group Energy (kWh) SOR 10,225 TVP 12,678 2.1.1 Eco Shift

AI summary The document includes a table showing energy usage by group, with SOR and TVP as categories, and a section titled '2.1.1 Eco Shift' which likely discusses energy efficiency or related initiatives.

2.2 Commercial TOU & CPP The same methodological approach as used with residential control group (with exception to Neighbourhood Criteria, Heating Classification, and Eco Shift) was used in attempting to select a control group for Small G...

AI summary The analysis of control groups for Commercial TOU and CPP rates using the same method as residential control groups showed poor matching, leading to unsuitable control groups. The results are similar to previous phases, and regression analysis for these TVP tariffs will use a within-subject approach.

2.3 MURB TOU For MURB TOU, the control group selection model was successful (Match Accuracy ≥ 90%) in selecting a 1:1 control for the ten MURB TOU treatment customers, refer to load profiles below in [Figure 11.](#page-30-2) Figure 11: MUR...

AI summary The MURB TOU control group selection model achieved a match accuracy of ≥90%, successfully selecting a 1:1 control for ten treatment customers. Load profiles in Figure 11 show a good match, supporting the use of a control group for this subset of commercial customers.

2.4 CPP Reference Days The CPP reference days were selected for Phase 4 are summarized in Table 8.

AI summary The document discusses the selection of Critical Peak Pricing (CPP) reference days for Phase 4, which are summarized in Table 8.

Table 8: Phase 4 CPP Event Reference Day Results Event Day HALIFAX AIRPORT KENTVILLE CDA CS NAPPAN AUTO SHEARWATER RCS SYDNEY AIRPORT TRACADIE WESTERN HEAD YARMOUTH AIRPORT 12/4/2024 12/3/2024 12/3/2024 12/3/2024 12/3/2024 12/3/2024 12/3/2...

AI summary This table outlines the reference days for Critical Peak Pricing (CPP) events across various locations in Nova Scotia. Each event day is paired with a reference day that has the most similar temperature profile. Some events have the same reference day for all locations, while others vary depending on the weather station.

3 Residential TOU Tariff Impacts This section presents the analysis results for load and economic impacts of Residential TOU tariffs for all cohorts in Phase 4. The goal of the residential TOU pilot is to encourage customers to shift their...

AI summary This section analyzes the load and economic impacts of Residential TOU tariffs in Phase 4, highlighting that Cohort 4 has nearly three times as many participants as the combined total of cohorts 1, 2, and 3. Participants with steady electric heating systems are more common than those with other heating types, and de-electrified heating is the least frequent.

Parameter Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Sample Size 430 190 1,016 3,302 4,938 Heating Type Steady Electric 48% 65% 61% 61% 60% Steady Non-Electric 26% 18% 22% 25% 24% Electrified 22% 11% 11% 9% 10% De-Electrified 4% 6% 6% 5% 6% R...

AI summary Table 9 provides a summary of the residential time-of-use (TOU) sample size across four cohorts, detailing the distribution of heating types and regions. The data shows the percentage of homes using steady electric, non-electric, electrified, and de-electrified heating, as well as regional distribution within Nova Scotia.

3.1 Load & Usage Impacts This section presents and discusses the electrical load impact from the residential TOU Tariff.

AI summary This section discusses the electrical load impact resulting from the implementation of a residential Time-of-Use (TOU) Tariff, focusing on how it affects residential consumers' energy usage patterns.

3.1.1 Change in Load during Peak Periods [Table 10](#page-34-0) summarizes the results of the analysis for morning and evening TOU peak hours for each cohort and for all cohorts combined. The average load reductions are presented along wit...

AI summary The analysis in Table 10 shows that TOU participants achieved statistically significant load reductions during morning and evening peak hours, with higher reductions in the evening. The average load reduction for all residential TOU participants was 0.16 kW, corresponding to 7.4% and 7.9% relative reductions during morning and evening periods, respectively.

Table 10: Change in Load during TOU Peaks for Residential TOU Participants Morning Peak Periods Evening Peak Periods Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Avg. Load Reduction (kW)a 0.18...

AI summary Table 10 presents the average load reduction during TOU peak periods for residential TOU participants across different cohorts. The data shows a significant load reduction with statistical significance, indicating the effectiveness of TOU pricing in managing residential energy consumption during peak times.

Change in Load by Space Heating Classes during TOU Peak Hours [Table 11](#page-37-0) summarizes the average load reductions during morning and evening TOU peak hours for space heating classes of all cohorts combined in Phase 4. The load re...

AI summary Table 11 summarizes average load reductions during TOU peak hours for different space heating classes in Phase 4. Steady electric heating systems showed the highest load reductions, while non-electric systems showed the lowest. Electrification of heating systems also resulted in notable load reductions during peak hours.

Change in Load by Region, Income Level, and Residents per Household [Figure 15](#page-37-1) illustrates the average load reduction achieved by TOU participants according to the region of premises in Nova Scotia. While no significant differ...

AI summary The text discusses load reduction among TOU participants in Nova Scotia, noting higher evening load reductions in the Halifax area compared to the rest of the province, and higher absolute load reductions among higher-income participants despite no significant trend in relative load reduction by income level.

Low-Income Medium-Income High-Income Parameters AM Peak PM Peak All Peak Hours AM Peak PM Peak All Peak Hours AM Peak PM Peak All Peak Hours Avg. Load 0.14 ± 0.15 ± 0.15 0.12 ± 0.16 ± 0.14 0.18 0.19 0.19 a Reduction (kW) 0.01 0.01 ± 0.01 0...

AI summary This table presents average load and load reduction data across different income levels in Nova Scotia, highlighting variations in energy consumption and the effectiveness of demand response programs. It includes statistical measures and significance indicators for each category.

Change in Load with Eco Shift E1's Eco Shift is a DR initiative offered separately from TVP and was implemented within subset of the TVP treatment participants who opted into both programs. It is designed to encourage load reduction during...

AI summary E1's Eco Shift DR initiative, combined with TOU, significantly increased load reduction during peak hours. Analysis using DDD regression showed an additional 0.29 kW reduction during all TOU peak hours, with even higher reductions during morning and evening peaks. During Eco Shift events, the combined effect of TOU and Eco Shift resulted in a total load reduction of 0.66 kW.

3.1.2 Snapback Effect While the TOU participants exhibit relatively small but statistically significant load increase of 0.014 kW during evening snapback period, they reduced their electricity usage by 0.013 kW during morning snapback hour...

AI summary The TOU participants showed a small but statistically significant increase in load during evening snapback periods and a decrease during morning snapback periods. However, overall, there was no statistically significant change in load during these periods.

Parameters Load Reduction a Avg. (kW) Significance (p_Value≤0.05) Morning Snapback 0.013 ± 0.004 ✓ Evening Snapback -0.014 ± 0.005 ✓ Overall Snapback -0.002 ± 0.003 X Table 13: Snapback Effect for Residential TOU Participants

AI summary Table 13 presents the snapback effect for residential Time-of-Use (TOU) participants, showing load reduction averages and significance levels. Morning snapback had a small positive effect, evening snapback had a slightly larger negative effect, and overall snapback was not statistically significant.

3.1.3 Change in Load during Highest ANL Hours [Figure 20](#page-42-0) depicts the distribution of Top 20, 50, and 88 highest ANL hours for residential TOU participants during morning peak, evening peak, and off-peak hours as well as weeken...

AI summary The text discusses the distribution of highest ANL hours for residential TOU participants, highlighting significant load reductions during peak periods. Results show a 6% relative load reduction during top 20, 50, and 88 highest ANL hours that coincide with TOU peak periods, with absolute reductions of 0.17 kW.

Participants Parameters High nest ANL Ho urs ANL Hours Coincide TOU Peak Periods Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 Avg. Load 0.16 ± 0.04 0.14 ± 0.13 ± 0.17 ± 0.17 ± 0.17 ± Reduction (kW) a 0.16 ± 0.04 0.03 0.02 0.03 0.03 0.02 Avg....

AI summary The table presents load reduction data for participants in a demand response program, comparing average load and reduction across different participant tiers and time periods. The data highlights the effectiveness of the program, with load reductions ranging from 4.8% to 6.2%, though statistical significance is only noted for the top 20 participants.

3.1.4 Change in Usage Table 15 summarizes changes in daily electricity usage level for cohorts 1 to 4 and all cohorts combined during non-holiday weekdays and holiday weekends in Winter. All cohorts exhibit statistically significant reduct...

AI summary Table 15 shows a statistically significant reduction in daily electricity usage across all cohorts during non-holiday weekdays and holiday weekends in Winter. TOU participants had an average load reduction of 0.6 kWh on holidays and weekends, which is also statistically significant.

Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Weekdays Avg. Usage Reduction 1.71 ± 2.70 ± 1.64 ± 1.10 ± 1.39 ± a (kWh/day) 0.21 0.31 0.14 0.08 0.06 Avg. Usage – Residential TOU Participants, Pre-Pilot (kWh/day) 39....

AI summary The table presents average usage reduction and relative usage reduction percentages across different cohorts during winter non-holiday weekdays, winter weekends/holidays, and non-winter periods. All cohorts show statistically significant results (p_Value≤0.05), indicating the effectiveness of the program in reducing residential TOU participants' energy usage.

[Table 16](#page-45-0) presents changes in daily electricity usage levels by space heating. During non-holiday weekdays in Winter, TOU participants with electrified space heating exhibit insignificant change in their daily usage level. Not...

AI summary Table 16 shows changes in daily electricity usage by space heating type among residential TOU participants. During non-holiday weekdays, electrified heating systems show no significant change, but significant increases during holidays and weekends. De-electrified and steady non-electric systems show reductions during non-holiday weekdays, with mixed results during holidays and weekends. Overall, savings are statistically significant and amount to 300 kWh annually.

3.2 Economic Impacts This section presents and discusses the impact of residential TOU tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of residential time-of-use (TOU) tariffs, focusing on their influence on electricity bills and price elasticity.

[Table 17](#page-46-2) summarizes the applicable tariffs used for residential TOU impact on billing. Tariff details can be found in [Attachment I: Riders and Tariff Structure.](#page-100-0) Customer Type and Period Applicable Tariff Contro...

AI summary Table 17 outlines the residential TOU tariffs used in the analysis, while Table 18 shows that residential TOU participants achieved average annual bill savings of $0.30 per day, with significant savings during non-Winter periods. However, during Winter, participants experienced an overall bill increase of $1.34 per day due to higher TOU rates during peak hours.

The analysis reveals that the type of space heating has significant influence on the bill impact for the TOU participants. While TOU participants with all space heating types experienced significant increases in bills during Winter season,...

AI summary The analysis shows that TOU participants with electrified space heating achieved average annual bill savings of $153, while all space heating types saw significant savings during non-Winter seasons. However, the study does not account for additional fuel costs or savings from non-electric heating sources.

34 & lt;sup>8 TOU rates were 32.12 ¢/kWh during peak hours and 16.931 ¢/kWh during off-peak hours. Table 19: Change in Daily Electricity Bill by Space Heating Type for All Cohorts of Residential TOU Participants Parameters El ec De tr ifi...

AI summary The document provides data on Time-of-Use (TOU) electricity rates and their impact on residential electricity bills, showing savings during winter and non-winter periods, with statistical significance across all cohorts.

3.2.2 Price Elasticity Residential TOU participants' responsivity to electricity prices ($/kWh) was evaluated by estimating daily price elasticity during non-holiday weekdays in Winter season, as well as the Inter-period Substitution Price...

AI summary The analysis of residential TOU participants' price elasticity during winter non-holiday weekdays shows a daily price elasticity of -1.05 and an inter-period substitution elasticity of -0.14, indicating that higher prices lead to reduced electricity usage and shifting of load to off-peak hours.

4 Residential CPP Tariff Impacts This section presents the analysis results for load and economic impacts of the Domestic CPP Tariff for all cohorts in Phase 4. The goal of the residential CPP pilot is to encourage customers to shift their...

AI summary This section evaluates the load and economic impacts of the Domestic CPP Tariff during Phase 4, from April 1, 2024, to March 31, 2025. The goal is to encourage load shifting during CPP events to reduce energy costs and infrastructure needs.

Table 21: Summary of Residential CPP Sample Size 8F [9](#page-50-3) Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Sample Size 161 75 468 1,606 2,310 Heating Type: Steady Electric 75% 79% 60% 62% 63% Steady Non-Electric 9% 8% 23% 23% 2...

AI summary Table 21 summarizes the sample size and distribution of residential Critical Peak Pricing (CPP) cohorts, showing variations in heating types and regions across four cohorts and the overall sample. The data highlights differences in electrification levels and geographic distribution.

4.1.1 Change in Load during Peak Periods [Table 22](#page-51-0) summarizes the results of the analysis for morning and evening CPP events for each cohort and all participants combined. The average load reduction metrics are presented along...

AI summary The analysis of load reduction during morning and evening Critical Peak Pricing (CPP) events shows statistically significant reductions across all cohorts, with cohort 4 having lower margin of error due to a larger number of participants. Overall, CPP participants achieved load reductions of 0.61 kW and 0.77 kW during morning and evening events, respectively.

Table 22: Change in Load during CPP Events for Residential CPP Participants Morning Events Evening Events Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Avg. Load Reductiona (kW) 0.68 ± 0.10 1.22...

AI summary Table 22 presents the average load reduction during Critical Peak Pricing (CPP) events for residential participants, comparing different cohorts and showing significant reductions in load across all groups during both morning and evening events.

Change in Load by Space Heating Classes During Peak Events [Table 23](#page-52-0) summarizes the average load reductions during morning and evening events for space heating classes of all cohorts combined in Phase 4. It is important to not...

AI summary Table 23 summarizes the average load reductions during morning and evening peak events for space heating classes in Phase 4. The analysis compares event and reference days during the 2024/25 Winter, noting that changes in space heating type between baseline and pilot periods do not directly affect load reduction results in the DiD analysis.

Morning Evening Parameters De -E le ct rifi ed El ec tr ifi ed El St ec ea tr dy ic No n- St El ea ec dy tr ic De -E le ct rifi ed El ec tr ifi ed El St ec ea tr dy ic No n- St El ea ec dy tr ic Avg. Load Reductiona 0.57 ± 0.66 ± 0.74 ± 0....

AI summary The table presents load reduction data for residential Critical Peak Pricing (CPP) participants in both morning and evening periods, showing average load reductions and their significance levels. The data indicates that load reduction percentages vary across different parameters and time periods, with all values showing statistical significance.

Change in Load per Critical Peak Event [Figure 23a](#page-53-0) illustrates the average load reduction (kW) per CPP event date for all Phase 4 cohorts, along the corresponding event-average outdoor temperature (°C). The residential CPP par...

AI summary The document discusses the average load reduction per Critical Peak Pricing (CPP) event, showing that residential participants achieved significant reductions, with higher reductions during evenings and in the Halifax Area. Higher-income households demonstrated greater relative load reductions compared to lower-income households.

4.1.2 Snapback Effect The CPP participants exhibit relatively small but statistically significant snapback effects during morning, evening and double-event snapback periods, indicating significant increase in electricity usage during the f...

AI summary CPP participants show small but statistically significant snapback effects, with a 0.15 kW increase in electricity usage during double-snapback periods compared to morning or evening snapbacks, as shown in Table 25.

Table 25: Snapback Effect for Residential CPP Participants Parameters Average Load Reduction a (kW) Significance (p_Value≤0.05) Morning Snapback -0.04 ± 0.02 ✓ Evening Snapback -0.08 ± 0.03 ✓ Double-Event Snapbackb -0.15 ± 0.05 ✓ Overall S...

AI summary Table 25 presents the snapback effect for residential Critical Peak Pricing (CPP) participants, showing average load reductions during morning, evening, and double-event snapbacks, with all values statistically significant at the 0.05 level.

4.1.3 Change in Load during Highest ANL Hours [Figure 29](#page-58-0) illustrates the distribution of Top 20, 50 and 88 highest ANL hours for residential CPP participants during weekdays and weekends as well as across CPP events. The major...

AI summary The text discusses the distribution of highest Adjusted Net Load (ANL) hours for residential Critical Peak Pricing (CPP) participants during weekdays and weekends. It notes that most high ANL hours occur on weekdays and highlights statistically significant load reductions during these periods, particularly during CPP peak times.

Parameters Highest ANL Hours ANL Hours Coincide with CPP Events Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 0.75 ± 0.63 ± 0.55 ± 0.85 ± 0.84 ± 0.80 ± Avg. Load Reductiona (kW) 0.07 0.06 0.04 0.07 0.06 0.05 Avg. Load – CPP 2.9 2.9 2.8 2.9 2.9...

AI summary This table presents load reduction data associated with Critical Peak Pricing (CPP) events, showing average load reductions in kilowatts and percentages for different participant groups. The data includes statistical significance and confidence intervals, indicating the effectiveness of CPP in reducing energy demand during peak hours.

Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Weekdays Avg. Usage Reduction a (kWh/day) 3.0 ± 1.4 3.1 ± 2.0 1.0 ± 0.9 1.1 ± 0.5 1.2 ± 0.4 Avg. Usage – Residential CPP Participants, Pre-Pilot (kWh/day) 50.7 60.5 44....

AI summary The table presents data on average usage reduction across different cohorts during winter non-holiday weekdays, weekends/holidays, and non-winter days. It highlights the impact of Critical Peak Pricing (CPP) on residential participants, showing varying degrees of significance and usage reduction percentages.

[Table 29](#page-61-1) presents changes in daily electricity usage level by space heating for all cohorts of residential CPP participants during pilot period compared to pre-pilot period. During non-holiday weekdays in Winter, CPP particip...

AI summary Table 29 shows that residential Critical Peak Pricing (CPP) participants with electrified space heating had a 13% increase in daily electricity usage during non-holiday weekdays in winter, while de-electrified and steady electric participants saw reductions. Steady non-electric participants showed no significant change in usage.

Table 30: Tariffs Used for Analyzing Residential CPP Impact on Electricity Bill Customer Type and Period Applicable Tariff Control, Reference Day Domestic Standard Tariff Control, during Pilot Domestic Standard Tariff Treatment, Reference...

AI summary Table 30 and Table 31 analyze the impact of the Conservation Program Participants (CPP) on residential electricity bills. The results show that CPP participants experienced average daily bill savings of $0.57 annually, with significant savings during non-Winter days and weekends/holidays in Winter. These savings are attributed to lower rates under the CPP Tariff compared to standard domestic tariffs.

4.2.2 Price Elasticity Price elasticity was evaluated to measure residential CPP participants' responsivity to electricity prices during Phase 4. Specifically, NS Power evaluated Daily Price Elasticity during Winter season and annual overa...

AI summary The document evaluates price elasticity for residential Conservation Program Participants (CPP) during Phase 4, focusing on Daily Price Elasticity and Inter-period Substitution Price Elasticity. Results show a Daily Price Elasticity of -0.2 and an Inter-period Substitution Price Elasticity of -0.19, both statistically significant, indicating reduced electricity usage in response to price changes.

5 Commercial TOU Tariff Impacts This section presents and discusses the estimated load and economic impacts of the commercial TOU program. The goal of the commercial TOU pilot is to encourage customers to shift their electricity usage from...

AI summary This section discusses the estimated load and economic impacts of the commercial Time-Varying Pricing (TOU) program. The goal is to encourage customers to shift electricity usage from peak to off-peak periods, reducing fuel and power costs and infrastructure expenses. Phase 4 has 50 participants, with most enrolled in earlier cohorts.

Parameter Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Sample Size 19 15 12 4 50 Rate Class Small General 9 13 6 4 32 General 10 2 6 0 18 Region HRM 12 3 6 3 24 Rest of Nova Scotia 7 12 6 1 26 Table 33: Summary of Commercial TOU Sample Size 9F...

AI summary Table 33 presents a summary of the commercial time-of-use (TOU) sample size, divided into four cohorts with varying sample sizes and distribution across rate classes and regions in Nova Scotia.

5.1 Load Impacts This section presents and discusses the electrical load impact from the commercial TOU pilot.

AI summary This section discusses the electrical load impact resulting from the commercial Time-Varying Pricing (TVP) pilot program.

