Topic:"Rate Design" in M11689

.................................................. 58 15 6.0 Commerical Sector ............................................................................................................ 64 16 6.1 Small General Service.......................

AI summary The text outlines a regulatory proceeding document's table of contents, detailing sections on commercial, industrial, and municipal sectors, system losses, net system requirements, peak demand, and sensitivity analysis. It structures rate classes and system performance metrics for regulatory review.

Vehicle Avg Avg kW/vehicle Avg kWh/year Type km/year 20 19F on Peak LDV 17,427 3,485 0.9 MDV 22,779 8,205 1.6 HDV 62,888 113,890 7.3 3 4 The peak impact assumes that 70 percent of charging is managed (including direct control 5 through EV...

AI summary The text discusses the average energy consumption and peak demand contributions of different vehicle types, including LDV, MDV, and HDV, based on managed and unmanaged EV charging scenarios. It highlights the impact of managed charging, using technologies like DERMS, on reducing peak demand and electricity costs.

4 14 9 5 2033 20 4 16 10 6 2034 20 4 16 10 6 DATE: April 30, 2024 Page 50 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 4.5 Price Data 2 3 Price data is an input to the SAE forecasts for the reside...

AI summary The 2024 Load Forecast Report discusses the use of price data in SAE forecasts, including the calculation of revenue per kWh and the derivation of a 12-month moving average. The nominal price of electricity for 2024 is based on a 7.7% average increase, incorporating the Base Cost of Fuel Increase and the BA Rider approved in April 2024.

rt of the 2023-2024 GRA and the BA Rider approved 14 in April of 2024. 26 2025 is forecast to increase to account for projected increased fuel costs 25F 15 while 2026 is forecast to increase to account for recovery of outstanding fuel cost...

AI summary The document discusses the 2023-2024 GRA and BA Rider approved in April 2024, with forecasts for 2025 and 2026 showing increases to account for fuel costs and recovery of outstanding fuel costs over three years. The forecast also indicates an average annual increase of 2% from 2027 onwards, with 2029 showing a return to inflation rates. Price elasticity is discussed in relation to the SAE model and the TVP Pilot EM&V in matter M11267.

lasticity estimation from the 8 TVP Pilot EM&V in matter M11267 and assess if the results provide a more robust model.” 9 The TVP Pilot estimates two elasticities: 2827F 10 • Own/daily price elasticity captures the change in the level of o...

AI summary The text discusses elasticity estimates from the TVP Pilot EM&V in matter M11267, focusing on own/daily price elasticity and substitution price elasticity. These estimates are based on subsets of customers enrolled in the TVP pilot and are not directly comparable to the overall population or long-term load forecasts.

ion behaviour in response to year-over-year price changes. The estimated 2 elasticities for the two TVP rates are shown in Figure 34. 3 4 Figure 34: TVP Price Elasticity Estimates 5 6 7 Although the Daily Price Elasticity for the TOU rate...

AI summary The document discusses price elasticity estimates for TVP rates and their impact on load forecasts, noting that elasticity has a minimal effect on sales compared to other factors. It also mentions the role of Demand Side Management (DSM) in electricity use forecasting, referencing E1's proposed supply agreement and 2019 study for DSM projections.

1 forecast DSM is overstated; rather, it is a way of accounting for DSM that is captured 2 elsewhere in the forecast. The methodology is not specific to DSM and could be applied to 3 other variables that need to be highlighted in the forec...

AI summary The text discusses the inclusion of historical DSM in forecasting models, noting that DSM is not specific to demand-side management and can be applied to other variables. The Residential model shows a slight improvement in fit with DSM included, indicating that 55.6% of DSM savings are not captured by other variables and must be included in the forecast.

nd Industrial customers by rate class or by month, so by creating a combined 23 model for these classes, the level of uncertainty around allocating historical DSM savings 24 across rate classes and months of the year is reduced. The DSM va...

AI summary The document discusses the use of a combined model for industrial customers by rate class and month to reduce uncertainty in allocating historical DSM savings. The DSM variable coefficient remains at -0.448, indicating a 45% adjustment to future load forecasts based on DSM amounts. The model has a high adjusted R-squared of 0.821 and a low MAPE of 2.75, showing a strong fit.

) 2024 Load Forecast Report REDACTED 1 Figure 45: Historical and Forecast Annual Small General Sales 2 3 4 5 Please refer to Appendix B for tables with a detailed breakdown of the changes from 2024 6 to 2034. Total change between 2024 and...