5.1.1 Change in Load during Peak Periods [Figure 31](#page-66-1) illustrates the load profiles for commercial TOU participants during the pre-pilot and pilot periods, along with the corresponding variation in outdoor temperature during the...

AI summary Commercial Time-of-Use (TOU) participants showed a reduction in electricity load during peak hours, with an overall peak reduction of 0.8 kW and average load reductions of 6.4%, 8.6%, and 7.4% during morning, evening, and overall peak periods, respectively. The results from the Mixed-Effects regression analysis confirmed these impacts as statistically significant.

Table 34: Change in Load during TOU Peaks for Commercial TOU Participants Parameters Morning Peak Evening Peak All Peak Hours (Overall) Avg. Load Reduction (kW)a 0.7 ± 0.2 0.9 ± 0.2 0.8 ± 0.1 Load – Avg. Commercial TOU 10.9 10.3 10.6 Parti...

AI summary Table 34 presents the average load reduction during morning and evening peaks for commercial Time-Varying Pricing (TVP) participants, showing statistically significant reductions of 6.4% and 8.6% respectively, with an overall reduction of 7.5% across all peak hours.

Change in Load during Peak Events by Region [Table 35](#page-67-0) presents the average load reduction (kW) by region (Halifax area versus the rest of Nova Scotia) for commercial TOU participants during morning, evening, and all peak hours...

AI summary Table 35 presents average load reductions during peak hours for commercial TOU participants in the Halifax area and the rest of Nova Scotia, showing statistically significant reductions in both regions, though with varying magnitudes.

Halifax Area Rest of Nova Scotia Parameters Morning Evening All Peak Morning Evening All Peak Peaks Peaks Hours Peaks Peaks Hours Avg. Load Reduction 1.22 ± 1.49 ± 1.38 ± (kW)a 0.29 0.31 0.20 0.16 ± 0.17 0.24± 0.18 0.20 ± 0.15 Load – Avg....

AI summary The table presents load reduction data for the Halifax Area and Rest of Nova Scotia, showing average load reductions during peak hours and the percentage of load reduction. The data highlights significant reductions in the Halifax Area compared to the Rest of Nova Scotia.

Change in Load by Month during Peak Periods [Figure 33](#page-69-2) illustrates the impact of commercial TOU in terms of average load reduction (kW), together with the average outdoor temperature (°C) during peak hours by month over the Wi...

AI summary Figure 33 shows that commercial TOU participants achieved significant load reductions during winter peak periods, except for a slight increase in December 2024. The greatest load reduction of 1.6 kW occurred in February 2025 when temperatures were at their lowest.

5.1.2 Snapback Effect NS Power evaluated the snapback effect based on the same method that was applied for load reduction calculation, but specifically for the four hours following the morning and evening peak hours. As summarized i[n Tabl...

AI summary NS Power evaluated the snapback effect for commercial TOU participants, finding a statistically significant load reduction of 0.51 kW during morning snapback hours and a load increase of 0.9 kW during evening snapback hours, resulting in a 13.3% relative load increase. The overall relative load increase of 1.2% was not statistically significant.

Table 36: Snapback Effect for Commercial TOU Participants Parameters Avg. Load Reductiona (kW) Relative Avg. Load a Reduction (%) Significance (p_Value≤0.05) Morning Snapback 0.51 ± 0.19 4.4% ✓ Evening Snapback -0.90 ± 0.17 -13.3% ✓ Overal...

AI summary Table 36 presents data on the snapback effect for commercial TOU participants, showing load reduction in the morning and load increase in the evening, with statistical significance noted for both morning and evening effects.

5.1.3 Change in Load during Highest ANL Hours [Figure 34](#page-70-1) depicts the distribution of Top 20, 50 and 88 highest ANL hours for commercial TOU participants during off-peak, morning peak, evening peak, Weekends and Holidays. As se...

AI summary The document analyzes the distribution of highest ANL hours for commercial TOU participants, showing that these hours disproportionately occur on weekdays and during peak periods. However, load changes during these hours were not statistically significant, indicating no major impact on overall load.

Parameters Highest ANL Hours ANL Hours Coincide TOU Peak Periods Top20 Top 50 Top88 Top20 Top 50 Top88 (kW)a Avg. Load Reduction 0.06 ± 0.34 ± -0.15 ± -0.12 ± 0.20 ± 0.10 ± 0.85 0.50 0.44 0.84 0.48 0.40 Avg. Load Participants, Pre Pilot (k...

AI summary The table presents data on load reduction and average load for different participant groups, showing variations in load reduction percentages and significance levels. It highlights the impact of abnormal load hours and their coincidence with TOU peak periods.

5.1.4 Change in Usage Changes in daily electricity usage were estimated by applying the same method which was used for estimating hourly load-impact, to daily electricity usage. [Table 38](#page-71-3) presents the estimated changes in dail...

AI summary The document discusses the estimation of changes in daily electricity usage for commercial TOU participants using a method similar to that used for hourly load-impact estimation. Table 38 provides the estimated changes in daily electricity usage in kWh/day.

5.2 Economic Impacts This section presents and discusses the impact of commercial TOU tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of commercial time-of-use (TOU) tariffs on electricity bills and price elasticity, analyzing how these tariffs influence consumer behavior and costs.

5.2.1 Change in Electricity Bills The bill impact analysis for the commercial TOU uses the same method that was used for estimating the commercial TOU load impact analysis. In the bill impact analysis, applicable tariffs applied in accorda...

AI summary The bill impact analysis for the commercial TOU uses the same method as the commercial TOU load impact analysis. Applicable tariffs are applied based on customer type and pilot period, as detailed in Table 39 and Attachment I: Riders and Tariff Structure.

Table 39: Tariffs Used for Evaluating the Impact of Commercial TOU on Electricity Bill Customer Type Period Applicable Tariff Treatment – General Pre-Pilot General Tariff – Rate Code 11 Treatment – General Pilot General TOU Tariff – Rate C...

AI summary Table 39 outlines the tariffs used for evaluating the impact of commercial Time-of-Use (TOU) pricing on electricity bills, comparing pre-pilot and pilot periods. Table 40 indicates that commercial TOU participants experienced statistically significant average daily bill increases of approximately 12.311.9 \/day in Winter and 3.81.1 \/day annually, consistent with increased electricity usage.

Table 40: Change in Daily Electricity Bill for Commercial TOU Participants Parameters Winter Non-Winter Annual Overall Bill Savings ($/day)a Avg. -12.311.9 ± 3.34 2.26.2 ± 2.23.1 -3.81.1 ± 2.63.1 Avg. Bill, Commercial TOU Participants, Pre...

AI summary Table 40 presents the change in daily electricity bills for commercial TOU participants, showing bill savings and increases during winter and non-winter periods, along with annual overall figures. The data includes average bill amounts, savings in dollars and percentages, and significance levels.

5.2.2 Price Elasticity Daily Price Elasticity reflects the change in overall daily electricity usage caused by changes in the average daily price ($) per kWh. It is expressed as the percent (%) change in the average electricity usage assoc...

AI summary The text discusses price elasticity in electricity usage, noting a Daily Price Elasticity of 0.13 during Winter and -0.21 annually. The inter-period substitution elasticity is -0.065, indicating load shifting from peak to off-peak periods during Winter. These results suggest that price changes influence consumption patterns, though some findings are not statistically significant.

6 Commercial CPP Tariff Impacts This section presents and discusses the estimated load and economic impacts of the commercial CPP program. The goal of the commercial CPP pilot is to encourage customers to shift their electricity usage from...

AI summary This section discusses the estimated load and economic impacts of the commercial Conservation Program Participants (CPP) program, focusing on load shifting during peak events. The analysis uses a Mixed-Effects modeling semi-DiD approach and covers CPP events from November 1, 2024, to March 31, 2025.

7 MURB TOU Tariff Impacts As this Phase represents the first year of the MURB TOU pilot program, participation was limited to 10 enrolled MURBs, with the pilot period beginning on November 1, 2024. The goal of the MURB TOU pilot is to info...

AI summary The MURB TOU pilot program, starting in November 2024, involves 10 enrolled MURBs and aims to assess the impact of removing the demand charge on load shifting potential compared to the commercial TOU pilot. This section discusses the estimated load and economic impacts of the commercial TOU pilot.

7.1 Load Impacts This section presents and discusses the electrical load impact from the commercial MURB TOU pilot.

AI summary This section discusses the electrical load impact from the commercial MURB TOU pilot, providing insights into how this initiative affects overall load management.

7.1.1 Change in Load during Peak Periods [Figure 41a](#page-88-0) illustrates the load profiles for MURB TOU participants and the control group during the pre-pilot and pilot periods with the corresponding variation in outdoor temperature....

AI summary The text discusses load reduction patterns among MURB TOU participants during peak and off-peak hours, showing statistically significant reductions in electrical load, particularly during morning and evening peak periods. The DiD analysis reveals an overall load reduction of 1.9%, with higher reductions observed during midpeak and off-peak hours.

Parameters Morning Peak Mid-Peak Periodb Evening Peak Overnight Periodc Overall On-Peak Avg. Load (kW)a Reduction 0.44 ± 0.49 1.34 ± 0.40 0.54 ± 0.49 0.48 ± 0.31 0.48 ± 0.35 Avg. Load – MURB TOU Participants, Pre Pilot (kW) 24.2 24.4 25.1...

AI summary The table presents load reduction data across different peak periods for TOU participants, showing average load reductions and their significance levels. The data highlights varying degrees of load reduction during morning, mid-peak, evening, and overnight periods, with statistical significance noted for most periods.

7.1.2 Snapback Effect The snapback effect refers to premises that usinge more electricity than the baseline during the hours immediately following peak periods, compared to the pre-pilot period. This effect is evaluated based on the same D...

AI summary The snapback effect refers to increased electricity usage following peak periods, evaluated using a DiD approach. MURB TOU participants showed average load reductions during morning and evening snapback periods, with only the morning reduction being statistically significant.

Table 51: Snapback Effect for MURB TOU Participants in Winter Parameters Avg. Load Reduction (kW)a Relative Avg. Load (%)a Reduction Significance (p_Value≤0.05) Morning Snapbackb 1.20 ± 0.48 5.0% ✓ Evening Snapbackc 0.53 ± 0.54 2.3% X Over...

AI summary Table 51 presents the snapback effect for Multi-Unit Residential Building Time-of-Use (MURBTOU) participants during winter, showing load reduction in the morning and overall, but not in the evening. The results indicate statistical significance for morning and overall snapback effects.

7.1.3 Change in Load during Highest ANL Hours [Figure 43](#page-91-0) depicts the distribution of Top 20, 50 and 88 highest ANL hours for MURB TOU participants during morning peak, evening peak, mid-peak, and off-peak hours. As seen in [Fi...

AI summary The text discusses the distribution of highest ANL (Abnormal Load) hours for MURB TOU (Multi-Unit Residential Building Time-of-Use) participants during peak and off-peak hours. It highlights that load reductions occur during the top 20, 50, and 88 highest ANL hours, with statistically significant reductions during the top 50 and 88 hours. Load reductions are also noted during TOU peak periods.

Parameters Highest ANL Hours ANL Hours Coincide TOU Peak Periods Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 Avg. Load (kW)a Reduction 3.3 ± 4.0 4.2 ± 2.9 3.2 ± 2.1 2.9 ± 4.2 3.7 ± 3.0 2.8 ± 2.5 Avg. Load – MURB TOU Participants, Pre-Pilot (...

AI summary The table presents load reduction data for participants in a Time-of-Use (TOU) program, comparing average load reductions before and during the pilot period. It highlights statistical significance and variability in load reduction percentages across different participant groups, with some reductions being statistically significant.

Table 53: Change in Daily Electricity Usage (kWh/day) for MURB TOU Participants Winter Winter Months Parameters Overall January February March November December Avg. Usage Reduction 16.5 ± 30 22 ± 45 33 ± 97 -34 ± 35 66 ± 68 11 ± 34 (kWh/d...

AI summary Table 53 presents the change in daily electricity usage (kWh/day) for Multi-Unit Residential Building Time-of-Use (MURB TOU) participants during winter months. The data shows varying levels of usage reduction and increase across different months, with statistical significance noted for all parameters.

7.1.5 Change in Demand Demand for this evaluation is defined as the maximum 15-minute electricity consumption in terms of power (kW) calculated at AMI interval data frequency (i.e. every 15 minutes)[. Figure 44](#page-93-0) illustrates a c...

AI summary The evaluation examines changes in electricity demand among MURB TOU participants during the Winter months. While some months showed potential demand reductions or increases, these changes were not statistically significant, indicating no overall impact on demand patterns.

Winter Winter Months Parameters Overall January February March November December Avg. Monthly Demand Reduction (kW)a -0.120.48 ± 1.624.45 3.2812. 9 ± 6.1322. 7 -1.666.60 ± 6.0124.0 0.873.5 1 ± 1.385.5 1 -1.656.60 ± 2.7611.2 -0.843.35 ± 2.6...

AI summary The table presents data on average monthly demand reduction and changes in demand for MURB TOU participants during winter and winter months. It includes values for different months and indicates statistical significance for all entries. Positive values indicate demand reduction, while negative values indicate demand increase.

[Figure 45](#page-95-0) illustrates the estimated relative demand reduction (%) overall and across specific TOU periods, including pre-morning peak, morning peak, morning snapback, pre-evening peak, evening peak, and evening snapback. Duri...

AI summary The text discusses estimated demand reductions during specific TOU periods for MURB TOU customers during the Winter 2024/25 evaluation period. While some periods show statistically significant reductions, others are not. The overall demand reduction of 1.4% is significant, with notable reductions during morning snapback and pre-evening peak periods.

Table 55: Changes in Demand by MURB TOU Participants during Winter Parameters Pre Morning b Peak Morning c Peak Morning Snapback d Pre Evening e Peak Evening Peakf Evening Snapbackg Overall Daily Avg. Demand Reduction (kW)a -0.2 80 ± 0.280...

AI summary Table 55 shows changes in demand by MURB TOU participants during winter, including average demand reduction, average demand, relative demand change percentages, and significance levels. The data highlights variations in demand reduction across different time periods and the statistical significance of these changes.

7.2 Economic Impacts This section presents and discusses the impact of MURB TOU Tariff on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of the MURB TOU Tariff, focusing on its influence on electricity bills and price elasticity.

84 12 Nova Scotia Power – Tariffs: January 2025 Table 56: Tariffs Used for Evaluating the Impact of MURB TOU on Electricity Bill Customer Type Period Applicable Tariff Control Pre-Pilot General Tariff Control Pilot General Tariff Treatment...

AI summary The document discusses the impact of MURB TOU on electricity bills, noting an average daily bill saving increase of approximately $124.5, though it is not statistically significant. The MURB TOU rate was designed to save during non-Winter seasons.

Table 57: Change in Daily Electricity Bill by Month during Winter for MURB TOU Participants Winter Winter Months Parameters Overall January February March November December Avg. Bill Savings 12.0-4.5 ± -7.47.7 ± -56.91.7 ± -1.112.3 ± 8.6 3...

AI summary Table 57 presents the change in daily electricity bills by month during winter for MURB TOU participants. It shows average bill savings and relative bill savings percentages, with significance indicators, highlighting variations across different months.

7.2.2 Price Elasticity NS Power evaluated participants' responsiveness to energy price under MURB TOU pricing program, focusing on estimating daily price elasticity and inter-period Substitution Price elasticity. While Daily Price Elastici...

AI summary NS Power evaluated the price elasticity of MURB TOU participants, finding a daily price elasticity of -1.19 and an inter-period substitution elasticity of -0.032. Both values are not statistically significant, indicating limited responsiveness to price changes in electricity usage.

Findings Summary The TVP pilot tariffs have demonstrated success in reducing load during peak periods while providing participating customers with bill savings. Both residential tariff options evaluated continue to demonstrate a strong cap...

AI summary The TVP pilot tariffs have successfully reduced peak load and provided bill savings for residential customers. Both residential and commercial rates show positive load shift, though only in general rate participants. The evaluation supports the continued progress of TVP tariffs in shifting electricity usage to off-peak periods.

Residential TOU & CPP - Participants continue to demonstrate statistically significant reduced load during peak periods with minimal snapback. - For the first time, TVP combined with technology (e.g. smart thermostats) and DR (i.e. Eco Shi...

AI summary Residential Time-Varying Pricing (TVP) combined with technology and Demand Response (DR) has led to significant load reduction during peak periods. Customers who electrified their space heating also showed reduced peak load without significant increases in annual energy consumption.

Commercial TOU & CPP - Participants for the first time have demonstrated statistically significant reduced load during peak periods. This new finding is largely attributable to improvement in methodology and increased sample sizes. - The l...

AI summary The text discusses the effectiveness of Commercial Time-of-Use (TOU) and Conservation Program Participants (CPP) tariffs in reducing load during peak periods, particularly during cold weather. Results show significant load reductions during specific events, though variability exists across rate classes and months.

Multi-Unit Residential Building TOU - Despite the absence of a demand charge, MURB TOU customers did not increase their monthly demand during Winter. - Winter energy and bill savings were positive negative but not statistically significant...

AI summary The analysis of Multi-Unit Residential Building Time-of-Use (MURB TOU) customers showed no increase in monthly demand during Winter despite the absence of a demand charge. Winter energy and bill savings were not statistically significant, but overall, participants showed modest load reductions, particularly during evening peak periods, with no evidence of snapback.

Attachment I: Riders and Tariff Structure A summary of the TVP rate designs is included. For additional details, review the publicly available Tariff book.12F [13](#page-100-5) The volumetric rates used within the billing models are summar...

AI summary This attachment outlines the TVP rate designs and includes a summary of volumetric rates used in billing models, along with visual aids to explain the TVP tariff structures. Further details can be found in the publicly available Tariff book.

Riders Although riders can change throughout a pilot Phase, to control for economic impacts associated with tariff change, a consistent tariff is used for all economic analyses. Riders are applied to all volumetric energy charges on a per...

AI summary Riders are applied consistently across all volumetric energy charges on a per kilowatt-hour basis to control for economic impacts from tariff changes. Table 58 provides a summary of rider rates for different rate classes, including TVP, DSM, and SCR.

Table 59: Tariff Summary (January 2025) Domestic SOR Customer Charge $19.17 per month Energy Charge $0.16931 per kWh Domestic TOU Customer Charge $19.17 per month Energy Charge (Winter on-peak) $0.33862 per kWh Energy Charge (Winter off-pe...

AI summary The document provides a detailed summary of various tariff structures effective January 2025, including Domestic SOR, Domestic TOU, Domestic CPP, Small General SOR, Small General TOU, General SOR, General TOU, General CPP, and MURB TOU. Each tariff includes customer charges, energy charges for different periods, and demand charges where applicable.

Table 60: Top 88 ANL Hours 2020 - 2021 Load - Wind % of Halifax Temp. TOU Period Rank Date Start Time (Adjusted Net Load) Maximum (°C) AM Peak / PM Peak / (MW) Load Off-Peak 1 19-Feb-21 8:00 AM 1,722.6 100.0% -8.7 AM 2 21-Jan-21 5:00 PM 1,...

AI summary Table 60 presents the top 88 ANL (Abnormal Load) hours between 2020 and 2021, including details such as date, start time, adjusted net load in MW, percentage of maximum load, Halifax temperature, and TOU (Time-of-Use) period. The data shows peak load times and their corresponding temperatures and periods.

evaluated sub-group combinations (Table 67) have acceptable group level load similarity and balancing for E1 programming. Sub-Group Possible Sub-Groupings (784 Possible Combinations) TVP Tariff TOU / CPP / MURB TOU Rate Class Domestic / Sm...

AI summary The document evaluates sub-group combinations for E1 programming, focusing on load similarity and balancing. Table 67 outlines various sub-groupings, including TVP tariff, rate class, cohort, neighbourhood, heating classification, and Eco Shift participation, to assess their suitability for control group selection.

a Participants Eco Shift Event Date Event Hour Window Is CPP Event? Is Weekend? All 04-Dec-2024 5 PM – 9 PM ✓ x CPP 15-Dec-2024 5 PM – 9 PM ✓ ✓ All 20-Dec-2024 7 AM – 11 AM ✓ x CPP 22-Dec-2024 5 PM – 9 PM ✓ ✓ All 23-Dec-2024 5 PM – 9 PM ✓...