AI summary The 2024 Load Forecast Report indicates a 19% increase in small general sales from 2024 to 2034. General class load is expected to decrease by 0.1% annually over the 10-year period, influenced by lower EV load, hybrid heating scenarios, and DSM programs. A drop in sales in 2026 is attributed to shifting to the RTR market and increased solar generation.

requiring 23 transformers with long-lead times, such as padmount transformers, large commercial 24 customers are asked to provide notice of intent to connect one year in advance. Date Filed: June 19, 2024 NSPI (CA) IR-8 Page 3 of 3 2024 Lo...

AI summary NSPI is required to provide data on the impact of time-varying pricing (TVP) rates, AMI technology's role in reducing peak demand, and additional data needed for extrapolating pilot results in the 2024 Load Forecast Report.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to CA Information Requests NON-CONFIDENTIAL 1 Response IR-9: 2 3 (a) The peak reduction associated with TVP rates is provided in Figure 56 of the 2024 Load 4 Forecast report. 5 6 (b)...

AI summary NSPI responds to NSUARB's information requests regarding the 2024 Load Forecast Report, referencing peak reduction from TVP rates, AMI-related savings by 2028/2029, and a table analyzing TOU and CPP event occurrences. The response highlights forecasted peak savings and event data.

00 Yes Potential 1/29/2024 Weekday Evening 17:00 – 18:00 Yes Potential 3/1/2024 Weekday Morning 7:00 – 8:00 Yes Potential 1/24/2024 Weekday Morning 8:00 – 9:00 Yes Yes 1/8/2024 Weekday Evening 17:00 – 18:00 Yes Potential 1/6/2024 Weekend E...

AI summary NSPI is developing long-term plans for TVP tariffs, referencing Synapse IR-09 and the Time Varying Pricing Pilot Year Three Report. Data collection for TVP effects is ongoing, with stakeholder collaboration on implementation. The Load Forecast Report (NSUARB M11689) and Technical Session 4 are mentioned as part of the process.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to EOne Information Requests NON-CONFIDENTIAL 1 Request IR-4: 2 3 Reference: NS Power 2024 Load Forecast, Page 39, Line(s) 4-7 4 5 The peak impact assumes that 70 percent of charging...

AI summary The 2024 Load Forecast Report (NSUARB M11689) includes NSPI's responses to EOne's information requests about managed electric vehicle (EV) charging assumptions, including jurisdictional research, current enrollment numbers, and future forecasts. The response refers to another part (IR-13 part a) for detailed information.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to EOne Information Requests NON-CONFIDENTIAL 1 (b) 2 (i) Based on survey results that indicate approximately 8 percent of customers on the 3 TVP rates have EVs, the total number of...

AI summary The 2024 Load Forecast Report (NSUARB M11689) indicates approximately 1,000 EVs on time-varying rates (TVP), with 8% of TVP customers owning EVs. EOne's Q1 DSM report notes 46 residential participants in the Eco Shift program for EV telematics, with enrollment ongoing. EV charging is forecasted to be 70% managed starting in 2024.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-3: 2 3 Page 19 explains that to reflect global warming, a trend is applied to the annual HDD and 4 CDD variables using an...

AI summary NSPI confirms that HDD and CDD trends are re-estimated annually using 30-year data and 10-year moving averages. While CDD increases are slower than HDD declines, NSPI notes that cooling demand from heat pumps may drive load growth on CDD days, citing changes in the WtXCool variable over time.

1 Request IR-17: 2 3 Page 52 of the Report discusses the price impact to sales through imposed price elasticities 4 and explains that the SAE models use a price elasticity of -0.15. In matter M11683 NS Power 5 identified that -0.15 would b...

AI summary The document discusses NS Power's use of a uniform price elasticity (-0.15) across all customer classes in its Load Forecast Report, despite varying responses to price changes. Questions challenge this approach, while NS Power defends it as simpler and less impactful on sales forecasts compared to end-use assumptions. Long-term elasticity considerations are also addressed.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-2: 2 3 Historical Sales and Energy Data (Figures 1, 3, 37-39, 43, 45-46, 48-50, 52). For all of the 4 following, to the...

AI summary NSPI responds to Synapse's IR-2 requests by directing to spreadsheet attachments containing historical sales data, electric space-heat usage, system load data, and unmetered sales. Notably, 2023 electric heat data is unavailable, and unmetered sales comprised ~0.7% of total sales in 2023.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 (v) For LDV, MDV, and HDV, please provide peak load reductions in kW per 2 vehicle for each vehicle category that NSPI expect and a...

AI summary The document outlines a series of information requests from the NSUARB to NSPI regarding the impacts of managed charging programs and time of use rates on peak load reductions for different vehicle categories, as well as the status of time of use tariffs in pilot stages. NSPI is asked to provide supporting evidence for assumptions about managed and unmanaged EV charging.

1 A third charge management type, charge management with Vehicle-Grid 2 Integration (VGI), still features drivers that shift their times of charging to minimize 3 charging costs, but also features an aggregator’s involvement to smooth peak...

AI summary The text discusses charge management strategies for electric vehicles, including Vehicle-Grid Integration (VGI) and the impact of managed charging on peak loads. It references a blended scenario with 70% of EV owners using an aggregator and 30% on flat rates. The findings from the Smart Grid Nova Scotia project are detailed in M11621 and are based on a small pilot group in Nova Scotia.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 (f) 2 (i-ii) No, Figure 26 is for all EVs types. 3 4 (g) NS Power is currently undertaking engagement with Time-Varying Pricing (TV...

AI summary NSPI is engaged in developing a long-term plan for Time-Varying Pricing (TVP) Tariffs through stakeholder engagement sessions, with upcoming sessions discussing tariff design, marketing, and recommendations for future deployment as part of matter M09777.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-21: 2 3 End-Use Intensity Trends (Section 4.4) 4 5 (a) The report references...

AI summary NSPI responds to Synapse's information requests regarding the 2024 Load Forecast Report, addressing the impact of critical peak pricing (CPP) and time-varying pricing (TVP) on EV charging behavior and load forecasting assumptions. NSPI assumes 70% of EV charging will be managed through rate structures and direct control, and TVP rates are expected to meet peak savings goals.

1 Request IR-24: 2 3 General Service (Section 6.2). 4 5 (a) Please explain and quantify the specific reasons for the differences from the previous 6 forecast. 7 8 (b) Please quantity separately and explain the derivation of the effects for...

AI summary The request seeks explanations for differences in load forecasts between 2023 and 2024, focusing on factors such as EV loads, space heating, DSM programs, and solar generation. The response notes a decrease in general service class load, a larger drop attributed to increased solar generation, and a reduced impact from EVs compared to previous forecasts.

as 28 revised accordingly. Date Filed: June 19, 2024 NSPI (Synapse) IR-28 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 R...

AI summary The document provides the 2024 Load Forecast Report for municipal loads, including total estimated load in GWh and peak demand in MW for the years 2024 through 2034. It notes that the load served by NS Power is expected to decrease in 2025 due to customers switching to third-party suppliers through the OATT and BUTU programs.

on from demand response measures? 28 Date Filed: June 19, 2024 NSPI (Synapse) IR-32 Page 2 of 8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFID...

AI summary The document includes information requests related to demand response programs, energy efficiency evaluations, and load forecasting. NSPI is asked to provide reports on DSM programs, the Eco Shift Pilot, and details on figures related to load forecasts. Responses reference prior filings, including a 2021 load forecast report.

Table 5: 2023 Residential DR Evaluation Approach Evaluation Objectives Research Questions Methodology Establish available DR › Are the data in the tracking sheet complete, › Tracking sheet audit capacity results for the accurate, and consi...

AI summary This section outlines the evaluation approach for the 2023 Residential Direct Load Control pathway, focusing on assessing data completeness, accuracy, and available DR capacity through a tracking sheet audit and water heater controller meter data analysis.

the Nova Scotia Utility and Review Board (NSUARB) as part of the 2014 Cost of Service Study Progress Update.8 Table 8: Evaluated 2023 Residential DR New Available DR Capacity Shifted Aquanta Total Number of Units 22 41 63 In-service Rate (...

AI summary The document references a 2014 Cost of Service Study Progress Update by the Nova Scotia Utility and Review Board (NSUARB), and includes tables evaluating residential demand response (DR) capacity for 2023, detailing metrics such as number of units, in-service rates, and available DR capacity at the meter and generator levels.

generator, thus exceeding the planned new and available DR capacity of 0 MW. 2023 Res DR Finding: The new baselining approach selected through the 2023 evaluation resulted in more accurate estimates. The residential DHW load during a DR ev...

AI summary The 2023 residential demand response (DR) findings indicate that the new baselining approach improved accuracy but resulted in lower available DR capacity. Available DR capacity varies by time of day, with mornings having 20% more capacity than evenings. Connectivity issues caused about 20% of controllers to fail to respond to DR events. The evaluated DR capacity was lower than what EOne tracked, prompting a recommendation to include in-service rates and unitary values in EOne's tracking.

fication & Qualifications 2 Q: Mr. Wilson, please state your name, occupation, and business address. 3 A: I am John D. Wilson. I am the Vice President of Grid Strategies, LLC, Bethesda, MD. 4 Q: Summarize your professional education and ex...