AI summary The table outlines Eco Shift events scheduled for various dates, specifying event hour windows, participant types (All or CPP), and whether the event occurs on a weekend. The section 'III.2.4 E1 Program Balancing' introduces a discussion on program balancing related to the E1 program.

III.2.6 CPP Reference Days Although the regression model controls for time synchronous (i.e. zero hour lag-lead) temperature effects in the form of heating degree days (HDD), it is critical to find reference days with similar temperature p...

AI summary The document outlines the methodology for selecting reference days in Critical Peak Pricing (CPP) evaluations. It emphasizes the need for similar temperature profiles to event days, using criteria such as weekday type, proximity in time, and temperature comparisons via Euclidean distance to ensure accurate regression results.

III.3 Regression Models The regression models are divided into three sections, Residential TOU & CPP, Commercial TOU & CPP and MURB TOU. Notably, these regression models utilize hourly AMI data on a per-customer basis. This shift from prev...

AI summary The regression models are categorized into Residential TOU & CPP, Commercial TOU & CPP, and MURB TOU. They use hourly AMI data on a per-customer basis, leading to smaller margins of error compared to earlier TVP evaluation reports due to larger sample sizes in Phase 4.

III.3.1 Residential TOU & CPP This section presents the methodology used to determine the load, usage, and economic impact of the residential TOU and CPP tariffs. The estimates for load and economic impacts are rounded and reported accordi...

AI summary This section outlines the methodology for assessing the load, usage, and economic impact of residential Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs. Estimates are rounded to reflect the margin of error at the 90% confidence level, typically using two significant figures.

III.3.1.1 Load & Usage Impact Regression Model The regression model used for load and usage impacts is presented in equation [(7).](#page-123-0) $$Load_{it} = \beta_0 + \beta_1.Treatment_i + \beta_2.PilotPeriod_t + \beta_3.(Pilot \times Tr...

AI summary The Load & Usage Impact Regression Model is presented in equation (7), which estimates the impact of treatment groups under TOU and CPP tariffs on load and energy consumption, incorporating variables such as HDD and pilot periods.

III.3.1.2 Economic Impact Regression Model The regression model used for billing impact is as follows in equation (9). $$DailyBill_{it} = \beta_0 + \beta_1.Treatment_i + \beta_2.PilotPeriod_t + \beta_3.(Pilot \times Treatment)_{it} + \beta...

AI summary The text presents a regression model used to analyze the economic impact of a billing program, incorporating variables such as treatment status, pilot period, HDD, and energy price. The model evaluates daily bill changes and price elasticity, with specific coefficients for each variable and their interactions.

III.3.2 Commercial TOU & CPP This section presents the methodology used to determine the load, usage, and economic impact of the commercial TOU and CPP tariffs. The estimates for load and economic impacts are rounded and reported according...

AI summary This section discusses the methodology used to evaluate the load and economic impacts of commercial Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs. It outlines the use of a Linear Mixed Effect model and semi-DiD method due to the absence of a control group and small sample sizes, highlighting the challenges in analyzing commercial load impacts compared to residential.

III.3.2.1 Load and Usage Impact Regression Model Considering the methodological choices discussed above, the commercial TOU and CPP load/usage, billing as well as daily and substitution price elasticity are described by the equations (14),...

AI summary The document describes a regression model used to analyze the load and usage impact of commercial time-of-use (TOU) and critical peak pricing (CPP) programs. The model incorporates variables such as treatment, pilot period, heating degree days (HDD), and their interactions to estimate load and energy consumption changes.

III.3.2.2 Economic Impact Regression Model $$\begin{aligned} \textit{DailyBill}_{it} &= (\beta_0 + u_i) + \beta_1. Treatment_i + \beta_2. \textit{PilotPeriod}_t \\ &+ \beta_3. (\textit{Pilot} \times \textit{Treatment})_{it} + \beta_4. \tex...

AI summary The text presents three regression models used to analyze the economic impact of energy programs. The models include variables such as treatment, pilot period, heating degree days, and energy prices. The equations are used to assess the effects of demand-side management and time-varying pricing on daily billing, energy usage, and load patterns. The treatment variable is excluded for commercial time-of-use and critical peak pricing analyses due to the lack of control groups.

III.3.3 MURB TOU The evaluation of MURB TOU is based on panel data estimation approach with matched control groups and pre-pilot data using the difference-in-difference (DiD) approach similar to the residential tariffs. Given the relativel...

AI summary The evaluation of MURB TOU uses a difference-in-difference approach with mixed-effects regression due to a small sample size. A review of fixed versus mixed effects was conducted, and mixed-effects were chosen for the regression analysis.

III.3.3.1 Load and Usage Impact Regression Model The same regression as equation (14) was used for load impact and usage impact analyses for MURB TOU.

AI summary The regression model from equation (14) was applied to analyze both load impact and usage impact for MURB TOU in the proceeding.

III.3.3.2 Economic Impact Regression Model The same regression as equations (15), (16) and (17) was used for bill saving and price elasticity analysis for MURB TOU. In addition to the metrics calculated for commercial TOU and CPP, the effe...

AI summary The economic impact regression model was applied to MURB TOU for bill saving and price elasticity analysis. The model uses 15-minute average AMI interval data to estimate demand, serving as a proxy for billed demand in TVP EM&V.

Attachment IV: Historical Methodological Changes All methodological modifications were made through collaboration with stakeholders and/or consultants. These changes and their progression have been summarized with two purposes. - 1. Inform...

AI summary This attachment outlines historical methodological changes made through stakeholder and consultant collaboration. The changes aim to inform readers about potential biases in comparing evaluation reports and highlight progress in rate innovation and evaluation methodology from the TVP pilot program.

IV.1.3 Neighbourhood Criteria & Load Similarity Metric Data (Phase 1, 2, 3) In the previous TVP evaluations (i.e. Phases 1-3) control selection included 2 stages.

AI summary The document discusses the control selection process in previous TVP evaluations, which involved two stages, as part of the Neighbourhood Criteria & Load Similarity Metric Data for Phases 1, 2, and 3.

IV.2.1 Phase 1 Heating classification in Phase 1 was based on rate code (i.e. 02 = Non-Electric, 03 = Electric). Premises are classified as rate 02 and 03 when first registered with NS Power as a customer. These rate codes are often not re...

AI summary In Phase 1, heating classification was based on rate codes (02 = Non-Electric, 03 = Electric), but these codes are not updated when a home's primary heating source changes. This has led to inaccuracies in rate code classifications, especially with increased heat pump adoption.

IV.2.4 Phase 4 Phase 4 (this Phase) of the evaluation uses a similar methodology as Phase 3, with two key distinctions that improved the accuracy of the model. - 1. Heating classification is used in addition to the neighborhood criteria du...

AI summary Phase 4 of the evaluation improves accuracy by using heating classification alongside neighborhood criteria for control group selection and restricting AMI data to overnight hours for heating classification. This ensures accurate load impact analysis and captures the effect of TVP price signals on space heating behavior.

Attachment V: Validation of Mixed Effects Regression The NS Power commercial TVP evaluations (Phase 1 – 3)24F [25](#page-137-1) has historically provided statistically insignificant results. Findings such as "statistically insignificant" c...

AI summary This document discusses the limitations of previous TVP evaluations by NS Power, noting that statistically insignificant results may stem from low statistical power or methodological issues. It highlights the difference between residential and commercial customer load profiles and explains how the use of a fixed effects regression model for commercial customers may have introduced Type II errors. In Phase 4, a mixed effects regression model was implemented to better account for commercial load heterogeneity.

ers Evaluated for Load Reduction during CPP Events, along with the Residual Error Distribution Associated with (c) Fixed Effect Modelling and (d) Mixed-Effect Modelling Given the baseload heterogeneity, time-series (hourly) load data and t...

AI summary The text discusses the use of Mixed-Effect modelling for analyzing commercial TOU and CPP load response, noting its improved model fit and balanced error structure compared to Fixed Effect modelling, due to baseload heterogeneity and business type variability.

MURB TOU Customers Unlike the commercial TOU and CPP rates, MURB TOU has not yet been evaluated using the fixed effects regression model. As such additional analyses are provided within in order to validate the choice of a mixed effects re...

AI summary The document discusses the evaluation of MURB TOU customers using a mixed effects regression model with a control group, as the fixed effects regression model has not yet been applied to this specific tariff.

Demand Response Overlap between NS Power and E1 In its Decision on E1's 2026 DSM Extension Application (M12249), the Board provided: The Board agrees that concerns about E1's demand response programs are better addressed in its consultatio...

AI summary The Board's decision on E1's 2026 DSM Extension Application (M12249) highlights concerns about potential overlap between E1's demand response programs and NS Power's Critical Peak Pricing Program. The Board expects E1 to address these concerns in its upcoming DSM Plan application and for NS Power to cooperate fully. An evaluation was conducted to assess load shift effects from overlapping programs.

Coincidence of Critical Peak Events and System Margin In its Decision and Order on the Year Three (2023/24) Evaluation Report (Year Three Report) in M11823, the Board provided: NS Power agreed with Synapse that system margin forecasts may...

AI summary The document discusses the relationship between system margin forecasts and Critical Peak Events (CPP) during the 2024/25 Winter Season. It notes that system margin forecasts during CPP events were significantly lower than during other peak hours and directs NS Power to analyze this correlation further in the Year 4 report.

Reporting on Small Business Characteristics that Enable Load Shifting As part of its 2024 TVP Consensus Agreement, the Company committed to: h. Reporting back to stakeholders on changes that could be made to help customers determine whethe...

AI summary As part of its 2024 TVP Consensus Agreement, NS Power committed to reporting on small business characteristics that enable load shifting, including load characteristics, recruitment tactics, and customer reluctance to participate in TVP, TOU, and CPP options.

Review of Marketing and Communication Efforts In its Decision and Order on the Year Three Report (M11823), the Board provided: Narrative Research conducted a customer survey, which highlighted residential customers' dissatisfaction regardi...

AI summary The Board directed NS Power to review its marketing and communication efforts, particularly regarding bill savings expectations for residential and commercial customers. NS Power has implemented tools and strategies to improve communication, including estimation tools for residential customers and coordinated approaches with commercial clients. Appendix C and E provide details on marketing efforts and stakeholder sessions.

Time-Varying Pricing Pilot Program Phase 4 Evaluation, Measurement & Verification Report June 30, 2026

AI summary This document is an Evaluation, Measurement & Verification Report for Phase 4 of the Time-Varying Pricing Pilot Program, dated June 30, 2026. It likely details the outcomes and performance of the program's fourth phase.

Definitions Adjusted Net Load The hourly net system requirement (MW) less all wind generation (MW) Cohorts Cohorts are numbered based on the Phase they enrolled in the TVP program. For example, Cohort 4 refers to participants recruited in...

AI summary The document defines key terms used in the regulatory proceeding, including Adjusted Net Load, Cohorts, Commercial, Consumption, Control, Demand, and Income categories. These definitions provide clarity on metrics and classifications relevant to the analysis of energy programs and customer data.

Nova Scotia Power (NS Power, Company) launched the Time-Varying Pricing (TVP) Tariff Pilot on November 1, 2021, with the purpose of encouraging customers to shift load from Winter peak periods to Winter off-peak periods. These tariffs pres...

AI summary Nova Scotia Power's Time-Varying Pricing (TVP) Tariff Pilot, launched in 2021, encourages load shifting to reduce winter peak energy demand. The fourth annual report highlights expanded participation, refined evaluation methods, and statistically significant load reductions, especially during high adjusted net load hours. The report also evaluates the first results for Multi-unit Residential Building (MURB) participants.

Tariffs Both TOU and CPP are available in the Domestic, Small General, and General rate classes, whereas MURB TOU is available to MURBs in the General rate class. A summary of the TVP Tariffs is provided in Attachment [I: Riders and Tariff...

AI summary The document outlines the structure of Time-Varying Pricing (TVP) tariffs, including TOU and CPP, detailing peak and off-peak periods, rates, and differences between rate classes such as Domestic, Small General, General, and MURB. It also explains the frequency and timing of CPP events and their associated pricing.

Residential Findings In total, 5,616 TOU and 2,642 CPP residential customers participated in the TVP program in Phase 4. Of these, 4,938 TOU and 2,310 CPP customers were included in the regression when counting only those who meet the crit...

AI summary Phase 4 of the TVP program saw 5,616 TOU and 2,642 CPP residential customers participate, with 4,938 TOU and 2,310 CPP customers included in the regression analysis. Participants achieved significant electricity load reductions during peak periods and events, consistent with Phase 3 results.

Table 1: Summary of Peak Load Reductions by Residential TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) TVP Tariff Morning Peak Evening Peak Morning Peak Evening Peak Residential TOU 0.15 kW 0.17 kW 7.4% 7.9% Residentia...

AI summary Table 1 summarizes peak load reductions by residential TVP tariff, showing that Residential CPP achieved higher reductions than Residential TOU. The text also discusses energy consumption patterns, technology impacts, and the benefits of electrification on load reduction and cost savings.

Commercial Findings The commercial TVP Tariffs attracted more businesses, with Phase 4 enrolment (108 businesses) higher compared to Phase 3 (65 businesses). While "small sample size and the wide variety of energy consumption profiles prev...

AI summary The commercial Time-Varying Pricing (TVP) Tariffs attracted more businesses in Phase 4 compared to Phase 3, with improved regression analysis enabling a more robust assessment of load and economic impacts. Significant electricity load reductions were achieved during peak periods and events.

3 M11823 – TVP Pilot Program — 2023/24 (Year Three) Evaluation Report, Appendix A, page 51. July 31, 2024. TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) Morning Peak Evening Peak Morning Peak Evening Peak Commercial T...

AI summary This table summarizes load reductions by commercial TVP tariff, showing absolute and relative reductions during morning and evening peaks, with statistical significance confirmed for all metrics.

MURB TOU Findings Phase 4 marks the first load and economic impacts evaluation of the MURB TOU Pilot Tariff. Ten MURBs were recruited and are enrolled in the MURB TOU Tariff. For the MURB TOU Tariff, this Phase 4 evaluation includes the Wi...

AI summary Phase 4 of the MURB TOU Pilot Tariff evaluation found a 0.48 kW load reduction during peak periods, with evening reductions being statistically significant. However, load increased significantly in March. The evaluation covers the winter period from November 2024 to March 2025.

Table 3: Summary of Load Reductions from MURB TOU Tariff TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) Morning Peak Evening Peak Morning Peak Evening Peak MURB TOU 0.44 kW 0.54 kW 1.8% 2.1% Statistical Significance X...

AI summary Table 3 summarizes load reductions from the MURB TOU tariff, showing absolute and relative reductions during morning and evening peaks. Only evening peak results are statistically significant.

Introduction Time-Varying Pricing (TVP) is a scalable customer-focused demand response (DR) program. In Nova Scotia, the TVP pilot has grown significantly since it began in November 2021. Since its inception, the TVP pilot has offered two...

AI summary Time-Varying Pricing (TVP) is a demand response program in Nova Scotia that offers customers TOU and CPP tariffs. The TVP pilot has expanded since 2021, with a new MURB TOU Tariff launched in 2024. The program aims to reduce fuel and power costs by shifting demand from peak periods and is evaluated through an EM&V report.

Introduction The first year a cohort enters the TVP pilot (e.g. Cohort 2 in Phase 2), the evaluation for this cohort was limited to the Winter period (i.e. November to March). Subsequent evaluations for all cohorts include a full year (i.e...

AI summary The evaluation of the TVP pilot program for the first year of a cohort is limited to the winter period (November to March), while subsequent evaluations cover a full year (April to March). Evaluation metrics are categorized into 'Load & Usage' and 'Economic'.

Table 4: Impact Evaluation Metric Summary Category Metric TOU, CPP, MURB TOU (all rate classes unless specified) • Change in load (kW) during peak, and overall impact during Winter and non-Winter. Mid-peak hours included for MURB TOU. • Ch...

AI summary Table 4 outlines the impact evaluation metrics for load and usage changes during peak periods, including changes in load by region, income classification, and space heating. It also covers economic impacts such as changes in electricity bills and price elasticity related to time-varying pricing programs.

The TVP pilot program has increased enrolment year over year with a total of 8,376 participants at the end of Phase 4. Refer to [Table 5](#page-21-0) and [Table 6](#page-21-1) for participation summaries.

AI summary The TVP pilot program has seen increasing participation, with 8,376 participants by the end of Phase 4. Participation summaries are detailed in Table 5 and Table 6.

Table 5: TVP Participation on March 31 by Phase and Tariff Phase DOM TOU SMG TOU GEN TOU DOM CPP SMG CPP GEN CPP MURB TOU Total Phase 1 676 24 8 0 992 Phase 2 891 17 373 2 0 1,283 Phase 3 2,241 37 19 922 3 6 0 3,228 Phase 4 5,616 37 18 2,6...

AI summary Table 5 and Table 6 present data on Time-Varying Pricing (TVP) participation across different phases and tariffs, highlighting the number of participants and retention rates. The retention rates range from 87% for Domestic TOU to 100% for MURB TOU. The data includes enrollment, withdrawals, and retention numbers for each phase and tariff category.

2 Control Group Selection The control group selection methodology uses 1-hour average and 15-minute peak load data to determine the best 1:1 control match by four neighbourhoods. If treatment customers are distributed throughout the provin...

AI summary The document discusses the methodology for selecting control groups in a regulatory proceeding, using geographic distribution data to ensure that treatment and control customers are proportionally aligned with Nova Scotia's population distribution. This ensures accurate comparisons between programs like CPP and TOU.

2.1 Residential TOU & CPP To best evaluate load and billing effects of the TVP pilot, it is important to have a control group with similar load characteristics to that of the treatment group. The control group selection load profile match...

AI summary The analysis compares the residential TOU and CPP control and treatment groups, showing a 96% match accuracy in load profiles. While baseline characteristics like income and housing style are similar, living space and electric space heating penetration differ, contributing to higher energy consumption in TVP customers compared to the average residential customer.

Group Energy (kWh) SOR 10,225 TVP 12,678 2.1.1 Eco Shift

AI summary The document presents a table comparing energy usage (in kWh) for different groups, specifically highlighting SOR and TVP. The section '2.1.1 Eco Shift' is introduced, indicating a potential discussion on energy efficiency programs or initiatives.

2.2 Commercial TOU & CPP The same methodological approach as used with residential control group (with exception to Neighbourhood Criteria, Heating Classification, and Eco Shift) was used in attempting to select a control group for Small G...

AI summary The document discusses the methodology used to select control groups for Commercial TOU and CPP rates, noting poor matching for Small General and General customers, leading to within-subject regression analysis. However, the MURB TOU control group selection was successful with a match accuracy of ≥90%.

2.4 CPP Reference Days The CPP reference days were selected for Phase 4 are summarized in Table 8. HALIFAX KENTVILLE NAPPAN SHEARWATER SYDNEY WESTERN YARMOUTH Event Day TRACADIE AIRPORT CDA CS AUTO RCS AIRPORT HEAD AIRPORT 12/4/2024 12/3/2...

AI summary The document outlines the selection of Critical Peak Pricing (CPP) reference days for Phase 4, highlighting that most weather stations share the same reference day, while some events have different reference days based on location. The temperature profiles of reference and event days are compared using statistical measures such as MAE, RMSE, and R², showing a strong correlation.

3 Residential TOU Tariff Impacts This section presents the analysis results for load and economic impacts of Residential TOU tariffs for all cohorts in Phase 4. The goal of the residential TOU pilot is to encourage customers to shift their...

AI summary This section evaluates the load and economic impacts of Residential TOU tariffs in Phase 4, aiming to encourage customers to shift electricity usage from peak to off-peak periods. Cohort 4 has significantly more participants than the combined total of cohorts 1-3, and participants with steady electric heating systems are more common than those with other heating types.

Parameter Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Sample Size 430 190 1,016 3,302 4,938 Heating Type Steady Electric 48% 65% 61% 61% 60% Steady Non-Electric 26% 18% 22% 25% 24% Electrified 22% 11% 11% 9% 10% De-Electrified 4% 6% 6% 5% 6% R...