AI summary John D. Wilson, Vice President of Grid Strategies, LLC, provides his educational background, professional experience in regulatory policy, and expertise in energy resource analysis, prudency reviews, ratemaking, and cost recovery for utility efficiency programs. His work spans over twelve years at the Southern Alliance for Clean Energy and includes involvement in regulatory proceedings and energy project evaluations.

s several areas in which load forecast methods could be improved. 8 Finally, I will discuss inconsistencies between the load forecast and the distribution system 9 planning forecast. 10 Q: Please summarize your recommendations. 11 A: I hav...

AI summary The expert outlines six recommendations to improve load forecasting, including updating residential heating intensity models, incorporating weather trends, convening a hearing on winter heating demand, adjusting EV charging forecasts, and aligning load forecasts with distribution planning. These aim to enhance forecast accuracy and address systemic inconsistencies.

has been shifted three years later.20 NS Power expects time-varying 6 pricing tariffs to reduce demand by 4 MW in 2025, 12 MW in 2026, and by 32-36 MW in 7 2086 and thereafter.21 8 Q: Is this forecast reasonable? 9 A: No, not given the cur...

AI summary The text questions the reasonableness of NS Power's forecast for demand reduction through time-varying pricing tariffs, citing insufficient pilot program results and lack of expansion plans. The response highlights that current participation levels and revised tariff design may not achieve projected reductions by 2026, referencing a 2021 load forecast report.

approval in time to enroll sufficient customers to achieve 12 25 MW of demand reduction in 2026. 20 Exhibit N-1, 2021 Load Forecast Report, Matter No. M10109 (April 30, 2021), p. 74. 21 Exhibit N-1, 2023 Load Forecast Report, p. 78. 22 Exh...

AI summary The text references a demand reduction target of 12.25 MW by 2026 and cites exhibits including load forecast reports and a time-varying pricing pilot program evaluation. These documents support regulatory proceedings related to demand-side management and rate design initiatives.

electric vehicle owners. Considering the impact of managed charging, which 7 further reduces the contribution to peak, a more reasonable forecast assumption is 0.45 8 kW/vehicle. 9 Q: What would be the impact of adjusting to your proposed...

AI summary NS Power estimates adjusting EV peak demand from 0.9 kW to 0.45 kW/vehicle would reduce 2033 peak demand by 120 MW (from 240 MW to 120 MW). This adjustment could be further reduced through managed charging programs. The correction would significantly impact resource planning, offsetting load forecast increases from removing peak savings attributed to the time-varying pricing pilot.

JOHN D. WILSON Vice President Grid Strategies, LLC SUMMARY OF PROFESSIONAL EXPERIENCE 2023– Vice President, Grid Strategies, LLC. Provides research, technical assistance, Present and expert testimony on electric- and gas-utility planning,...

AI summary John D. Wilson's professional experience includes roles in utility regulation, energy efficiency, and renewable resource evaluation. He has provided expert testimony on rate design, cost recovery mechanisms, and resource planning for electric utilities, as well as directed regulatory policy and litigation activities related to clean energy and air quality.

gia PSC Docket Nos. 4822, 16573 and 19279, direct, rebuttal and surrebuttal testimony in Georgia Power Company’s PURPA avoided cost review on behalf of the Georgia Large Scale Solar Association. Reviewing compliance with prior Commission o...

AI summary The text outlines legal and regulatory proceedings involving fuel adjustment mechanisms, rate design, and compliance with resource planning. Key entities include advocacy groups and utility regulators. Topics include fuel cost adjustments, rate design elements, and compliance with regulatory orders in multiple jurisdictions.

John D. Wilson  Grid Strategies, LLC Page 9 Critical Peak Pricing programs and Time of Use periods. Modifications to load management programs. Nova Scotia UARB Matter No. M09898, direct testimony on Nova Scotia Power’s Annually Adjusted R...

AI summary The text outlines testimony related to energy pricing programs, regulatory matters, and evaluations. It covers topics like Critical Peak Pricing, Time-Varying Pricing, and load management programs, with references to Nova Scotia UARB matters and other jurisdictional dockets involving rate design, capacity savings, and program evaluation.

Hourly Real Time Pricing Pilot on behalf of the Small Business Utility Advocates. Rate design for real time pricing tariff. Marketing to small businesses. Evaluation plan. California PUC Docket R.20-08-020, direct and reply testimony with...

AI summary The text outlines regulatory activities involving the Small Business Utility Advocates (SBUA) and Nova Scotia Consumer Advocate, including rate design for real-time pricing and net energy metering (NEM) tariffs, testimony in California PUC dockets, and addressing risks in Nova Scotia Power’s Solar Garden Pilot Rate Rider. It highlights work on cost-of-service methods, rate allocation, and pilot program evaluations.

John D. Wilson  Grid Strategies, LLC Page 10 Nova Scotia UARB Matter No. M10110, direct testimony on Nova Scotia Power’s Wreck Cove hydroelectric project on behalf of the Nova Scotia Consumer Advocate. Reasonableness of project and unreso...

AI summary John D. Wilson of Grid Strategies, LLC provided testimony in multiple regulatory proceedings regarding the reasonableness of capital expenditures, cost recovery, and alignment with integrated resource plans (IRP) for energy projects. Key issues included project justification, prudence of remedial costs, and compliance with regulatory standards in Nova Scotia and other jurisdictions.

John D. Wilson  Grid Strategies, LLC Page 11 Massachusetts DPU Docket No. 22-22, direct, surrebuttal and supplemental testimony on Eversource Energy’s 2022 Base Distribution Rate Case on behalf of the Cape Light Compact. Allocation of dis...

AI summary John D. Wilson of Grid Strategies, LLC provided testimony in multiple regulatory proceedings, including Nova Scotia UARB matters and Massachusetts DPU dockets, addressing rate cases, fuel adjustment mechanisms, distribution revenue allocation, and impacts of power delivery projects like Maritime Link on electrification and energy efficiency.

report provides EV forecasts for a low scenario, where sales in Nova Scotia lag the federal EV mandates, and a high scenario where EV sales in the country are distributed evenly across the provinces. NSPI’s 2024 EV forecast assumes that cu...

AI summary The document discusses NSPI's 2024 EV forecast, which assumes a low scenario for 2035 but notes that recent EV adoption has exceeded this. It highlights the need for rate designs and programmatic interventions to manage peak load from increased EV penetration and references the SGNS project's findings on EV impacts.

ast, Figure 26 39 NSPI’s response to Synapse IR-9 (c). 40 2024 Load Forecast, page 37. 41 Saxifrage, Barry. 2024. “How your province rates in the global electric car race.” Canada’s National Observer. April 8. Available at: https://www.nat...

AI summary The text discusses the need for NSPI to monitor EV adoption, update load forecasts, and consider load management strategies. It recommends examining the reasonableness of Dunsky’s low scenario and developing rate designs to reduce on-peak EV charging as EV penetration increases.

itor the coincidence of solar generation with month system peaks and make updates to coincidence factors as warranted. 44 2024 Load Forecast, page 90. 45 2024 Load Forecast, Appendix D, page 9. Synapse Energy Economics, Inc. Evidence Regar...

AI summary The document discusses the impact of solar-plus-battery systems on load forecasting, noting limited effects but acknowledging potential peak management benefits. It also addresses the contribution of new residential customers to load growth, projecting a modest increase by 2034.

out 428 GWh (7.0 percent) to the residential load by 2034, a modest decrease in the growth rate relative to last year’s forecast. 46 New customer load is calculated outside of the regression model. 47 Synapse has expressed concerns about t...

AI summary The document discusses NSPI's load forecast and the concerns raised by Synapse regarding the correlation between new housing and customer growth. The NSUARB has directed NSPI to re-evaluate the use of housing completions in its forecast model and consider additional demographic factors. NSPI maintains that housing completions remain the best proxy for customer growth.

means an increase in capacity requirements of about 434 MW (using a 20 percent planning reserve margin). This represents a significant increase and investment cost. Recommendations and Considerations We ask NSPI to investigate what can be...

AI summary The text discusses an increase in capacity requirements of 434 MW, emphasizing the need for investment and suggesting that NSPI explore time-of-use rates and other measures to mitigate peak load increases, particularly in the C&I sectors.

and Considerations We ask NSPI to investigate what can be done with time-of-use rates and other measures to mitigate the peak load increases for all these components, especially for the C&I sectors.

AI summary The text requests NSPI to investigate measures such as time-of-use rates to mitigate peak load increases, particularly for the commercial and industrial sectors.

tomer usage of secondary heating equipment. Finally, NSPI should model hybrid electric heating within its model instead of making a simplified adjustment based on E3’s hybrid scenario. 3. We recommend that NSPI model heat pump water heater...

AI summary The document outlines several recommendations for NSPI regarding load forecasting and load management strategies, including modeling hybrid electric heating, heat pump water heaters, EV adoption, solar generation coincidence factors, battery storage incentives, and validating customer growth proxies.

lly for peak management. 7. NSPI should validate the use of new home construction as a proxy for customer growth, addressing concerns about potential shortcomings of this proxy variable. 8. We ask that NSPI reassess its modeling approach f...