AI summary Table 9 provides a summary of the residential TOU sample size, including distribution across different cohorts and regions. It details the percentage of homes using steady electric, non-electric, electrified, and de-electrified heating types, along with regional distribution in Nova Scotia.

3.1 Load & Usage Impacts This section presents and discusses the electrical load impact from the residential TOU Tariff.

AI summary This section discusses the electrical load impact resulting from the residential Time-of-Use (TOU) Tariff, focusing on how it affects residential electricity usage patterns.

3.1.1 Change in Load during Peak Periods [Table 10](#page-34-0) summarizes the results of the analysis for morning and evening TOU peak hours for each cohort and for all cohorts combined. The average load reductions are presented along wit...

AI summary The document discusses load reductions during peak periods for residential TOU participants, showing statistically significant reductions in both morning and evening hours. Evening peak hours saw slightly higher reductions, with overall load reductions of 0.15 kW and 0.17 kW during morning and evening periods, respectively. The analysis also highlights the impact of outdoor temperature on load shifts.

Change in Load by Space Heating Classes during TOU Peak Hours [Table 11](#page-37-0) summarizes the average load reductions during morning and evening TOU peak hours for space heating classes of all cohorts combined in Phase 4. The load re...

AI summary The text discusses load reductions during TOU peak hours for different space heating classes. Steady electric heating systems show the highest reductions, while non-electric systems show the lowest. Electrification of heating systems also results in load reductions, though less than steady electric systems.

Morning Evening Parameters De - El ec tr ifi ed El ec tr ifi ed El St ec ea tr dy ic No St n- El ea ec dy tr ic De - El ec tr ifi ed El ec tr ifi ed El St ec ea tr dy ic No St n- El ea ec dy tr ic Avg. Load Reduction 0.15 ± 0.07 ± 0.18 ± 0...

AI summary The table presents load reduction data for residential Time-of-Use (TOU) participants before a pilot program, showing average load reductions and percentages across different parameters. The data indicates significant reductions in load, with all values marked as statistically significant.

Change in Load by Region, Income Level, and Residents per Household [Figure](#page-37-1) 15 illustrates the average load reduction achieved by TOU participants according to the region of premises in Nova Scotia. While no significant differ...

AI summary The document analyzes load reduction among TOU participants in Nova Scotia, showing higher evening load reduction in the Halifax area and higher absolute load reductions among higher-income participants, though relative reductions do not vary significantly by income level.

Low-Income Medium-Income High-Income Parameters AM Peak PM Peak All Peak Hours AM Peak PM Peak All Peak Hours AM Peak PM Peak All Peak Hours Avg. Load 0.14 ± 0.15 ± 0.15 0.12 ± 0.16 ± 0.14 0.18 0.19 0.19 (kW) a Reduction 0.01 0.01 ± 0.01 0...

AI summary The table presents load reduction percentages for low-, medium-, and high-income residential TOU participants before the pilot, with significant reductions observed across all income levels, indicating the effectiveness of time-varying pricing in load management.

Change in Load with Eco Shift E1's Eco Shift is a DR initiative offered separately from TVP and was implemented within subset of the TVP treatment participants who opted into both programs. It is designed to encourage load reduction during...

AI summary E1's Eco Shift DR initiative, when combined with TOU, significantly increased load reduction during peak hours. Analysis using DDD regression showed an additional 0.29 kW reduction during all TOU peak hours, with even greater reductions during morning and evening events. The combined effect of TOU and Eco Shift led to a total load reduction of 0.66 kW during Eco Shift events.

3.1.2 Snapback Effect While the TOU participants exhibit relatively small but statistically significant load increase of 0.014 kW during evening snapback period, they reduced their electricity usage by 0.013 kW during morning snapback hour...

AI summary The text discusses the snapback effect observed in TOU (Time-of-Use) participants, noting a small but statistically significant load increase of 0.014 kW during evening snapback periods and a reduction of 0.013 kW during morning snapback hours, though overall changes were statistically insignificant.

Table 13: Snapback Effect for Residential TOU Participants Parameters Load Reduction a (kW) Avg. Significance (p_Value≤0.05) Morning Snapback 0.013 ± 0.004 ✓ Evening Snapback -0.014 ± 0.005 ✓ Overall Snapback -0.002 ± 0.003 X a Positive an...

AI summary Table 13 presents the snapback effect for residential Time-of-Use (TOU) participants, showing load reduction during morning and evening hours, with the overall effect being statistically insignificant. The data indicates a slight increase in electricity usage during the evening and a small reduction in the morning.

[Figure](#page-42-0) 20 depicts the distribution of Top 20, 50, and 88 highest ANL hours for residential TOU participants during morning peak, evening peak, and off-peak hours as well as weekends and holidays. As provided in [Figure](#page...

AI summary The text discusses the distribution of highest ANL hours for residential TOU participants and highlights significant load reductions during these periods. Results show a 6% relative load reduction during top ANL hours coinciding with TOU peak periods, with absolute reductions of 0.17 kW.

Participants Parameters High Highest ANL Hours ANL Hours Coincide TOU Peak Periods Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 Avg. Load 0.16 ± 0.04 0.14 ± 0.13 ± 0.17 ± 0.17 ± 0.17 ± Reduction (kW) a 0.16 ± 0.04 0.03 0.02 0.03 0.03 0.02 Avg...

AI summary The table presents statistical analysis of load reduction among participants in a demand response program, comparing average load, reduction in kW, and relative load reduction percentages across different participant tiers. It highlights the effectiveness of the program in reducing energy usage during peak periods.

Table 15 summarizes changes in daily electricity usage level for cohorts 1 to 4 and all cohorts combined during non-holiday weekdays and holiday weekends in Winter. All cohorts exhibit statistically significant reduction in daily usage lev...

AI summary Table 15 shows a statistically significant reduction in daily electricity usage for residential TOU participants during non-holiday weekdays and holiday weekends in Winter. The overall average load reduction was 1.39 kWh on non-holiday weekdays, with an additional 0.6 kWh reduction on holidays and weekends.

Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Weekdays Avg. Usage Reduction 1.71 ± 2.70 ± 1.64 ± 1.10 ± 1.39 ± a (kWh/day) 0.21 0.31 0.14 0.08 0.06 Avg. Usage – Residential TOU Participants, Pre-Pilot 39.4 50.4 43....

AI summary The table presents usage reduction data across four cohorts during different seasons, showing average kWh/day reductions and relative usage reductions in percentages. Statistical significance is marked with a check, indicating consistent results across all cohorts.

[Table 16](#page-45-0) presents changes in daily electricity usage levels by space heating. During non-holiday weekdays in Winter, TOU participants with electrified space heating exhibit insignificant change in their daily usage level. Not...

AI summary Table 16 shows changes in daily electricity usage by space heating type for residential TOU participants. During non-holiday weekdays, electrified heating shows no significant change, but increases during holidays. De-electrified systems show reductions during non-holiday weekdays, while steady electric heating systems show reductions during both periods. Overall, savings are statistically significant and amount to 300 kWh annually on average.

Parameters De - El ec tr ifi ed El ec tr ifi ed El St ec ea tr dy ic No St n- El ea ec dy tr ic Winter, Non-Holiday Weekdays a Avg. Usage Reduction(kWh/day) 0.75 ± 0.20 -0.09 ± 0.14 1.96 ± 0.10 0.15 ± 0.07 Avg. Usage – Residential TOU Part...

AI summary The document presents data on average usage reduction across different seasons and customer segments, showing that residential TOU participants experienced varying levels of reduction, with higher reductions during non-holiday weekdays. No significant differences were found among income levels or between Halifax and other regions.

3.2 Economic Impacts This section presents and discusses the impact of residential TOU tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of residential time-of-use (TOU) tariffs on electricity bills and price elasticity, analyzing how these tariffs affect consumer spending and behavior.

3.2.1 Change in Electricity Bills [Table 17](#page-46-2) summarizes the applicable tariffs used for residential TOU impact on billing. Tariff details can be found in [Attachment I: Riders and Tariff Structure.](#page-100-0) Customer Type a...

AI summary This section discusses the change in electricity bills, focusing on the impact of residential Time-of-Use (TOU) tariffs. Table 17 outlines the applicable tariffs for different customer types and periods, showing that the Domestic Standard Tariff was used for control groups, while the Domestic TOU Tariff was applied to treatment groups during the pilot period.

[Table 18](#page-47-0) presents the bill impact for residential TOU, where participants exhibit an overall annual average bill saving of $0.30 per day, corresponding to 5.5% of average annual bill. This amount of annual bill saving is stat...

AI summary Table 18 shows that residential TOU participants saved an average of $0.30 per day annually, or 5.5% of their average bill. Non-Winter savings were higher at $1.54 per day, due to lower rates during non-Winter periods. However, during Winter, bill increases of $1.34 per day occurred, as TOU peak rates were twice off-peak rates, which offset savings from load reduction.

Table 18: Change in Daily Electricity Bill for All Cohorts of Residential TOU Participants Parameters Winter Non- Holiday Weekdays Winter Holiday/ Weekends Winter Overall Non-Winter Annual Average Avg. Bill Savings ($/day) a -2.05 ± 0.01 0...

AI summary Table 18 presents the change in daily electricity bills for residential TOU participants across different time periods and categories. It shows average bill savings, pre-pilot average bills, relative savings percentages, and significance levels. The data indicates mixed results, with savings in non-winter periods and increases during winter.

The analysis reveals that the type of space heating has significant influence on the bill impact for the TOU participants. While TOU participants with all space heating types experienced significant increases in bills during Winter season,...

AI summary The analysis shows that TOU participants with electrified space heating achieve average annual bill savings of $153, while all space heating types show significant savings during non-Winter seasons. However, the analysis does not account for additional fuel costs or savings from non-electric heating sources.

- & lt;sup>8 TOU rates were 32.12 ¢/kWh during peak hours and 16.931 ¢/kWh during off-peak hours. Table 19: Change in Daily Electricity Bill by Space Heating Type for All Cohorts of Residential TOU Participants Parameters El ec De tr ifi e...

AI summary The document presents data on the impact of Time-of-Use (TOU) rates on residential electricity bills, showing significant savings during non-winter months and mixed results during winter. It also introduces a section on price elasticity, indicating a focus on how pricing affects consumer behavior.

4 Residential CPP Tariff Impacts This section presents the analysis results for load and economic impacts of the Domestic CPP Tariff for all cohorts in Phase 4. The goal of the residential CPP pilot is to encourage customers to shift their...

AI summary This section discusses the load and economic impacts of the Domestic CPP Tariff during Phase 4, from April 1, 2024, to March 31, 2025. The goal is to encourage customers to shift electricity usage during CPP events, reducing system costs through demand response and infrastructure savings.

Change in Load by Space Heating Classes During Peak Events [Table 23](#page-52-0) summarizes the average load reductions during morning and evening events for space heating classes of all cohorts combined in Phase 4. It is important to not...

AI summary Table 23 summarizes average load reductions during morning and evening peak events for space heating classes in Phase 4. The analysis compares event and reference days during the 2024/25 Winter, noting that changes in space heating type between baseline and pilot periods do not directly impact load reduction results in the DiD analysis.

Change in Load per Critical Peak Event [Figure](#page-53-0) 23a illustrates the average load reduction (kW) per CPP event date for all Phase 4 cohorts, along the corresponding event-average outdoor temperature (°C). The residential CPP par...

AI summary The document analyzes load reduction patterns among Critical Peak Pricing (CPP) participants in Nova Scotia. It shows that residential participants achieve significant load reductions, with higher reductions during evening events and in the Halifax area. Higher-income participants also exhibit greater load reduction percentages compared to lower-income participants.

4.1.2 Snapback Effect The CPP participants exhibit relatively small but statistically significant snapback effects during morning, evening and double-event snapback periods, indicating significant increase in electricity usage during the f...

AI summary CPP participants show small but statistically significant snapback effects, with a 0.15 kW increase in electricity usage during double-snapback periods compared to single morning or evening events.

Table 25: Snapback Effect for Residential CPP Participants Parameters Average Load Reduction a (kW) Significance (p_Value≤0.05) Morning Snapback -0.04 ± 0.02 ✓ Evening Snapback -0.08 ± 0.03 ✓ Double-Event Snapbackb -0.15 ± 0.05 ✓ Overall S...

AI summary Table 25 presents the snapback effect for residential Critical Peak Pricing (CPP) participants, showing average load reductions during morning, evening, and double-event snapback periods, with statistical significance indicated. The results suggest that CPP programs lead to reduced electricity usage during peak times.

Chapter 4: Residential CPP Tariff Impacts approximately 40%, 28% and 21% of all CPP events, which coincided with the top 20, 50 and 88 ANL hours, respectively, occurred during weekdays, while only 15%, 8% and 6% of CPP events, which coinci...

AI summary Chapter 4 discusses the impact of residential Critical Peak Pricing (CPP) tariff on load reduction. The analysis shows that CPP participants achieved statistically significant load reductions during the highest Adjusted Net Load (ANL) hours, with slightly higher reductions during CPP peak periods compared to overall highest ANL hours.

Parameters Highest ANL Hours ANL Hours Coincide with CPP Events Top 20 Top 50 Top 88 Top 20 Top 50 Top 88 Avg. Load Reductiona (kW) 0.75 ± 0.63 ± 0.55 ± 0.85 ± 0.84 ± 0.80 ± 0.07 0.06 0.04 0.07 0.06 0.05 Avg. Load – CPP Participants, Pre-P...

AI summary Table 26 presents data on load reduction during highest winter ANL hours for residential CPP participants, showing average load reductions and significance levels. The data indicates a reduction in average load for participants compared to pre-pilot levels, with statistical significance noted for all categories.

The change in daily usage levels was evaluated through two analyses. For the first analysis, the daily usage reduction during event days was estimated, when at least one CPP event occurred, compared to reference days. For the second analys...

AI summary The document evaluates the impact of Critical Peak Pricing (CPP) on daily electricity usage through two analyses. The first analysis found that CPP participants reduced their daily usage by 1.7 kWh during event days compared to reference days, with cohort 4 showing a statistically significant reduction. However, reductions were not significant for other cohorts or heating-class segments.

Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Weekdays Avg. Usage Reduction a (kWh/day) 3.0 ± 1.4 3.1 ± 2.0 1.0 ± 0.9 1.1 ± 0.5 1.2 ± 0.4 Avg. Usage – Residential CPP Participants, Pre-Pilot (kWh/day) 50.7 60.5 44....

AI summary The table presents data on average usage reduction and relative usage reduction across different cohorts during winter non-holiday weekdays, winter weekends/holidays, and non-winter days. The results show significant reductions in energy usage, particularly during winter non-holiday weekdays, with statistical significance noted for most cohorts.

[Table 29](#page-61-1) presents changes in daily electricity usage level by space heating for all cohorts of residential CPP participants during pilot period compared to pre-pilot period. During non-holiday weekdays in Winter, CPP particip...

AI summary Table 29 shows that during the pilot period, residential CPP participants with electrified space heating had a 13% increase in daily electricity usage, while de-electrified and steady electric participants saw reductions. Steady non-electric participants showed no significant change in usage.

4.2 Economic Impacts This section presents and discusses the impact of residential CPP tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of residential CPP tariffs on electricity bills and examines price elasticity, highlighting how these tariffs influence consumer behavior and financial outcomes.

4.2.1 Change in Electricity Bills [Table 30](#page-62-3) summarizes the applicable tariffs used for residential CPP impact on billing. Tariff details can be found in [Attachment I: Riders and Tariff Structure.](#page-100-0)

AI summary This section discusses the change in electricity bills, referencing Table 30 and Attachment I for details on applicable tariffs and rider structures affecting residential customers.

Table 30: Tariffs Used for Analyzing Residential CPP Impact on Electricity Bill Customer Type and Period Applicable Tariff Control, Reference Day Domestic Standard Tariff Control, during Pilot Domestic Standard Tariff Treatment, Reference...

AI summary Table 30 and Table 31 analyze the impact of the Residential CPP on electricity bills. The Domestic CPP Tariff results in significant savings, especially during non-Winter days and weekends/holidays in Winter, due to lower rates during non-peak hours compared to peak hours.

Parameters De- Electrified Electrified Steady Electric Steady Non-Electric Winter Avg. Bill Savings ($/day) a $0.36 \pm 0.04$ -0.47 ± 0.03 $0.56 \pm 0.02$ 0.14 ± 0.01 Avg. Bill – Residential CPP, Pre- Pilot ($/day) 6.3 8.0 10.3 3.4 Relativ...

AI summary The text presents a table comparing average bill savings and relative bill savings percentages for different electrification scenarios during winter, non-winter, and annual periods. The data shows significant variations in savings, with some scenarios showing bill increases. The significance of these findings is indicated with p-values.

5 Commercial TOU Tariff Impacts This section presents and discusses the estimated load and economic impacts of the commercial TOU program. The goal of the commercial TOU pilot is to encourage customers to shift their electricity usage from...

AI summary This section discusses the estimated load and economic impacts of the commercial TOU program, aiming to encourage load shifting by offering customers lower energy bills during off-peak periods. The sample size for Phase 4 includes 50 participants, with most enrolled in earlier cohorts.

5.1.1 Change in Load during Peak Periods [Figure](#page-66-1) 31 illustrates the load profiles for commercial TOU participants during the pre-pilot and pilot periods, along with the corresponding variation in outdoor temperature during the...

AI summary The analysis shows that commercial TOU participants reduced their electricity load during peak hours by an average of 0.8 kW, with reductions of 6.4%, 8.6%, and 7.4% during morning, evening, and overall peak periods, respectively. The results are statistically significant and consistent with the load profiles shown in Figure 31.

Chapter 5: Commercial TOU Tariff Impacts TOU participants located in the Halifax area exhibit statistically significant load reductions during both morning and evening peak hours with an overall load reduction of 1.4 kW, corresponding to 1...

AI summary Commercial TOU participants in the Halifax area show significant load reductions during peak hours, with a 12% overall reduction. Participants in other regions of Nova Scotia also show reductions, but only during evening peak hours and overall load reduction is statistically significant.

Halifax Area Rest of Nova Scotia Parameters Morning Peaks Evening Peaks All Peak Hours Morning Peaks Evening Peaks All Peak Hours Avg. Load Reduction (kW)a 1.22 ± 0.29 1.49 ± 0.31 1.38 ± 0.20 0.16 ± 0.17 0.24± 0.18 0.20 ± 0.15 Avg. Load ‒...

AI summary The table provides load reduction data for Halifax Area and Rest of Nova Scotia under time-of-use (TOU) programs. It shows average load reductions during peak hours and their significance, with higher reductions noted in the Halifax Area compared to the Rest of Nova Scotia.

Change in Load by Month during Peak Periods [Figure](#page-69-2) 33 illustrates the impact of commercial TOU in terms of average load reduction (kW), together with the average outdoor temperature (°C) during peak hours by month over the Wi...

AI summary Figure 33 shows the impact of commercial time-of-use (TOU) pricing on load reduction during winter peak periods from November 2024 to March 2025. Load reductions were significant across most months, with the largest reduction of 1.6 kW occurring in February 2025, despite low temperatures.

Table 38: Change in Daily Electricity Usage (kWh/day) for Commercial TOU Participants Parameters Annual Average Winter Overall Winter – Non-Holiday Weekdays Winter – Holiday Weekends Non Winter Avg. Usage Reduction (kWh/day)a -15.4 ± 3.9 -...

AI summary Table 38 presents the change in daily electricity usage (kWh/day) for Commercial TOU participants across different time periods. It includes average usage reduction, relative usage reduction percentages, and significance levels. The data indicates varying degrees of usage reduction during different seasons and days of the week.

5.2 Economic Impacts This section presents and discusses the impact of commercial TOU tariffs on the electricity bill as well as price elasticity. a Positive values represent 'Load Reduction' and Negative values represent 'Load Increase'

AI summary This section discusses the economic impacts of commercial time-of-use (TOU) tariffs on electricity bills and price elasticity, with positive values indicating load reduction and negative values indicating load increase.

5.2.1 Change in Electricity Bills The bill impact analysis for the commercial TOU uses the same method that was used for estimating the commercial TOU load impact analysis. In the bill impact analysis, applicable tariffs applied in accorda...