AI summary The document outlines various requests for NSPI to refine its load forecasting models, including validating proxies for customer growth, reassessing the impact of the pandemic on residential load, and exploring the effects of solar, DSM, and RTR on different sectors. It also suggests adjusting DSM adjustment factors if savings increase and investigating measures to mitigate peak load increases.

ervice customers? Are they implementing DSM measures to reduce load? Adding solar generation? Entering into RTR contracts? Might all this reduce their loads to some degree? (page 25) Synapse Energy Economics, Inc. Evidence Regarding Nova S...

AI summary The text presents a series of questions and requests directed at Nova Scotia Power Inc. (NSPI) regarding load forecasting, demand-side management (DSM) program savings, industrial electrification, real-time rates, and the impacts of renewable energy contracts (RTR) and technologies like heat pumps and thermal storage.

Page 7 of 25 2024 Load Forecast Report Rebuttal Evidence Non-Confidential 1 2.1.4 Recommendation 4 2 3 NSPI should carefully monitor EV adoption and update its forecast as needed. As 4 part of this update, NSPI should examine the reasonabl...

AI summary The 2024 Load Forecast Report recommends NSPI monitor EV adoption, assess Dunsky’s low EV scenario, and develop rate designs to manage peak EV load. NS Power agrees, citing Synapse Recommendation 16 for rate design details. It also agrees to monitor solar generation coincidence with system peaks.

idence of solar generation with month 24 system peaks and make updates to coincidence factors as warranted. 10 25 26 NS Power Response: 27 28 NS power agrees with this recommendation. 29 30 2.1.6 Recommendation 6 31 32 NSPI should continue...

AI summary The document discusses a recommendation for NSPI to investigate incentives for battery storage deployment, including rate design. NS Power agrees with this recommendation. Synapse's 2024 Load Forecast Report (M11689) is cited as evidence. The analysis focuses on aligning battery storage opportunities with system needs and cost-effectiveness.

, page 33. 20 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. 21 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. DATE FILED: September 6, 2024 Page 12 of 25 2024 Load Forecast Rep...

AI summary NS Power responds to Synapse's 2024 Load Forecast Report, addressing DSM program savings adjustments and peak load mitigation strategies. DSM savings are determined through NSUARB proceedings, with E1 developing new DSM programming. Time-of-use rates and other measures are proposed to manage peak load increases, particularly for C&I sectors.

29 NS Power notes Synapse's observations with respect to price signal-based interventions (time- 30 varying pricing, interruptibility rider, etc.) as tools to moderate and/or mitigate system peak 22 Synapse Evidence, 2024 Load Forecast Rep...

AI summary NS Power acknowledges Synapse's evidence on using price signal-based interventions like time-varying pricing and interruptibility riders to manage system peak demand. The discussion references Synapse's 2024 Load Forecast Report (M11689) and focuses on demand-side management strategies.

1 impacts due to heating and transportation electrification. As part of its 2024/25 Time-Varying 2 Pricing (TVP) Tariff Application, filed July 31, 2024 under M11822, NS Power has proposed to 3 establish an ongoing pricing innovation proce...

AI summary NS Power proposes an ongoing pricing innovation process for Time-Varying Pricing (TVP) tariffs under M11822, including stakeholder collaboration and analysis of demand response programs. Recommendation 17 urges NSPI to analyze portfolio ELCC values for demand response, with NS Power referencing its 10-Year System Outlook (M11764) and collaboration with E1.

ers (end-use 26 saturation of around 2.6 percent) on the associated time-of-day rate with around 200 new 27 customers every year. The low uptake numbers are unlikely to change in the near term, and given 28 the low overall saturation, the...

AI summary The text discusses low adoption rates of time-of-day rates and heat pump water heaters in Nova Scotia, noting minimal saturation (2.6%) and limited impact on overall energy use. NS Power argues these end uses do not warrant further investigation due to their small scale, citing reports (M11621, M11689) on load forecasts and smart grid initiatives.

, page 33. 28 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. 29 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. DATE FILED: September 6, 2024 Page 16 of 25 2024 Load Forecast Rep...

AI summary NS Power responds to Synapse's 2024 Load Forecast Report, acknowledging sensitivity analyses for peak load projections and referencing ongoing initiatives like SGNS, IRP, and TVP. The Consumer Advocate recommends refining residential heating intensity adjustments using AMI data for better accuracy.

on previous occasions. In the Board decision letter in matter M11108, the Board provided NS Power with direction on enhancements for continuous improvement in the development of the load forecast and 1 Based on Table A1 in each annual repo...

AI summary The Board directed NS Power to improve load forecasting and stakeholder engagement, with specific recommendations including incorporating hydrogen production scenarios, IRP data, and evaluating model assumptions. NS Power conducted a virtual consultation with stakeholders and included materials in Appendix E of the Report.

sted EV forecast appropriate and directs NS Power to continue following the modified approach until the lag in EV sales in Nova Scotia disappears. -4- NS Power compared the previous two forecasts for large customer growth in the Large Gene...

AI summary NS Power adjusted its EV and large customer load forecasts based on the Board’s 2023 Load Forecast decision, improving accuracy by aligning with actual year-over-year changes. Price elasticity analysis from the TVP Pilot showed discrepancies in TOU and CPP rates compared to load forecasts, though differences were deemed insignificant.

the demands from its residential customers. The Board directs NS Power to continue to revisit the unexplained variance and report on its findings in the 2025 Load Forecast Report. Intervenor Comments As in previous Load Forecast Reports, i...

AI summary The Board directs NS Power to investigate unexplained variance in residential load forecasts and report findings in the 2025 Load Forecast Report. Intervenors commend NS Power's efforts but urge continued improvement, while the Consumer Advocate recommends using AMI data, adjusting TVP peak reduction assumptions, and revising EV charging forecasts.

Forecast Report. Synapse Synapse noted NS Power’s continued improvement to the Load Forecast Report. However, Synapse also remarked on several aspects, suggesting revisions. These included: • modeling heat-pump-based hot water heating, exa...

AI summary Synapse recommends revisions to NS Power’s Load Forecast Report, emphasizing improved modeling of heat pumps, solar impacts, EV adoption, DSM adjustments, and peak forecasting methodology. Key areas include hybrid heating scenarios, electrification effects, and validating new home construction as a proxy for customer growth.

NS Power agreed to monitor several of the model’s inputs, including EV adoption, solar generation, battery storage deployment and bi-directional EV charging, and the associated load impacts for each. NS Power agreed to review pricing innov...

AI summary NS Power agreed to monitor EV adoption, solar generation, battery storage, and bi-directional EV charging impacts. It will review pricing innovations, update DSM Program savings, and analyze demand response capacity value. NS Power disagreed with removing TVP benefits from peak forecasts and adding certain weather metrics to the SAE model, but agreed to study temperature and cloud cover trends.

Document: 313458 Date Filed: 05/28/24 UARB Page 5 1 Request IR-17: 2 Page 52 of the Report discusses the price impact to sales through imposed price elasticities and 3 explains that the SAE models use a price elasticity of -0.15. In matter...

AI summary The UARB requests clarification from NS Power on three issues: (1) why different price elasticities were not applied to rate classes despite evidence from Appendix C; (2) discrepancies in population growth forecasts between the 2023 Load Forecast Report and the Conference Board of Canada; and (3) the basis for the structural index in the Report. These questions challenge NS Power's modeling approaches and data reconciliation.

provide peak load reductions in kW per vehicle 34 for each vehicle category that NSPI expect and assumed through managed 35 charging programs or time of use rates.

AI summary The text requests NSPI to provide peak load reductions in kW per vehicle category, based on their expectations from managed charging programs or time-of-use rates.

Date Filed: May 29, 2024 Synapse (NSPI) Page 8 of 24 1 e. The SGNS project found average evening peak reductions of 0.24 kW/vehicle from one 2 EV pilot program participant cohort and 0.65 kW/vehicle from another cohort. NSPI states 3 that...

AI summary The text includes questions to NSPI about EV pilot program impacts on peak load, managed charging strategies, time-of-use tariffs, and assumptions regarding EV charging management percentages. It seeks clarification on SGNS project findings, peak load impact estimates, and the relevance of these findings to winter peak and different vehicle types.

ntial model more robust, considering the following: 24 o Given the continued population growth in Nova Scotia and ongoing housing 25 shortage, re-evaluate the use of housing completions for the near-term. 26 o Consider incorporating househ...

AI summary The text requests re-evaluation of housing completions, demographic factors, and economic data in energy models, along with updates to EV adoption rates and infrastructure communication. It also seeks clarification on price elasticity assumptions and data sources for electricity pricing models.

literature for a more recent relevant study than the 2006 National Energy Research Lab 15 study provided in response to IR-15 in 2023. 16 c. Please provide the technical definitions of the daily price elasticity and inter-period 17 substit...