AI summary The document discusses the method used for analyzing the impact of commercial time-of-use (TOU) tariffs on electricity bills, referencing Table 39 and an attachment for detailed tariff information.

Customer Type Period Applicable Tariff Treatment – General Pre-Pilot General Tariff – Rate Code 11 Treatment – General Pilot General TOU Tariff – Rate Code 83 Treatment – Small General Pre-Pilot Small General Tariff – Rate Code 10 Treatmen...

AI summary The document outlines the changes in daily electricity bills for commercial TOU participants during the Winter season and annually in Phase 4, showing an average increase of 11.9 \/day and 1.1 \/day, respectively, consistent with increased electricity usage.

Table 40: Change in Daily Electricity Bill for Commercial TOU Participants Parameters Winter Non-Winter Annual Overall Bill Savings ($/day)a Avg. -11.9 ± 3.4 6.2 ± 3.1 -1.1 ± 3.1 Avg. Bill, Commercial TOU Participants, Pre-Pilot 36.7 37.4...

AI summary Table 40 shows the change in daily electricity bills for commercial TOU participants, with winter savings of -11.9 \/day and non-winter savings of 6.2 \/day. Annual overall savings are -1.1 \/day. Savings percentages are -32% in winter, 16.7% in non-winter, and -3.1% annually. Significance is indicated for winter and non-winter, but not for annual overall.

5.2.2 Price Elasticity Daily Price Elasticity reflects the change in overall daily electricity usage caused by changes in the average daily price ($) per kWh. It is expressed as the percent (%) change in the average electricity usage assoc...

AI summary Price elasticity measures how changes in electricity prices affect daily usage and load shapes. Daily price elasticity refers to changes in overall daily usage due to price changes, while inter-period substitution price elasticity refers to shifts in load from peak to off-peak periods based on price ratios.

6 Commercial CPP Tariff Impacts This section presents and discusses the estimated load and economic impacts of the commercial CPP program. The goal of the commercial CPP pilot is to encourage customers to shift their electricity usage from...

AI summary This section discusses the estimated load and economic impacts of the commercial Controlled Load Program (CPP) pilot, which aims to shift electricity usage from peak to off-peak periods. The analysis uses a Mixed-Effects modeling semi-DiD approach and covers CPP events from November 2024 to March 2025.

Chapter 6: Commercial CPP Tariff Impacts [Figure](#page-78-0) 37b further disaggregates results of the average load reduction by morning and/or evening events per CPP event date. Notably, commercial CPP participants exhibited an average lo...

AI summary Chapter 6 examines the impact of the Commercial Controlled Load Program (CPP) tariff on load reduction. While some events showed load increases, others, particularly consecutive events, resulted in significant reductions. However, data limitations prevent broader conclusions about consecutive events' overall impact.

6.2 Economic Impacts This section presents and discusses the impact of commercial CPP tariffs on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of commercial CPP tariffs on electricity bills and price elasticity, highlighting how these tariffs influence consumer behavior and costs.

7 MURB TOU Tariff Impacts As this Phase represents the first year of the MURB TOU pilot program, participation was limited to 10 enrolled MURBs, with the pilot period beginning on November 1, 2024. The goal of the MURB TOU pilot is to info...

AI summary The MURB TOU pilot program, starting in November 2024 with 10 enrolled MURBs, aims to assess the impact of removing the demand charge on load shifting potential compared to the commercial TOU pilot. This section discusses the estimated impacts on load and economics.

Parameters Morning Peak Mid-Peak Periodb Evening Peak Overnight Periodc Overall On-Peak Avg. Load (kW)a Reduction 0.44 ± 0.49 1.34 ± 0.40 0.54 ± 0.49 0.48 ± 0.31 0.48 ± 0.35 Avg. Load – MURB TOU Participants, Pre Pilot (kW) 24.2 24.4 25.1...

AI summary This table presents load reduction data across various peak and off-peak periods, showing average load reductions and their significance. The data includes metrics such as average load reduction in kilowatts, relative load reduction percentages, and statistical significance levels.

7.1.2 Snapback Effect The snapback effect refers to using more electricity during hours immediately following peak periods. This effect is evaluated based on the same DiD approach that was applied to the load reduction calculation, but spe...

AI summary The snapback effect refers to increased electricity usage following peak periods. Analysis shows that MURB TOU participants had average load reductions during morning and evening snapback periods, with only the morning reduction being statistically significant.

7.2 Economic Impacts This section presents and discusses the impact of MURB TOU Tariff on the electricity bill as well as price elasticity.

AI summary This section discusses the economic impacts of the MURB TOU Tariff, focusing on its influence on electricity bills and price elasticity.

7.2.1 Change in Electricity Bills For the assessment of the economic impacts of the MURB TOU program, the same DiD approach used to estimate load and demand impacts was applied to evaluate changes in electricity bills for MURB TOU particip...

AI summary The document discusses the economic impact of the MURB TOU program on electricity bills, using a DiD approach. Although MURB TOU participants experienced an average daily bill increase of about $4.5, it is not statistically significant. The rate was designed to save participants during non-Winter seasons.

7.2.2 Price Elasticity NS Power evaluated participants' responsiveness to energy price under MURB TOU pricing program, focusing on estimating daily price elasticity and inter-period Substitution Price elasticity. While Daily Price Elastici...

AI summary NS Power evaluated the price elasticity of electricity usage under the MURB TOU pricing program, finding a daily price elasticity of -0.17 and an inter-period substitution elasticity of -0.032. Both values are not statistically significant, indicating limited responsiveness of residential customers to price changes.

Findings Summary The TVP pilot tariffs have demonstrated success in reducing load during peak periods while providing participating customers with bill savings. Both residential tariff options evaluated continue to demonstrate a strong cap...

AI summary The TVP pilot tariffs have successfully reduced peak load and provided bill savings. Residential options continue to benefit the grid and customers, while commercial rates show positive load shift in general rate participants. The evaluation supports the ongoing progress of TVP tariffs in shifting electricity use to off-peak periods.

Residential TOU & CPP - Participants continue to demonstrate statistically significant reduced load during peak periods with minimal snapback. - For the first time, TVP combined with technology (e.g. smart thermostats) and DR (i.e. Eco Shi...

AI summary The document discusses the effectiveness of Time-Varying Pricing (TVP) combined with smart technology and demand response programs in reducing peak load. It also notes that customers on TOU and CPP who electrified their heating showed similar or slightly higher annual energy consumption compared to non-TVP customers.

Commercial TOU & CPP - Participants for the first time have demonstrated statistically significant reduced load during peak periods. This new finding is largely attributable to improvement in methodology and increased sample sizes. - The l...

AI summary The document discusses the effectiveness of Commercial Time-of-Use (TOU) and Controlled Load Program (CPP) tariffs in reducing load during peak periods. Statistically significant reductions were observed, particularly during cold weather events, though results vary by rate class and month.

Multi-Unit Residential Building TOU - Despite the absence of a demand charge, MURB TOU customers did not increase their monthly demand during Winter. - Winter energy and bill savings were negative but not statistically significant, which a...

AI summary The analysis of Multi-Unit Residential Building Time-of-Use (TOU) rates shows that customers did not increase their monthly demand during Winter, despite no demand charge. Winter energy and bill savings were not statistically significant, but overall, participants showed modest load reductions, particularly during evening peak periods, with no evidence of snapback.

Attachment I: Riders and Tariff Structure A summary of the TVP rate designs is included. For additional details, review the publicly available Tariff book.[13](#page-100-5) The volumetric rates used within the billing models are summarized...

AI summary Attachment I provides a summary of TVP rate designs and includes volumetric rates used in billing models, along with visual aids to explain each TVP Tariff structure. Additional details can be found in the publicly available Tariff book.

Riders Although riders can change throughout a pilot Phase, to control for economic impacts associated with tariff change, a consistent tariff is used for all economic analyses. Riders are applied to all volumetric energy charges on a per...

AI summary The document discusses the use of riders in tariff structures, emphasizing the application of consistent tariffs during pilot phases to manage economic impacts. It provides a summary of rider rates for different residential and commercial rate classes, including FAM, DSM, and SCR.

Table 59: Tariff Summary (January 2025) Domestic SOR Customer Charge $19.17 per month Energy Charge $0.16931 per kWh Domestic TOU Customer Charge $19.17 per month Energy Charge (Winter on-peak) $0.33862 per kWh Energy Charge (Winter off-pe...

AI summary Table 59 outlines various tariff structures for different customer categories in January 2025, including Domestic SOR, Domestic TOU, Domestic CPP, Small General SOR, Small General TOU, Small General CPP, General SOR, and General TOU. It details customer charges, energy charges for different periods (winter on-peak, winter off-peak, non-winter), and demand charges where applicable.

18 Please refer to Appendix E, Attachment 3, page 23. evaluated sub-group combinations (Table 67) have acceptable group level load similarity and balancing for E1 programming. Sub-Group Possible Sub-Groupings (784 Possible Combinations) TV...

AI summary The document references a table that outlines possible sub-groupings for evaluating load similarity and balancing in E1 programming, including factors like TVP tariff, rate class, cohort, neighbourhood, heating classification, and Eco Shift participation.

III.2.3 Eco Shift A new addition to the TVP evaluation included the effect of combining the Eco Shift administered by E1 with TVP. Control group selection for these customers was incorporated into this evaluations methodology to ensure tha...

AI summary The Eco Shift program, administered by E1, was combined with TVP in an evaluation. Control group selection was used to ensure similarity between treatment and control groups. NS Power requested a list of Eco Shift events from E1, which were mostly CPP events due to alignment between E1 and NS Power.

Treatment and control customer participation in E1 programs (Home Energy Assessment, Green Heat, Appliance Retirement, Efficient Product Installation, Small Business Energy Solutions, Business Energy Rebates, and Custom) are balanced using...

AI summary The text discusses the process of balancing treatment and control customer participation in E1 programs to mitigate confounding effects on TVP results. It outlines the methodology for allocating energy savings based on program year and TVP cohort using a specific equation and references evaluation reports and matter numbers.

III.2.6 CPP Reference Days Although the regression model controls for time synchronous (i.e. zero hour lag-lead) temperature effects in the form of heating degree days (HDD), it is critical to find reference days with similar temperature p...

AI summary The text discusses the methodology for selecting reference days for Critical Peak Pricing (CPP) events, emphasizing the need for similar temperature profiles and weekday types to minimize bias in regression models. Reference days must meet specific criteria, including proximity to the event day and matching weekday types, and are ranked using the Euclidean distance method based on temperature data.

III.3 Regression Models The regression models are divided into three sections, Residential TOU & CPP, Commercial TOU & CPP and MURB TOU. Notably, these regression models utilize hourly AMI data on a per-customer basis. This shift from prev...

AI summary The regression models are divided into three sections: Residential TOU & CPP, Commercial TOU & CPP, and MURB TOU. They use hourly AMI data on a per-customer basis, leading to smaller margins of error due to increased sample sizes in Phase 4.

III.3.1 Residential TOU & CPP This section presents the methodology used to determine the load, usage, and economic impact of the residential TOU and CPP tariffs. The estimates for load and economic impacts are rounded and reported accordi...

AI summary This section outlines the methodology for assessing the load, usage, and economic impact of residential Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs. Estimates are rounded based on the margin of error at the 90% confidence level to ensure accuracy and avoid false precision.

III.3.1.1 Load & Usage Impact Regression Model The regression model used for load and usage impacts is presented in equation ([7)](#page-123-0). $$Load_{it} = \beta_0 + \beta_1. Treatment_i + \beta_2. PilotPeriod_t + \beta_3. (Pilot \times...

AI summary The document presents a regression model for analyzing load and usage impacts under different tariff structures, including Time-of-Use (TOU) and Critical Peak Pricing (CPP). The model includes variables for treatment groups, pilot periods, and heating degree-days (HDD), with adjustments for Eco Shift participants. The analysis will cover a specific time period for TVP customers in Eco Shift and compare them with non-Eco Shift customers.

Attachment III: Methodology second, the addition of a random intercept, changing the model from a fixed effects to mixed-effects model. Given the relatively small participant count of Eco Shift with TVP (TOU = 115 , CPP = 94) and heterogen...

AI summary This section discusses the methodology used in analyzing the impact of the Eco Shift program on Time-Varying Pricing (TVP) participants. It highlights the use of a mixed-effects model to account for heterogeneity among participants and the inclusion of a random intercept to improve the precision and reliability of the estimated program impacts.

age daily bill. The regression models for daily price elasticity and inter-period substitution price elasticity are presented in equations ([10)](#page-125-1) and ([11)](#page-127-0), respectively. $$ln(Daily\ Avg\ Usage\ kWh)_{it} = \\ =...

AI summary The text presents regression models for daily price elasticity and inter-period substitution price elasticity, including equations and variables related to energy usage, temperature, and pricing structures. These models aim to analyze customer behavior and price responsivity in relation to energy consumption.

III.3.2 Commercial TOU & CPP This section presents the methodology used to determine the load, usage, and economic impact of the commercial TOU and CPP tariffs. The estimates for load and economic impacts are rounded and reported according...

AI summary This section outlines the methodology used to evaluate the load and economic impact of commercial Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs using a Mixed-Effects regression analysis and a within-customer modeling framework due to the absence of a control group. The analysis accounts for small sample sizes and heterogeneity among participants.

Attachment III: Methodology following common segmentation practice in demand research (e.g., Borenstein, $2005^{23}$ ; Hledik et al., $2010^{24}$ ); refer to equation (13). $$SLR_{i} = \frac{\overline{\left(L_{i,W}^{adj.}\right)}}{\overlin...

AI summary This section of Attachment III outlines the methodology used to classify commercial participants in the Time-Varying Pricing (TVP) program based on their seasonal load patterns. A seasonal load ratio (SLR) threshold of 0.7 was used to identify seasonal businesses, which showed a significant reduction in electricity usage during the winter. Most businesses were classified as non-seasonal, with only a few exhibiting seasonal behavior.

III.3.2.1 Load and Usage Impact Regression Model Considering the methodological choices discussed above, the commercial TOU and CPP load/usage, billing as well as daily and substitution price elasticity are described by the equations ([14)...

AI summary This section discusses the Load and Usage Impact Regression Model, using equations to describe commercial TOU and CPP load/usage, billing, and price elasticity. The model includes variables such as baseline, treatment, pilot period, HDD, and random intercepts.

III.3.3 MURB TOU The evaluation of MURB TOU is based on panel data estimation approach with matched control groups and pre-pilot data using the difference-in-difference (DiD) approach similar to the residential tariffs. Given the relativel...

AI summary The evaluation of MURB TOU uses a difference-in-difference approach with mixed-effects regression due to a small sample size, ensuring more reliable program impact estimates.

III.3.3.1 Load and Usage Impact Regression Model The same regression as equation (14) was used for load impact and usage impact analyses for MURB TOU.

AI summary The regression model from equation (14) was applied to analyze both load impact and usage impact for MURB TOU in the proceeding.

Attachment IV: Historical Methodological Changes All methodological modifications were made through collaboration with stakeholders and/or consultants. These changes and their progression have been summarized with two purposes. - 1. Inform...

AI summary Attachment IV outlines historical methodological changes made through stakeholder and consultant collaboration. The changes aim to inform readers about biases in comparing evaluation reports and document progress in rate innovation and evaluation methodology from the TVP pilot program.

IV.1.1 CPP (Phase 1) Consistent with the approved evaluation plan, the CPP evaluations used a within-subject control group methodology. In practice this meant that there was no control group for CPP customers, rather the only control was t...

AI summary The evaluation of the Critical Peak Pricing (CPP) program used a within-subject control group methodology initially, but after the first year, Econoler recommended modifying the approach to create a control group for CPP customers to align with Time-of-Use (TOU) evaluations.

IV.1.2 E1 Program Balancing (Phase 1) No balancing for E1 program effects was completed. As a result, the effects associated with E1 programs were not controlled for and could influence TVP EM&V results. Subsequent evaluations (i.e. Phase...

AI summary No balancing for E1 program effects was completed in Phase 1, potentially influencing TVP EM&V results. Subsequent phases have addressed this by balancing control group selection for E1 participation.

IV.1.3 Neighbourhood Criteria & Load Similarity Metric Data (Phase 1, 2, 3) In the previous TVP evaluations (i.e. Phases 1-3) control selection included 2 stages.

AI summary The document discusses the selection process for control groups in previous TVP evaluations, which consisted of two stages and involved neighborhood criteria and load similarity metrics.

IV.2.1 Phase 1 Heating classification in Phase 1 was based on rate code (i.e. 02 = Non-Electric, 03 = Electric). Premises are classified as rate 02 and 03 when first registered with NS Power as a customer. These rate codes are often not re...

AI summary Phase 1 heating classification uses rate codes (02 = Non-Electric, 03 = Electric) based on initial customer registration with NS Power. However, these classifications are not updated when a home's primary heating source changes, leading to inaccuracies as heat pump adoption increases electrification.

IV.2.4 Phase 4 Phase 4 (this Phase) of the evaluation uses a similar methodology as Phase 3, with two key distinctions that improved the accuracy of the model. - 1. Heating classification is used in addition to the neighborhood criteria du...

AI summary Phase 4 of the evaluation improves accuracy by using heating classification alongside neighborhood criteria for control group selection and restricting AMI data to overnight hours for heating classification. This ensures more accurate load impact analysis and captures the effect of TVP price signals on space heating behavior.

IV.3 Regression Model Changes to the regression model are documented within this section with the intent to summarize the change and its justification so that future evaluations can benefit from the iterative development of the TVP evaluat...

AI summary This section discusses changes to the regression model, aiming to summarize the changes and their justifications to support future evaluations and the iterative development of the TVP evaluation.

Commercial TOU and CPP Customers [Figure](#page-138-1) 51 illustrates the baseload heterogeneity of TVP commercial premises, where substantial differences in baseline (Low, Medium and High), associated with time-invariant variables (e.g. s...

AI summary The text discusses the baseload heterogeneity of commercial premises under Time-Varying Pricing (TVP), highlighting differences in baseline levels associated with time-invariant variables like business size. It contrasts Fixed-Effect and Mixed-Effect models in handling this heterogeneity, with the latter accounting for differences through a random intercept.

MURB TOU Customers Unlike the commercial TOU and CPP rates, MURB TOU has not yet been evaluated using the fixed effects regression model. As such additional analyses are provided within in order to validate the choice of a mixed effects re...

AI summary The MURB TOU Tariff has not been evaluated using the fixed effects regression model, so additional analyses are provided to validate the use of a mixed effects regression model with a control group for this tariff.

Residual Diagnostics for Fixed- vs. Mixed-Effect Modeling Approaches It is important to note that a Fixed-Effect model absorbs the time-invariant differences, such as Baseload heterogeneity across MURBs, by eliminating it from the analysis...

AI summary The text discusses the comparison between fixed-effect and mixed-effect modeling approaches in evaluating the impact of time-varying pricing (TOU) programs on load reduction and bill savings. It highlights that mixed-effect models better handle baseline load heterogeneity, producing lower residual autocorrelation and more normally distributed residuals compared to fixed-effect models.

Attachment V: Validation of Mixed Effects Regression Given the small sample size of MURBs (n = 10), the substantial heterogeneity in Baseline electricity consumption across MURBs (Figure 54), and the supporting results from the comparison...

AI summary Due to the small sample size of MURBs, significant variability in baseline electricity consumption, and model comparison results, the Mixed-Effect modeling approach is recommended for estimating the impact of the TOU-MURBs pilot program.

Robust Margin of Error When TVP load impact was estimated using the DiD analysis, the residual errors can be autocorrelated. If residual autocorrelation is not adjusted for, the standard error will be underestimated. As such, it is necessa...

AI summary The text discusses the adjustment of the margin of error (MoE) in estimating TVP load impact using DiD analysis, accounting for residual autocorrelation and heteroskedasticity. Formulas are provided for adjusted and robust MoE calculations, which involve standard error, autocorrelation coefficient, and robust covariance matrix.

Demand Response Overlap between NS Power and E1 In its Decision on E1's 2026 DSM Extension Application (M12249), the Board provided: The Board agrees that concerns about E1's demand response programs are better addressed in its consultatio...