AI summary The text includes requests (IR-15, IR-18) seeking technical definitions, data sources, and explanations related to price elasticity and Demand Side Management (DSM) in energy forecasting, emphasizing the need for updated studies and detailed DSM scenarios.

Date Filed: May 29, 2024 Synapse (NSPI) Page 13 of 24 1 f. Has the estimated impact of ongoing changes associated with COVID-19 changed since 2 the previous load forecast? If so, please explain in detail. 3 g. Please provide the inputs and...

AI summary The document includes regulatory requests for detailed explanations on load forecast assumptions, home size growth, EV charging behavior impacts, and commercial sector load effects from COVID-19. Questions focus on methodology, data inputs, and regulatory implications for energy efficiency and rate design.

Date Filed: May 29, 2024 Synapse (NSPI) Page 14 of 24 1 b. Please identify and quantify in detail the specific components in the forecast model that 2 are causing the increase starting about 2025 as shown in Figure 45. 3 4 5 6 7 Request IR...

AI summary The document contains regulatory requests (IR-24 to IR-26) seeking detailed explanations for forecast discrepancies in energy demand, including EV load impacts, DSM program effects, and solar generation growth. Requests focus on quantifying changes in model variables (XHeat, XCool, XOther) and differences between current and previous forecasts for General Service, Large General Service, and Small Industrial categories.

Date Filed: May 29, 2024 Synapse (NSPI) Page 17 of 24 1 j. How did the 2022 Evergreen IRP estimate peak demand reductions. How many 2 customers and which end uses or technologies does the IRP assume for 3 estimating the peak load reduction...

AI summary The text contains a series of requests related to demand-side management (DSM) programs, peak demand research, and data analysis, including requests for reports, evaluations, and detailed explanations of figures and calculations.

Date Filed: May 29, 2024 Synapse (NSPI) Page 19 of 24 1 i. Please note any changes in the model specification relative to the 2023 forecast 2 residential model, and please further quantify the impact of any such changes in 3 specification...

AI summary The document contains requests for detailed information and data related to residential and general service models, including statistical parameters, spreadsheet formats, and calculations for various variables and programs such as PV, EV, and DSM. The requests are part of a regulatory proceeding.

FIDENTIAL 1 In the same Information Request response, NS Power shared the E3 RESHAPE COP 2 Curves which characterized heat pump COP performance between -25oC and 10oC. 3 4 ii) With the growing prevalence of cold climate heat pumps and the...

AI summary NS Power shared E3 RESHAPE COP curves for heat pump performance in cold climates. EfficiencyOne (E1) questions whether a -15°C lockout for heat pumps should be adopted in load forecasts and seeks data on managed EV charging percentages and enrollment numbers in NS Power's 2024 Load Forecast Report.

dentifying the sources of 40 data for the relevant factors, including but not limited to the number of customers 41 connected, panel sizes, and special loads such as EVs. 42 Date Filed: May 29, 2024 CA (NS Power) Page 5 of 6 1 (d) Are tran...

AI summary The text outlines regulatory inquiries into NSP's data practices for transformer sizing, time-varying pricing (TVP) impact assessments, and AMI technology implementation timelines. Requests focus on quantifying TVP's system peak reduction, forecasting AMI benefits, and analyzing peak demand patterns from winter 2023-2024.

sted EV forecast appropriate and directs NS Power to continue following the modified approach until the lag in EV sales in Nova Scotia disappears. -4- NS Power compared the previous two forecasts for large customer growth in the Large Gene...

AI summary The Board directed NS Power to adjust its load forecast methodology for large customers, acknowledging improved accuracy after correcting overestimations. NS Power also analyzed price elasticity differences between Time of Use and Critical Peak Pricing rates, finding minimal impact on forecasted sales.

NS Power agreed to monitor several of the model’s inputs, including EV adoption, solar generation, battery storage deployment and bi-directional EV charging, and the associated load impacts for each. NS Power agreed to review pricing innov...

AI summary NS Power agreed to monitor EV adoption, solar generation, and load impacts but disagreed with the CA's recommendation to remove TVP benefits from peak forecasts. It contested EV peak value assumptions and weather factor inclusions, though it agreed to analyze temperature and cloud cover trends.

he model. Board Findings As in previous Board decisions for the Load Forecast Reports, the Board encourages NS Power to pursue additional review with the aim of improving the forecast, specifically: • Evaluate the input variables in the re...

AI summary The Board directs NS Power to enhance its residential load forecast model by evaluating input variables, aligning economic data with Canadian banks' forecasts, revisiting EV adoption rates, and testing TVP elasticity. It also urges investigation into CMHC housing data limitations affecting 10-Year Forecast Classes.