AI summary The Board's decision on E1's 2026 DSM Extension Application highlights concerns about potential overlap between E1's demand response programs and NS Power's Critical Peak Pricing Program. It emphasizes the need for E1 to address these issues in its upcoming DSM Plan application and expects NS Power to cooperate in exploring these matters.

Coincidence of Critical Peak Events and System Margin In its Decision and Order on the Year Three (2023/24) Evaluation Report (Year Three Report) in M11823, the Board provided: NS Power agreed with Synapse that system margin forecasts may...

AI summary The Board directed NS Power to analyze the relationship between system margin forecasts and Critical Peak Pricing (CPP) events in the Year 4 report, and to refine methods for estimating load reductions from Time-Varying Pricing (TVP) tariffs. Analysis showed that during CPP events, system margin was significantly lower compared to non-CPP event hours.

31 M11823 – Board Decision and Order, 316514, page 5. October 31, 2024. Period of Low Forecast System Margin During Scheduled Critical Peak Event Date Hour Start Yes / Cancelled / No 2024-12-04 17:00 2024-12-04 18:00 2024-12-04 19:00 Yes 2...

AI summary The document lists dates and times for periods of low forecast system margin during scheduled critical peak events, indicating when these events were confirmed (Yes) or not (blank). This information is relevant for managing electricity demand during high usage periods.

Reporting on Small Business Characteristics that Enable Load Shifting As part of its 2024 TVP Consensus Agreement, the Company committed to: h. Reporting back to stakeholders on changes that could be made to help customers determine whethe...

AI summary As part of its 2024 TVP Consensus Agreement, the Company committed to reporting back to stakeholders on changes that could help customers determine if they would benefit from TVP, TOU, and CPP options. The report will be provided by NS Power.

Attachment VII: Board Directives and Consensus Agreement Commitments - i. Summary of the general load characteristics of small business customers that may enable a small business customer to shift load in response to TVP, CPP, or TOU rates...

AI summary This section outlines NS Power's commitments related to customer recruitment and education for demand-side management programs, including the collection of business sector data and the evaluation of pilot tariffs. It also references the Board's decision on the Year Three Report and NS Power's agreement to improve customer education efforts.

Other Board Directives and Consensus Agreement Commitments Across the 2024 Consensus Agreement, Year Three Report (M11823), 2024/25 TVP Application (M11822), and other proceedings, other Board directives and commitments have been made. Thr...

AI summary The document discusses Board directives and commitments from the 2024 Consensus Agreement and other proceedings, including the 2024/25 TVP Application. The Company has reviewed these items through NS Power's pricing innovation process and stakeholder consultations, with references to appendices and a Board decision.

July 31, 2026 Crystal Henwood Clerk of the Board Nova Scotia Energy Board 1601 Lower Water Street, 3rd Floor Halifax, NS B3J 3S3 Re: M12932 Time-Varying Pricing Pilot Program – Year Five (2025/26) Evaluation Report Dear Ms. Henwood: Nova S...

AI summary Nova Scotia Power Inc. submits the Time-Varying Pricing Pilot Program Year Five (2025/26) Evaluation Report as part of proceeding M12932. The report covers results from April 1, 2025, to March 31, 2026, and is submitted as a separate exhibit per the Nova Scotia Energy Board's direction.

Background The TVP Pilot Program was developed by NS Power with the assistance of Brattle Group and stakeholder input in M09777. The Pilot, testing Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs across the Domestic, Small Genera...

AI summary The TVP Pilot Program, including TOU and CPP tariffs, was approved by the Board in M09777 and M11822. The MURB TOU Tariff remained active during the 2025/26 season despite the suspension of other tariffs due to a cybersecurity incident affecting AMI data. The evaluation focuses on the MURB TOU Tariff.

Summary of Year Five Evaluation Results The Year Five Report represents the second evaluation of the MURB TOU Tariff since its implementation in November 2024. In the 2025/26 Season, all ten enrolled MURB customers continued participation...

AI summary The Year Five Evaluation of the MURB TOU Tariff indicates modest load increases during peak periods, with no significant bill savings observed during the evaluated Winter period. The evaluation was limited by data availability due to a cybersecurity incident, and findings are based on a small participant population. The results are consistent with the tariff's design to encourage bill savings outside of Winter peak conditions.

Conclusion The Year Five Report ( Appendix A ) provides the second evaluation of the MURB TOU Tariff and continues the Company's assessment of customer response to this time-varying rate. While the evaluation scope was narrower than prior...

AI summary The Year Five Report evaluates the MURB TOU Tariff and customer response to time-varying rates. Despite a narrower scope due to AMI data limitations, the report uses the EM&V framework to assess impacts. NS Power plans to resume the TVP Pilot in 2026/27 under the Board-approved tariff (M12451) and will notify stakeholders 30 days before resuming.

Time-Varying Pricing Pilot Program Phase 5 Evaluation, Measurement & Verification Report July 31, 2026

AI summary This document is an Evaluation, Measurement & Verification Report for Phase 5 of the Time-Varying Pricing Pilot Program, dated July 31, 2026. It provides an analysis of the program's performance and outcomes.

Definitions Adjusted Net Load The hourly net system requirement (MW) less all wind generation (MW) Cohorts Cohorts are numbered based on the Phase they enrolled in the TVP program. For example, Cohort 4 refers to participants recruited in...

AI summary The document defines key terms used in the regulatory proceeding, including Adjusted Net Load, Cohorts, Commercial, Consumption, Control, Demand, Load, Peak, and Phase. These definitions are essential for understanding the evaluation methodology and results of the Time-Varying Pricing (TVP) program.

Tariffs The MURB TOU Tariff has two four-hour peak periods (7 – 11 AM, 5 – 9 PM) with a mid-peak (11 AM – 5 PM) occurring seven days per week during the Winter period (i.e. November 1 to March 31, inclusive). During the non-Winter period (...

AI summary The MURB TOU Tariff defines peak, mid-peak, and off-peak periods during Winter and non-Winter months, with varying rates relative to the SOR first energy block. It applies the same rate structure on holidays and weekends, and does not include a demand charge, unlike the General SOR.

MURB TOU Findings Maintaining participation of the 10 MURBs under the MURB TOU Tariff, Phase 5 marks the second load and economic impact evaluation of this Tariff. Phase 5 results are inclusive of the Winter period from November 2025 to Ma...

AI summary The Phase 5 evaluation of the MURB TOU Tariff shows increased load during morning and evening peak periods, with overall peak load increasing by approximately 1.09 kW. The evaluation covered the winter period from November 2025 to March 2026 due to meter data availability issues during the non-winter portion of the 2025/26 Season.

TVP Tariff Absolute Load Reduction (kW) Relative Load Reduction (%) Morning Peak Evening Peak Morning Peak Evening Peak MURB TOU -1.29 kW -0.78 kW -5.3% -3.1% Statistical Significance ✓ ✓ ✓ ✓ Table 1: Summary of Load Reductions by MURB TOU...

AI summary Table 1 presents load reduction data for the MURB TOU rate class under the TVP tariff, showing absolute and relative load reductions during morning and evening peaks, along with statistical significance indicators.

Note: Throughout this report, statistically significant results will be displayed in tables with black font, whereas statistically insignificant results will be displayed in grey font. MURB TOU participants demonstrated statistically signi...

AI summary The analysis of MURB TOU participants shows statistically significant increases in electricity use during snapback periods and during high Adjusted Net Load hours. However, the overall increase in energy use during Winter did not lead to a statistically significant increase in bills. The study also notes limitations due to incomplete data coverage and small sample size, affecting the conclusiveness of findings.

s not reasonable for all months and Winter overall; for months where the data quality is consistent between the two phases (i.e. February and March), a comparison is provided in [Table 2](#page-12-0). Table 2: Comparison of Phase 4 and Pha...

AI summary The text discusses the comparison of Phase 4 and Phase 5 MURB TOU results during February and March, noting data quality consistency between the two phases and referencing Table 2 for the comparison.

February March Parameter a Phase 4 Phase 5 Phase 4 Phase 5 (Change)b (Change)b Avg. Load Reduction during Morning Peak +1.36 -1.36 -1.87 +0.06 Period (kW) (-2.72, ✓) (+1.93, ✓) Avg. Load Reduction during Mid Peak Period +2.80 -0.66 -0.67 +...

AI summary The table compares load and cost reductions between Phase 4 and Phase 5 for various peak periods and overall usage. The data shows mixed results, with some metrics showing statistically significant improvements and others not. Positive values indicate reductions/savings, while negative values represent increases in load or cost.

Introduction Time-Varying Pricing (TVP) is a scalable customer-focused demand response (DR) program. In Nova Scotia, the TVP pilot enrolment has grown significantly since it began in November 2021. Since its inception, the TVP pilot has of...

AI summary Time-Varying Pricing (TVP) is a demand response program in Nova Scotia that offers Time-of-Use (TOU) and Critical Peak Pricing (CPP) tariffs. Due to a cyber incident, these tariffs were temporarily paused during the 2025/26 Winter, except for the MURB TOU Tariff, which continued with AMR meters. The evaluation of the program is limited to the MURB TOU Winter-period performance, primarily February and March 2026.

Table 3: Impact Evaluation Metric Summary Category Metric MURB TOU Change in load during peak periods (kW) • Change in load (kW) during peak, mid-peak, and overall impact during Winter and non-Winter. • Change in load by month. Snapback (k...

AI summary Table 3 summarizes impact evaluation metrics for MURB TOU, including load changes during peak periods, snapback effects, load and usage impacts, and economic changes such as electricity bill variations and price elasticity.

The TVP pilot program has increased enrolment year over year with a total of 8,376 participants at the end of Phase 4. Due to the temporary pause of six of seven TVP tariffs, excluding the MURB TOU, Phase 5 contains only 10 participating T...

AI summary The TVP pilot program has seen increased participation over the years, reaching 8,376 participants by the end of Phase 4. However, Phase 5 has only 10 participants due to the temporary pause of most TVP tariffs, with all 10 remaining participants being from the MURB TOU category.

Table 4: TVP Participation on March 31 2026 by Phase and Rate Class Phase DOM TOU SMG TOU GEN TOU DOM CPP SMG CPP GEN CPP MURB TOU Total Phase 1 676 24 284 8 0 992 Phase 2 891 17 373 2 0 1,283 Phase 3 2,241 37 19 922 3 6 0 3,228 Phase 4 5,...

AI summary Table 4 presents TVP participation by phase and rate class as of March 31, 2026, showing the number of customers enrolled in Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs across different phases and rate classes, with Phase 5 having no participating customers except for MURB TOU.

1 Methodology The methodology is primarily composed of two components: control group selection and regression modelling of load and economic impacts. This methodology in detail was filed as Attachments III to V to the Phase 4 TVP EM&V Repo...

AI summary The methodology for evaluating Time-Varying Pricing (TVP) involves control group selection and regression modeling. Control groups are matched based on location and load profiles, and a mixed-effects regression model using difference-in-differences (DiD) is applied. Data quality for Phase 5 is noted to be lower than in Phase 4, which may affect results.

2 MURB TOU Tariff Impacts The goal of the MURB TOU pilot is to inform if removing the demand charge for select customer segments on the General Rate will enable additional load shifting potential compared to the commercial TOU pilot. This...

AI summary The MURB TOU pilot aims to assess load shifting potential by removing demand charges for select customer segments on the General Rate. However, data availability is limited, with only 60% of Winter period control data available, and November data entirely missing. This affects the accuracy of monthly and Winter overall results, which exclude November and rely heavily on February and March data.

2.1 Load Impacts This section presents and discusses the electrical load impact from the commercial MURB TOU pilot.

AI summary This section discusses the electrical load impact from the commercial MURB TOU pilot, providing insights into how time-of-use pricing affects load patterns in multi-unit residential buildings.

2.1.1 Change in Load during Peak Periods [Figure 2](#page-18-0) illustrates the load profiles for MURB TOU participants and the control group during the prepilot and pilot periods, along with the corresponding variation in outdoor temperat...

AI summary The analysis of load profiles for MURB TOU participants and the control group during the prepilot and pilot periods reveals statistically significant load increases, except during certain hours. The DiD analysis shows average relative load increases of 5.3% and 3.1% during morning and evening peak periods, respectively, with the largest increase observed during offpeak overnight hours.

Parameters Morning Peak Mid-Peak Periodb Evening Peak Overnight Periodc Overall On-Peak Avg. Load (kW)a Reduction -1.29 ± 0.40 -0.37 ± 0.32 -0.78 ± 0.42 -1.39 ± 0.27 -1.09± 0.30 Avg. Load – MURB TOU Participants, Pre Pilot (kW) 24.0 23.9 2...

AI summary The table presents load reduction data for MURB TOU participants during various peak and off-peak periods, showing average load reductions and their statistical significance. The results indicate a consistent reduction in load across all periods, with the highest reduction observed during the overnight period.

Change in Load by Month during Peak Periods [Figure 3](#page-20-3) illustrates the impact of MURB TOU on average load reduction (kW), along with corresponding average outdoor temperature (°C) during peak periods as well as mid-peak and off...

AI summary The text discusses the impact of MURB TOU on average load reduction during peak periods in the winter of 2025-2026. It notes that load increased in December, January, and February but decreased slightly in March, with the most significant increase occurring in January due to colder temperatures.

2.1.2 Snapback Effect The snapback effect refers to using more electricity during hours immediately following peak periods. This effect is evaluated based on the same DiD approach that was applied for load reduction calculation, but specif...

AI summary The snapback effect refers to increased electricity usage following peak periods. Using a DiD approach, MURB TOU participants showed significant load increases of 0.41 kW and 1.6 kW during morning and evening snapback periods, respectively.

Table 6: Snapback Effect for MURB TOU Participants in Winter Parameters Avg. Load Reduction (kW)a Relative Avg. Load Reduction (%)a Significance (p_Value≤0.05) Morning Snapbackb -0.41 ± 0.39 -1.7% ✓ Evening Snapbackc -1.60 ± 0.46 -7.1% ✓ O...

AI summary Table 6 presents the snapback effect for MURB TOU participants in winter, showing average load reductions during morning and evening periods, with statistical significance indicated. The data highlights the impact of time-varying pricing on load behavior in multi-unit residential buildings.

2.1.3 Change in Load during Highest ANL Hours [Figure 4](#page-21-0) depicts the distribution of Top 20, 50, and 88 highest ANL hours for MURB TOU participants during morning peak, evening peak, mid-peak, and off-peak hours. As seen in [Fi...

AI summary The document discusses the distribution of highest ANL hours for MURB TOU participants, showing that load increases occur during these hours, particularly during morning and evening peak periods. The load increases during top 20, 50, and 88 ANL hours were 6 kW, 1.7 kW, and 2.4 kW, respectively, with statistically insignificant differences between peak and non-peak periods.

Table 8: Change in Daily Electricity Usage (kWh/day) for MURB TOU Participants Parameters Winter Winter Mo nths Parameters Overall January February March November December Avg. Usage Reduction (kWh/day) a -21.2 ± 17.5 -104.7 ± -28.4 ± 18.9...

AI summary Table 8 shows the change in daily electricity usage (kWh/day) for MURB TOU participants during winter months. The data indicates mixed results, with some months showing a reduction in usage and others showing an increase. The significance of the results is also noted, with some months showing statistically significant changes.

Table 9: Change in Monthly Demand by MURB TOU Participants during Winter (Feb, Mar) Winter Winter Months Parameters Overall January February March November December Avg. Monthly -1.2 ± 5.3 -3.9 ± 5.8 -3.4 ± Demand Reduction 12.2 (kW)a Avg....

AI summary Table 9 presents the change in monthly demand by MURB TOU participants during winter months (February, March) compared to baseline periods. It includes average monthly demand reduction, percentages, and statistical significance of the changes observed.

[Figure 6](#page-25-0) illustrates the estimated percent relative demand reduction overall and across specific TOU periods, including pre-morning peak, morning peak, morning snapback, pre-evening peak, evening peak, and evening snapback. D...

AI summary The text discusses the impact of Time-Varying Pricing (TOU) on demand in Multi-unit Residential Buildings (MURB) during the Winter evaluation period. It highlights an overall increase in relative demand by 5.8%, with the highest increase of 9.0% observed during the evening snapback period. The estimated overall daily demand increase of 1.6 kW is statistically significant, with variations observed across different TOU periods.

Table 10: Changes in Demand by MURB TOU Participants during Winter (Feb, Mar) Parameters Pre Morning Peak b Morning Peak c Morning Snapback d Pre Evening Peak e Evening Peak f Evening Snapback g Overall Daily Avg. Demand Reduction (kW)a -1...

AI summary Table 10 presents data on changes in demand by Multi-unit Residential Building (MURB) Time-of-Use (TOU) participants during winter months (February and March). The table shows average demand reduction during morning and evening peak periods, along with statistical significance, indicating the effectiveness of the TOU program in reducing energy consumption.

2.2 Economic Impacts This section presents and discusses the impact of MURB TOU Tariff on the electricity bill as well as price elasticity. Notably, due to data quality during November, December, and January, these months are not included...

AI summary This section discusses the economic impacts of the MURB TOU Tariff on electricity bills and price elasticity, noting that data from November to January was excluded due to quality issues affecting the regression analysis.

2.2.1 Change in Electricity Bills For the assessment of the economic impacts of the MURB TOU program, the same DiD approach used to estimate load and demand impacts was applied to evaluate changes in electricity bills for MURB TOU particip...

AI summary The economic impact of the MURB TOU program on electricity bills was assessed using a DiD approach, applying 2026 tariffs based on customer type and pilot period as outlined in Table 11.

2.2.2 Price Elasticity NS Power evaluated participants' responsiveness to energy price under the MURB TOU Tariff, focusing on estimating daily price elasticity and inter-period substitution price elasticity. While daily price elasticity re...

AI summary NS Power evaluated the price elasticity of MURB TOU Tariff participants, finding a daily price elasticity of -0.19 and an inter-period substitution elasticity of 0.64, though neither was statistically significant, indicating limited responsiveness of customers to price changes during Phase 5.

Findings Summary Although six of the seven TVP pilot tariffs were not evaluated in this report due to a temporary pause in those tariffs for the 2025/26 Season, the MURB TOU Tariff was evaluated for the second time. Due to data limitations...

AI summary The evaluation of the MURB TOU Tariff during Phase 5 showed modest load increases during peak and snapback periods, but no significant load shifting in response to price signals. Bill increases were statistically insignificant, and demand trends were inconsistent. The findings are limited by a small sample size and data constraints, leading to inconclusive results.

Attachment I: Riders and Tariff Structure A summary of the TVP rate designs is included. Additional details, such as tariff terms and conditions, are available in NS Power's Tariff Book. [2](#page-31-5) The volumetric rates used within the...

AI summary Attachment I provides a summary of TVP rate designs and references additional details in NS Power's Tariff Book. It includes volumetric rates and visual aids to explain the TVP tariff structures.

Table 13: Rider Summary Rider Rate Used in Analysis Fuel Adjustment Mechanism ($/kWh) 0.00207 Demand Side Management Cost Recovery ($/kWh) 0.00582 Storm Cost Recovery ($/kWh) 0.00091 Tariffs Although tariffs can change throughout a pilot P...

AI summary Table 13 summarizes three key riders used in the analysis, including the Fuel Adjustment Mechanism, Demand Side Management Cost Recovery, and Storm Cost Recovery, with associated rates per kWh. The document also notes that consistent tariffs are used in economic analyses to control for economic impacts.

Table 15: Top 88 ANL Hours 2025/26 Rank Date Start Time Load - Wind (Adjusted Net Load) (MW) % of Maximum Load Halifax Temp. (°C) MURB TOU AM Peak / PM Peak / Off Peak 28 29-Jan-26 9:00 AM 2016.0 85.2% -13.3 AM 29 3-Mar-26 7:00 AM 2013.8 8...

AI summary Table 15 lists the top 88 adjusted net load (ANL) hours for 2025/26, detailing dates, times, load levels, temperature, and peak periods. It highlights high load events and their corresponding time-of-use (TOU) classifications.

Agenda - 1. Welcome & Introduction/Background - 2. TVP Pilot Status - 3. Customer Communications - 4. Current TVP Systems Status - 5. Items Raised in Prior Technical Sessions - 6. TVP Objectives for Winter 6 (2026-2027) - 7. Near Term Next...

AI summary The agenda outlines the topics to be discussed in a proceeding, including the status of the TVP pilot, customer communications, current TVP systems status, items raised in prior technical sessions, TVP objectives for Winter 6 (2026-2027), and near-term next steps.

TVP Pilot Benefits Provides customers directional price signals on electricity costs. Gives customers choice in how and when they consume energy. Customers are empowered to decrease their bills by shifting their use of electricity when it...

AI summary The TVP Pilot Benefits section outlines how Time-Varying Pricing (TVP) provides customers with price signals to manage their electricity use, offering them the ability to shift consumption to off-peak times. This results in lower bills, reduced need for infrastructure investment, and system savings through decreased fuel, power purchase costs, and carbon emissions.

Time-of-Use & Critical Peak Pricing - Pilot rates are paused during system restoration - Customers remain enrolled in the TVP pilot program - Time-of-Use and Critical Peak rates are set at the standard offer rate for their rate class - Cus...

AI summary The Time-of-Use and Critical Peak Pricing pilot program has been paused during system restoration, but customers remain enrolled. Rates are set at the standard offer rate for their rate class, and customers have been notified of the changes.

DOM TOU SMG TOU GEN TOU DOM CPP SMG CPP GEN CPP MURB TOU Total Phase 1 676 24 284 8 0 992 Phase 2 891 17 373 2 0 1,283 Phase 3 2,241 37 19 922 3 6 0 3,228 Phase 4 5,616 37 18 2,642 17 36 10 8,376 Phase 5 5,020 34 16 2,376 16 36 10 7,508

AI summary The table presents data on the number of participants in different rate classes (DOM, SMG, GEN, MURB) across various phases for TOU and CPP programs. The data shows an increasing trend in participation from Phase 1 to Phase 5, with the highest number of participants in Phase 4 and Phase 5.

Customer Communications - An adaptive communication strategy was implemented in response to the cyber incident which outlined a series of planned customer communications and website updates. - Updated messaging was delivered internally to...

AI summary In response to a cyber incident, an adaptive communication strategy was implemented, including planned customer communications and website updates. Internal messaging was updated to ensure NS Power staff and Customer Care teams could effectively address customer inquiries about the program.

2025 Communications - Following the Board's direction in M12499, on the approach for the 2025/26 Season, NS Power completed the following: - Emailed all TOU customers on October 31, 2025 - Emailed all CPP customers on November 13, 2025 - L...

AI summary NS Power followed the Board's direction in M12499 to communicate with customers regarding the pause of the 2025/26 Season program. Emails were sent to TOU and CPP customers, and letters were mailed to those without valid email addresses. The website was updated to inform customers that the program is paused and that applications are closed.

TVP Year Five Report Appendix B Page 9 of 79 Copy of Residential TOU Letter - Page 1 Copy of Residential CPP Letter - Page 1 Copy of Residential CPP Letter – Page 2 (TOU had a similar FAQ structure for its back page) PO Box 910 Halifax, No...

AI summary The document contains copies of letters related to Time-Varying Pricing (TVP) programs, specifically Time-of-Use (TOU) and Critical Peak Pricing (CPP), from the TVP Year Five Report Appendix B. It includes a page reference and a mailing address, with no further content provided in the text.

Important Update on the Time-of-Use Rate Pilot As a current participant in the Time-of-Use Rate Pilot, you are receiving this letter, as we do not have an email on file or we were unable to successfully email you last week, to inform you t...

AI summary The Time-of-Use Rate Pilot has been temporarily paused, and participants will now be billed under the Standard Residential Service Rate until further notice, effective November 1.

It's important to note that: - The Standard Residential Service Rate currently matches the Time-of-Use off-peak rate. Visit paraway, ca/standard-rate to view rate details. - Since you won't have peak hours, you'll pay a lower overall rate...

AI summary The Standard Residential Service Rate aligns with the Time-of-Use off-peak rate, offering lower winter rates and continued perks for enrolled participants. Resources for managing electricity use are available at nspower.ca/save.

Stay Informed. When the Time-of-Use Rate Pilot is restored, we will notify you in advance so you can be prepared for the return of on-peak and off-peak rates. Thank you for your continued participation and interest in the rate pilot. To en...

AI summary The Time-of-Use Rate Pilot is set to be restored, with participants being notified in advance. Customers are encouraged to update their contact information to stay informed about the pilot's changes, including the return of on-peak and off-peak rates.

Important Update on the Critical Peak Pricing Rate Pilot As a current participant in the Critical Peak Pricing Rate Pilot , you are receiving this letter because we could not reach you by email last week to inform you that the rate pilot h...

AI summary The Critical Peak Pricing Rate Pilot has been temporarily paused, and participants will now be on the Standard Residential Service Rate. They remain enrolled in the pilot and will still qualify for perks once the program resumes. Resources for managing electricity use are available on the NSPower website.

What does this mean While you remain enrolled in the Critical Peak Pricing Rate Flot, your power rate will temporarily reflect the Standard Reclinical Sorvice Rate, which will be oppid as a single, flat energy rate, 247 – with no Critical...

AI summary Enrolled customers in the Critical Peak Pricing Rate Flot will temporarily see a flat energy rate (Standard Reclinical Sorvice Rate) without Critical Peak Events. This change is temporary and will revert once full functionality is restored, with advance notice provided to affected customers.

2026 Communications - An update was sent to both Residential and Business customers via email on March 19, 2026. - The purpose of this email was to maintain a line of communication and share the anticipated timeline for when the program wi...

AI summary An update was sent to residential and business customers on March 19, 2026, to maintain communication and share the anticipated timeline for resuming a program. NS Power staff were prepared to discuss the rate pilot at 2026 Home Shows and Billing Events, and prospective participants were encouraged to join a mailing list for updates.

Future communications - NS Power is planning to share another update for existing customers late this summer to maintain the communication channel and inform them about what is going on and when the rate pilot is returning. - Current parti...

AI summary NS Power plans to provide an update to existing customers later this summer regarding the Time-Varying Pricing Rate Pilot, ensuring continued communication and informing customers about the pilot's return. Current participants will be notified first, followed by general public communications through channels such as the website.

Systems & Processes • All systems required for the administration of TVP Tariffs are expected to be restored by the end of Q3 2026.

AI summary The document indicates that all systems necessary for the administration of Time-Varying Pricing (TVP) Tariffs are expected to be fully restored by the end of the third quarter of 2026.

Data & Reporting - Planning for Data Lake Reporting is still ongoing with and estimated completion date of October 30, 2026: - Potential changes in analytics tools - This may impact Phase 6 EM&V - The Phase 4 (2024/25) Evaluation Report wi...

AI summary Planning for Data Lake Reporting is ongoing with an estimated completion date of October 30, 2026. Potential changes in analytics tools may impact Phase 6 EM&V. The Phase 4 (2024/25) Evaluation Report will be filed by June 30, 2026, and the Phase 5 (2025/26) Evaluation report by July 31, 2026, which evaluates the MURB TOU Tariff for winter phase 5.

MyEnergy Insights - The Customer Energy Management system (M10164, CI C0021839) also referred to as MyEnergy Insights – included the implementation of TVP tariffs. - MyEnergy Insights allowed customers to gain insights and manage their ene...

AI summary MyEnergy Insights is a customer energy management system that provides users with insights into their energy usage, enabling informed decisions about energy use and rates. The system, which includes TVP tariffs, is expected to be restored by the end of Q3 2026.

Customer Information System (CIS) replacement project - Capital Work Order is expected to be filed in 2026 with the launch of new system anticipated in 2029. - Pending future CIS replacement work, NS Power expects to: - Minimize developmen...

AI summary The Customer Information System (CIS) replacement project is expected to be filed with a Capital Work Order in 2026, with the new system anticipated to launch in 2029. In the interim, NS Power plans to minimize development on existing CIS systems and continue TVP rate design work.

Items provided in the Year Four (2024/25) Evaluation Report (and previously discussed in 2024/25 Technical Session 2) Summary of 2024/25 Areas of Focus & Board Directives – Updated for 2026/27 Type Items to be Discussed/Reviewed 4.0 – Repo...

AI summary The document outlines the focus areas for the 2024/25 Evaluation Report, including reporting on small business customer items and changes to Time-Varying Pricing (TVP). It discusses analyzing load characteristics, customer recruitment, and reasons for customer reluctance to participate in TVP.

Items to be Discussed at Future Technical Sessions and/or provided in the Year Four (2024/25) Evaluation Report Summary of 2024/25 Areas of Focus & Board Directives – Updated for 2026/27 Type Items to be Discussed/Reviewed 5.0 – Potential...

AI summary The document outlines areas of focus for 2024/25, including potential tariff changes to improve customer participation in the TVP program, discussions on new tariffs enabling behind-the-meter energy storage, and examination of alternative domestic tariffs with TOU structures. It also mentions the development of a weekend-inclusive TOU tariff and evaluation of energy storage use cases.

TVP Objectives for Winter 6 (2026-2027) - Restore all Pilot TVP rates to operational status for November 1, 2026. - Focus on the customer experience of existing TVP customers to retain their trust in the stability of the rates. - Continue...

AI summary The document outlines objectives for the Time-Varying Pricing (TVP) program for Winter 6 (2026-2027), including restoring pilot TVP rates to operational status, improving customer experience, continuing communication efforts, applying learnings from prior evaluation reports, and advancing the Areas of Focus Work Plan from stakeholder engagements.

TIME-VARYING PRICING TARIFF PROGRAM NS POWER RESPONSES TO STAKEHOLDER COMMENTS TVP Session 2026/27 Kick-off Session – held 16 June 2026 Comments Received 26 June 2026

AI summary Nova Scotia Power Inc. (NSPOWER) is responding to stakeholder comments on the Time-Varying Pricing (TVP) Tariff Program, following a kick-off session held on 16 June 2026 and comments received on 26 June 2026.

Responses Filed 31 July 2026 Stakeholder Comment NS Power Response 1. The SBA understands that Phase 6 (Winter 2026-27) is focused on retention rather than recruitment, and enrollment has declined since the cyber incident. Clarity on the r...

AI summary The SBA has raised concerns about low participation in Phase 6 of the TVP pilot due to a cyber incident and declining enrollment. NS Power plans to recruit customers before the 2027/28 TVP Season and will use trusted advisors for outreach, though limited resources may affect SMB recruitment efforts.

TIME-VARYING PRICING TARIFF PROGRAM NS POWER RESPONSES TO STAKEHOLDER COMMENTS Stakeholder Comment NS Power Response business customers (e.g., farms and agricultural operations) being identified and engaged, given low program awareness and...

AI summary NS Power is addressing stakeholder concerns about the Time-Varying Pricing (TVP) Tariff Program, emphasizing that there are no upfront fees for participation and that the program is behavioral in nature. NS Power also notes that no recruitment events are planned for the 2026/27 season but will reassess goals for the 2027/28 season. Customer education activities are planned to maintain communication with participants.

Cohort - Cohorts are numbered based on the Phase they enrolled in the TVP program. For example, Cohort 4 refers to participants recruited in Phase 4 (i.e. the fourth Winter), which started November 2024. - Notably, the pre-pilot period for...

AI summary The document explains that cohorts in the TVP program are numbered based on the phase they enrolled in, with Cohort 4 representing participants from Phase 4, starting in November 2024. The pre-pilot period for each cohort is static, and the text introduces the EM&V scope for the program.

- 2. Multi unit residential building (MURB TOU) Tariff EM&V. MURB TOU scope includes existing commercial TOU scope and additional scope specific to MURB TOU. Table 4: Impact Evaluation Metric Summary Category Metric TOU, CPP, MURB TOU (all...

AI summary The document discusses the evaluation metrics for the Multi Unit Residential Building (MURB) Time-Varying Pricing (TVP) Tariff, including load changes during peak and non-peak periods, regional differences, income classification impacts, and economic effects such as changes in electricity bills and price elasticity.

TVP Regression Models • Full difference-in-difference (DiD) approach for Residential TOU and CPP & MURB TOU (Consistent with methodology in Phases 2 & 3) Control Pre-Pilot Control Pilot Period Treatment Pre-Pilot Treatment Pilot Period • S...

AI summary The document discusses the use of Time-Varying Pricing (TVP) regression models, specifically employing a full difference-in-difference (DiD) approach for residential Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs, and a semi-DiD approach for commercial TOU and CPP due to the absence of a control group. A figure is referenced for further details.

Fixed and Mixed Effects Regression Modelling $$Load_{it} = \beta_0 + \beta_1. Treatment_i + \beta_2. PilotPeriod_t + \beta_3. (Pilot \times Treatment)_{it} + \beta_4. HDD_{it} + \beta_5. (Pilot \times Treatment)_{it}. HDD_{it} + \varepsilo...

AI summary The text discusses the use of Fixed and Mixed Effects Regression Modelling to analyze load data, considering factors like treatment, pilot periods, heating degree days (HDD), and Eco Shift participation. Mixed Effect modelling was chosen due to small sample sizes and heterogeneity among commercial TVP, MURB TOU customers, and Eco Shift participants.

Robust Margin of Error $$MoE(90\%)_{robust} = z. \frac{SE_{robust}}{\sqrt{1 - \rho^2}}$$ (23) $$SE_{robust} = \sqrt{c^T \cdot V_{robust} \cdot c}$$ (24) In Phases 1–3, standard errors and MoE assume homoscedastic residuals. Because our ana...

AI summary The document discusses the calculation of a robust margin of error (MoE) using a formula that accounts for heteroscedasticity and serial correlation in customer load data, which was identified in Phase 4 of the analysis.

Conclusion of the Review Econoler provided guidance and clarifications to NS Power to ensure a consistent and appropriate application of the overall evaluation methodology established for TVP Phase 1 to 3. Additionally, based on the discus...

AI summary Econoler provided guidance and clarifications to NS Power to ensure consistent application of the evaluation methodology for TVP Phases 1 to 3. Econoler also validated the methodological changes in the draft report for TVP Phase 4, finding the justifications provided by NS Power to be sound.

Context This memo summarizes the support provided by Econoler to Nova Scotia Power (NS Power) in the finalization of Time-Varying Pricing (TVP) Pilot Program Phase 4 Evaluation. Econoler was contracted by NS Power to provide advisory suppo...

AI summary Econoler provided advisory support to Nova Scotia Power (NS Power) in finalizing the evaluation of Time-Varying Pricing (TVP) Pilot Program Phase 4. Econoler reviewed methodological changes, including the use of mixed-effect models and robust margins of error, and submitted clarifying questions, which were addressed by NS Power.

Participation & Retention - Total enrolment has increased by 5,095 participants from Phase 3 to Phase 4 across both residential TVP rates. - Commercial enrolment in CPP and MURB TOU only.

AI summary Total enrolment in residential TVP rates has increased by 5,095 participants from Phase 3 to Phase 4, while commercial enrolment is limited to CPP and MURB TOU programs.

- The average customer retention rate per TVP Tariff ranges from 87% (Domestic TOU) to 100% (MURB TOU). Phase DOM TOU SMG TOU GEN TOU DOM CPP SMG CPP GEN CPP MURB TOU Total Phase 1 676 2 4 284 3 0 992 Phase 2 891 1 17 2 0 1,283 Phase 3 2,2...

AI summary The document presents data on customer retention rates for various Time-Varying Pricing (TVP) Tariffs across different phases. The retention rates range from 87% for Domestic TOU to 100% for MURB TOU, with detailed enrollment and withdrawal statistics provided for each phase and tariff type.

TVP Year Five Report Appendix B Page 36 of 79 RESIDENTIAL TOU FINDINGS

AI summary The document presents findings related to residential Time-Varying Pricing (TOU) in the fifth year of the TVP program. It focuses on the impact of TOU on residential customers, including energy usage patterns and program effectiveness.

Load Impact by Cohort - All TOU cohorts exhibit statistically significant load reduction during morning and evening peak hours. - TOU participants achieved slightly higher load reduction during the evening peak hours.

AI summary The analysis shows that all Time-of-Use (TOU) cohorts experienced statistically significant load reduction during morning and evening peak hours, with participants achieving slightly higher reductions during the evening.

- Overall, TOU participants demonstrated load reductions of 0.15 kW and 0.17 kW, corresponding to relative load reductions of 7.4% and 7.9% during morning and evening periods, respectively. Mornin g Peak P eriods Evening g Peak Pe eriods P...

AI summary The analysis shows that TOU participants achieved load reductions of 0.15 kW and 0.17 kW during morning and evening peak periods, representing 7.4% and 7.9% reductions respectively. The data is presented across multiple cohorts, with varying levels of significance.

- Participants who electrified their heating system, by transitioning from non-electric to electric space heating, exhibit load reductions of 0.07 kW and 0.14 kW during morning and evening peak hours. Mor ning Eve ning Parameters De-Electr...

AI summary Participants who transitioned from non-electric to electric space heating show load reductions of 0.07 kW and 0.14 kW during morning and evening peak hours. The table shows average load reductions and relative percentages across different electrification scenarios.

- All cohorts reduced their daily usage during Non -Winter, regardless that peak periods are not applicable. Overall, a reduction of 0.54 kWh per day was observed. Parameters Cohort 1 Cohort 2 Cohort 3 Cohort 4 All Winter, Non-Holiday Week...

AI summary All cohorts reduced their daily energy usage during the Non-Winter period, with an overall reduction of 0.54 kWh per day. Usage reductions were observed across different cohorts and time periods, including weekdays and weekends/holidays.

Table 16: Change in Daily Electricity Usage Level by Space Heating Type for All Cohorts of Residential TOU Participants Parameters De-Electrified Electrified Steady Electric Steady Non-Electric Winter, Non-Holiday Weekdays Avg. Usage Reduc...

AI summary Table 16 presents the change in daily electricity usage levels for residential TOU participants, categorized by space heating type. The data shows varying degrees of usage reduction or increase across different cohorts, with statistical significance noted for some categories. The findings highlight the impact of TVP on electricity usage, particularly during winter and non-winter periods.

Bill Impact by Space Heating Classification - Space heating has significant influence on the Winter bill impact for the TOU participants. With those relying on electric heating experiencing the highest winter bill increase. - Annually howe...

AI summary Space heating significantly affects winter bills for TOU participants, particularly those using electric heating, which see the highest increases. However, annually, TOU participants with steady electric and electrified space heating experience average bill savings of $120 and $153, respectively.

- This analysis does not account for additional cost/savings from nonelectric heating sources. Parameters De- Electrified Electrified Steady Electric Steady Non-Electric Winter Avg. Bill Savings ($/day) a -1.12 ± 0.02 -1.49 ± 0.02 -1.61 ±...

AI summary This analysis examines the impact of Time-Varying Pricing (TVP) on residential electricity bills, comparing electrified and non-electrified homes across winter, non-winter, and annual periods. It shows varying levels of average bill savings and significance, though annual results are not statistically significant.

Load Impact by Space Heating Classification Mor ning Eve ning Parameters De-Electrified Electrified Steady Electric Steady Non-Electric De-Electrified Electrified Steady Electric Steady Non-Electric Avg. Load Reduction® 0.57 ± 0.66 ± 0.74...

AI summary This section presents load impact data by space heating classification, showing average load reductions and significance levels for different electrification scenarios. The data compares de-electrified, electrified, and steady electric/non-electric categories during morning and evening periods, highlighting the impact of Time-Varying Pricing (TVP) on residential Critical Peak Pricing (CPP) participants.

- All Space Heating Classes exhibit statistically significant load reduction during morning and evening CPP events. - CPP participants with Steady-Electric heating systems achieved the highest load reductions of 0.74 kW and 0.92 kW during...

AI summary The text discusses load reduction during Critical Peak Pricing (CPP) events, noting that all space heating classes show significant reductions. Steady-Electric heating systems achieved the highest load reductions, followed by electrified space-heating systems.

Load Impact with EcoShift Participants a Eco Shift Event Date Event Hour Window Is CPP Event? Is Weekend? All 04-Dec-2024 5 PM - 9 PM ~ x CPP 15-Dec-2024 5 PM – 9 PM ✓ ✓ All 20-Dec-2024 7 AM – 11 AM ✓ х CPP 22-Dec-2024 5 PM – 9 PM ✓ ✓ All...

AI summary The document outlines the alignment of Eco Shift events with Critical Peak Pricing (CPP) and Time-of-Use (TOU) events, noting that nearly all Eco Shift events coincided with CPP events, with seven events aligning with both CPP and TOU.

Important: These effects represent the effect of TVP on customers relative to their control, of whom are in the same heating classification. Parameters De- Electrified Electrified Steady Electric Steady Non- Electric Winter, Non-Holiday We...

AI summary The text presents data on the impact of Time-Varying Pricing (TVP) on customer energy usage across different categories, including de-electrified, electrified, and steady electric/non-electric customers. It compares average usage reductions and significance levels during winter weekdays, weekends/holidays, and non-winter days, indicating varying effectiveness of TVP strategies.

Key Findings - Residential TOU & CPP participants continue to demonstrate statistically significant load reduction during peak periods with minimal snapback. - For the first time, TVP combined with technology (e.g. smart thermostats) and D...

AI summary The Key Findings section highlights that residential Time-Varying Pricing (TVP) participants, especially those using smart thermostats and demand response programs like Eco Shift, showed significant load reduction during peak periods. Electrification of space heating also contributed to reduced peak load without significant increases in annual energy consumption.

Parameters Morning Peak Evening Peak All Peak Hours (Overall) Avg. Load Reduction (kW) a 0.7 ± 0.2 0.9 ± 0.2 0.8 ± 0.1 Avg. Load – Commercial TOU 10.9 10.3 10.6 Participants, Pre-Pilot (kW) Relative Avg. Load Reduction (%) 8 6.4% 8.6% 7.5%...

AI summary The table presents data on load reduction for commercial Time-of-Use (TOU) participants during morning and evening peak hours, showing average load reductions and statistical significance. The overall load reduction is reported as 0.8 kW, with varying levels of significance across different time periods.

Load Reduction during Peak Periods by Rate Class - General commercial TOU participants exhibit significant load reductions during both morning and evening peak periods, with an average overall reduction of approximately 2.6 kW. - Small Gen...

AI summary The text discusses load reduction during peak periods by rate class, showing that general commercial TOU participants have significant load reductions, while small general TOU participants show slight increases during peak hours.

Energy Usage - Commercial TOU participants exhibit an increase in daily electricity usage of 15.4 kWh/day on annual average. - Participants demonstrated the greatest increases in daily electricity usage during weekends and holidays in Wint...

AI summary Commercial Time-of-Use (TOU) participants show an average increase of 15.4 kWh/day in daily electricity usage, with the highest increases occurring on weekends and holidays during both winter and non-winter seasons.

- Load reduction during the midpeak period is the highest, which was not expected as the MURB TOU mid-peak electricity rate is half that of the evening peak rate. Parameters Morning Peak Mid-Peak Period b Evening Peak Overnight Period c Ov...

AI summary Load reduction during the midpeak period was the highest, despite the MURB TOU mid-peak electricity rate being half that of the evening peak rate. Statistical significance was noted, but results are not conclusive due to a low sample size.

TVP Phase 4 Key Milestones - NS Power has completed the EM&V completely in-house for the first time. - Residential customers continue to shift load similarly to previous evaluations with significant increase in enrolment. - Eco Shift + TVP...

AI summary TVP Phase 4 has seen NS Power complete EM&V in-house for the first time, with residential customers showing continued load shifting and significant enrolment increases. Eco Shift and TVP have enhanced load shift, while commercial and MURB TOU and CPP rates are showing positive results. Updates on the Year Five (2025/26) Evaluation Report are also mentioned.

Year Five Report - The Evaluation Report for the 2025/26 TVP Season will be filed by July 31, 2026. - This report will include Phase 5 Winter results for the MURB TOU Tariff. - This presentation along with the June 2026 Kick-off & Work Pla...

AI summary The Year Five Report outlines the submission of the 2025/26 TVP Season Evaluation Report by July 31, 2026, which will include Phase 5 Winter results for the MURB TOU Tariff. The report will be accompanied by related presentations and responses.

Technical Session 2 Topics Technical Session 2 is to be scheduled for Fall 2026, and is expected to cover the following: - Recommended EM&V refinements - Review of System Planning related values applicable to TVP - Updated ELCC study resul...

AI summary Technical Session 2, scheduled for Fall 2026, will address EM&V refinements, TVP-related system planning values, ELCC study results, system load impacts, avoided costs application, TVP pricing alignment, and an updated rate design scorecard.

July 7, 2026 [[email protected]](mailto:[email protected]) Kathleen Murray Regulatory Counsel Nova Scotia Power Inc. PO Box 910 Halifax NS B3J 2W5 Dear Ms. Murray: M12932 – Nova Scotia Power Inc. – Time-Varying Pricing Pi...

AI summary Nova Scotia Power Inc. submitted its 2024/25 Evaluation Report for the Time-Varying Pricing Pilot Program to the Nova Scotia Energy Board. The Board will review the report concurrently with the upcoming 2025/26 Evaluation Report, which NS Power is required to file as a separate exhibit in matter M12932.

August 7, 2026 Regulatory Counsel Nova Scotia Power Inc. PO Box 910 Halifax NS B3J 2W5 Kathleen Murray [[email protected]](mailto:[email protected]) Dear Ms. Murray: M12932 – Nova Scotia Power Inc. – Time-Varying Pricing...

AI summary Nova Scotia Power Inc. submitted evaluation reports for its Time-Varying Pricing Pilot Program for 2024/25 and 2025/26. The Nova Scotia Energy Board has decided to review both reports concurrently through a paper hearing process, with specific deadlines for interventions and submissions.

NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The Public Utilities Act - and - IN THE MATTER OF: Nova Scotia Power Inc., - Time-Varying Pricing Pilot Program – 2024/25 (Year Four) and 2025/26 (Year Five) Evaluation Reports

AI summary This document pertains to the evaluation of Nova Scotia Power Inc.'s Time-Varying Pricing Pilot Program for the years 2024/25 and 2025/26 under the Public Utilities Act.

NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The Public Utilities Act , RSNS 1989, c 380 as amended - and - IN THE MATTER OF: Nova Scotia Power Inc. – Time-Varying Pricing Pilot Program – 2024/25 (Year Four) Evaluation Report

AI summary The document pertains to a regulatory proceeding under the Public Utilities Act, involving an evaluation of Nova Scotia Power Inc.'s Time-Varying Pricing Pilot Program for its fourth year (2024/25).

NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The Public Utilities Act IN THE MATTER OF: Nova Scotia Power Inc. – Time-Varying Pricing Pilot Program – 2024/25 (Year Four) and 2025/26 (Year Five) Evaluation Reports

AI summary The Nova Scotia Energy Board is evaluating Nova Scotia Power Inc.'s Time-Varying Pricing Pilot Program for the 2024/25 and 2025/26 periods. This evaluation is part of a regulatory proceeding under the Public Utilities Act.

NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The Public Utilities Act IN THE MATTER OF: NOVA SCOTIA POWER INCORPORATED'S Time Varying Pricing Pilot Program – 2024/2025 (Year Four) and 2025/26 (Year 5 Evaluation Reports)

AI summary The Nova Scotia Energy Board is considering Nova Scotia Power Incorporated's Time Varying Pricing Pilot Program for 2024/2025 (Year Four) and 2025/26 (Year 5 Evaluation Reports) under the Public Utilities Act.

NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The PUBLIC UTILITIES ACT -and- IN THE MATTER OF: NOVA SCOTIA POWER INCORPORATED'S Time Varying Pricing Pilot Program – 2024/2025 (Year Four) and 2025/26 (Year 5 Evaluation Reports)

AI summary The Nova Scotia Energy Board is considering Nova Scotia Power Incorporated's Time Varying Pricing Pilot Program for the years 2024/2025 and 2025/26, based on evaluation reports submitted.

NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: THE PUBLIC UTILITIES ACT - and - IN THE MATTER OF: AN APPLICATION by NOVA SCOTIA POWER INCORPORATED for the Time-Varying Pricing Pilot Program - 2024/25 (Year Four) and 2025/26 (Year Five) Evaluat...

AI summary The Nova Scotia Energy Board is considering an application by Nova Scotia Power Incorporated for the evaluation of the Time-Varying Pricing Pilot Program for the years 2024/25 and 2025/26.

Request IR-1: - The Board's decision in matter M11823 directed Nova Scotia Power (NS Power) to provide an - analysis of the corresponding system margin forecasts and Critical Peak Pricing (CPP) events in - the Year 4 report. In Appendix A...

AI summary The Board's decision in matter M11823 requested Nova Scotia Power (NS Power) to provide an analysis of system margin forecasts and Critical Peak Pricing (CPP) events in the Year 4 report. NS Power provided a table identifying dates and times of low forecast system margin and whether a CPP event was scheduled, but the table lacks forecast system margin values.

Request IR-3: - Please quantify by rate class who left the TVP pilot and those who switched from CPP to TOU - and vice versa.

AI summary Request IR-3 asks for quantification of customer movements between the Time-of-Use (TOU) pilot and Critical Peak Pricing (CPP), specifically by rate class, including those who left the TVP pilot and switched from CPP to TOU and vice versa.

Request IR-4: - Did NS Power anticipate any energy savings during off-peak periods? - a) If so, how much by rate class, and was it achieved?

AI summary The document asks whether NS Power anticipated energy savings during off-peak periods and, if so, how much by rate class and whether those savings were achieved.

Request IR-5: - a) Please describe the heating scenario mix for domestic customers who are on a standard - tariff. - b) Please also describe the anticipated change in this mix over the next ten years and the anticipated effects of changes...

AI summary The request asks for a description of the current heating scenario mix for domestic customers on a standard tariff and the anticipated changes over the next decade, along with the expected impact on Time-of-Use (TOU) and Critical Peak Pricing (CPP) rates.

Request IR-7: - Appendix A discusses how NS Power has improved communications with potential TVP pilot - participants regarding Bill Savings using an estimation tool for inbound customer inquiries. Please - discuss the communication improv...

AI summary Appendix A outlines communication improvements made by NS Power to existing TVP pilot customers regarding Bill Savings using an estimation tool for inbound customer inquiries.

Request IR-8: - NS Power's Demand Charge Assessment on pdf page 502 states "On average customers shifting - load from peak to off-peak hours experience demand increase with negligible increase in savings - after shifting 6% or more of peak...

AI summary NS Power's demand charge assessment indicates that shifting load beyond 6% may increase demand charges despite energy cost savings. The document requests discussion on NS Power's plans to model the removal of the demand charge.

Request IR-9: - In reference to Appendix C, TVP Tariff Marketing and Recruitment:

AI summary The document refers to Appendix C, which outlines the TVP Tariff Marketing and Recruitment process. This section is part of Request IR-9 and appears to be related to the implementation or discussion of Time-of-Use tariff strategies.

Question: How would NS Power characterize the commercial TOU tariff's load-shifting performance given that Table 37 shows no statistically significant load change during any of the top 20, 50 or 88 highest ANL hours, whether coincident wit...

AI summary The question asks NS Power to characterize the load-shifting performance of the commercial time-of-use (TOU) tariff, noting that Table 37 shows no statistically significant load change during the top 20, 50, or 88 highest ANL hours, whether during TOU peak periods or overall.

Request IR-2: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 73, and Table 40 on that page. "The commercial TOU customers experienced an average Bill increase of approximately 12.3 $/day and 3.8 $/day across the Winter and ann...

AI summary The text references a report indicating that commercial TOU customers experienced statistically significant bill increases during Phase 4 of the pilot program. It asks whether NS Power considers these customers to have been financially worse off and if any changes to tariffs, eligibility, or screening are being considered before the pilot resumes in 2026/27.

Request IR-3: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 18. "When separated by rate class, Small General customers exhibit a load increase during peak periods (0.22 kW) relative to the General rate class that demonstrate...

AI summary The text discusses load differences between Small General and General rate classes, noting a 0.22 kW increase during peak periods for Small General customers compared to a 2.6 kW reduction for General rate class customers.

Questions: a) Please provide the Phase 4 commercial TOU and commercial CPP results separately for the Small General and General rate classes, including load reduction, ANL-hour, usage and bill-impact results. b) Given the load increase for...

AI summary The document includes two questions regarding Phase 4 commercial TOU and CPP results for specific rate classes and potential changes to the Small General TOU and CPP tariffs by NS Power.

Request IR-4: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 15. "Notably, no change in monthly demand was observed in MURB TOU participants, despite the removal of the demand charge." Question: Does the referenced finding of...

AI summary The referenced finding indicates that removing the demand charge on MURB TOU tariffs did not change monthly demand, raising questions about whether demand charges are a barrier to load shifting on other TVP tariffs.

Request IR-5: Reference: M12932 N-1 TVP Evaluation Report, Appendix Am Table 52 and the following statement from Appendix A, p. 92: "Results indicate that MURB TOU participants exhibit load reduction during the top 20, 50, and 88 highest A...

AI summary The text references a study on MURB TOU participants' load reduction during peak ANL hours, noting that only reductions during top 50 and 88 hours are statistically significant. It asks NS Power to clarify which ANL-hour distribution they rely on for assessing the MURB TOU tariff's peak reduction contribution and how they handle the lack of significance in the top 20 ANL hours.

Request IR-6: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 91 and Table 51, footnotes b and c. "This effect is evaluated based on the same DiD approach that was applied to the load reduction calculation, but specifically for...

AI summary The text discusses the evaluation of load reduction during the morning and evening snapback periods under a Time-Varying Pricing (TVP) program. It notes that the morning snapback period is a three-hour window (11 AM – 2 PM), while the evening snapback period is described as a four-hour window. The question raised is why there is a discrepancy in the timeframes used for analysis.

Request IR-7: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 20. "The objective of these rates is to provide customers with rate choice that can enable them to save on their electricity bill while shifting demand from peak per...

AI summary The Year Four Report discusses the objective of TVP tariffs to reduce fuel and power costs and avoid infrastructure capital costs in the long term. However, it only reports per-customer metrics such as load reduction, daily usage, and bill impacts, without quantifying aggregate peak load reduction or its monetary value.

Request IR-9: Reference: M12932 N-1 TVP Evaluation Report, Appendix E, Attachment 4, p. 17 of 47 (Rate Design Scorecard, Fair Value criterion added at Technical Session 2). "The Tariff provides customers savings equal to the avoided cost t...

AI summary The document requests the completed Rate Design Scorecard for each TVP tariff in Phase 4, including the Fair Value criterion and the dollar avoided-cost figure used. It also asks NS Power to explain how they assess cost-reflectiveness if the criterion has not been scored.

Request IR-10: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 148, quoting the Board's Decision in M12249: "… the Board notes that E1 should be fully prepared to address the questions raised in this proceeding about potential...

AI summary The Board has directed E1 to address potential overlap between its DSM Plan and NS Power's Critical Peak Pricing Program, and to explain how each program targets constrained areas of the grid. It also expects NS Power to cooperate with E1 in this exploration. The request asks for an analysis of equity and rate-impact consequences of funding demand response through DSM charges versus tariff design.

Request IR-11: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 17. For Residential TOU : "Significant enhancements to load reduction (+0.40 kW) occurred where technology (i.e. Eco Shift + smart device) were present." For Reside...

AI summary The document references TVP Evaluation Reports showing that residential TOU and CPP programs achieved greater load reduction when combined with Eco Shift and smart devices. It questions whether NS Power plans to incentivize or require enabling technologies as part of TVP enrolment.

Request IR-12: Reference: M12932 N-1 TVP Evaluation Report, Appendix E, Attachment 2, p. 16 of 121. Regarding TVP and EcoShift cross enrolment: "NS Power and EfficiencyOne (E1) will be monitoring this year before deciding whether cross-pro...

AI summary NS Power and EfficiencyOne are monitoring cross-program enrolment between TVP and EcoShift before deciding its future. They are collaborating on marketing efforts to enhance cross-promotion. The request asks for details on cross-promotional activities in Phase 4 and plans for combining Eco Shift with TOU and CPP tariffs.

5 Request IR-14: 6 Reference: M12932 N-1 TVP Evaluation Report, Appendix B, p. 13 of 67. 7 "Overall satisfaction with the Time-Varying Pricing Rate Pilot (TVP) is consistent from 8 2025, with top 4 box scores increasing by two points." 9

AI summary The document references a report evaluating the Time-Varying Pricing Rate Pilot (TVP), noting that overall customer satisfaction has increased by two points since 2025, with top 4 box scores remaining consistent.

23 Survey question Reported mean (2025, 10-point Appendix scale) B page Q.24b – Overall satisfaction with the TVP Overall 7.1 (n=2,103); TOU 6.9 p. 13 of 67 Rate Pilot (n=1,332); CPP 7.5 (n=771) Q.15 – "I understand how the rate plan TOU 7...

AI summary Customer satisfaction survey results from the Rate Pilot show varying levels of satisfaction with TVP, TOU, and CPP rate plans, with overall satisfaction at 7.1 for TVP, 6.9 for TOU, and 7.5 for CPP. Customers also expressed mixed feelings about understanding their power bills and the impact of the rate plans on their bills.

Request IR-16: Reference: M12932 N-1 TVP Evaluation Report, Appendix A, p. 22, Table 6 (figures as reported): Domestic TOU — 2,174 enrolled prior to the Phase 4 Winter plus 4,271 newly enrolled, less 829, leaving 5,616 enrolled at March 31...

AI summary NS Power reports high residential retention rates for Time-of-Use (TOU) and Critical Peak Pricing (CPP) programs, but participant satisfaction scores are low at 7.1 out of 10. The question asks NS Power to explain how these figures align and whether the satisfaction results are a concern.

Request IR-17: Reference: M12932 N-1 TVP Evaluation Report, Appendix B, p. 14 of 67. "Comparing satisfaction results across the provinces, overall TVP pilot participant satisfaction is significantly lower in Western Nova Scotia compared to...

AI summary The text discusses participant satisfaction with TVP and CPP programs, noting lower satisfaction in Western Nova Scotia due to higher prevalence of electric heating, but also states that overall satisfaction does not vary significantly by heat source. This apparent contradiction needs reconciliation.

Request IR-18: Reference: M12932 N-1 TVP Evaluation Report, Appendix E, Attachment 4, p. 12 of 47. "This indicates that, at the anticipated levels of load shift for a TOU customer, the current rate structure and/or pricing signal ratios of...

AI summary The text discusses challenges with achieving load shifting above 6% under the current TOU rate structure, suggesting that revisions to the demand pricing structure may be necessary. It also raises questions about system capabilities, interim solutions, and NS Power's position on restructuring non-coincident demand charges.

Refer to M12932, Exhibit N-1, NS Power Time Varying Pricing (TVP) Pilot Program Year Four (2024/2025) Evaluation Report, and Exhibit N-2, NS Power TVP Year 4 Report Appendix A (Clean) - Refiled, dated July 13, 2026, (collectively the "Year...

AI summary The document references the evaluation report of NS Power's Time Varying Pricing (TVP) Pilot Program for Year Four (2024/2025), including specific appendices and tables that detail participation and retention results as of March 31.

Request IR-2: Refer to Exhibit N-1, Year 4 Report Results, Summary of Year Four Evaluation Results, pp. 2-3 of 5, which states: Importantly, the Year Four evaluation identifies statistically significant load shifting for commercial TOU and...

AI summary The Year Four evaluation found statistically significant load shifting for commercial TOU and CPP tariffs, a first-time occurrence, and confirmed residential TVP load reductions during peak periods. The request asks NS Power to explain these findings, including program changes, methodological differences, implications for future evaluations, and the timing of peak load reductions.

ANL hours that coincide with TOU peak periods, participants did not exhibit statistically significant load reduction. a solution to heterogeneity. Please also refer to NS Power's TVP Pilot Year 3 2023-2024 evaluation report, (M11823, Exhib...

AI summary The document discusses the lack of statistically significant load reduction among commercial participants in NS Power's TOU and CPP programs, referencing Econoler's evaluation report and querying NS Power on modeling approaches, program value, and methodological differences between report years.