Topic:"Grid Modernization" in M10569

urrently in the pilot stage, 12 Based on the NRCan 2009 Canadian Vehicle Survey Summary Report, https://oee.nrcan.gc.ca/publications/statistics/cvs/2009/appendix-1.cfm?graph=11 DATE: April 29, 2022 Page 43 of 98 REDACTED (CONFIDENTIAL INFO...

AI summary The document discusses the impact of electric vehicles (EVs) on Nova Scotia's grid, noting that data is being collected through the Smart Grid Nova Scotia (SGNS) Project. The project includes the installation of EV smart chargers and vehicle-to-grid smart chargers to study the effects of EV charging and utility-managed charging events.

INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 Figure 62: Commercial End-Use Peak Shares 2 3 4 The trend in the Commercial classes shows that the heating component of the peak is 5 expected to increase significantly over the for...

AI summary The 2022 Load Forecast Report discusses trends in commercial end-use peak demand, noting an increase in heating demand due to electrification. NS Power uses interval data and advanced metering infrastructure to refine peak demand modeling and improve forecasting accuracy.

Page 93 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 The bottom-up approach, which relies on class-level load research, captures customer 2 behavior, at peak, more realistically. For instance, ther...

AI summary The 2022 Load Forecast Report discusses the use of a bottom-up approach for load research, highlighting its ability to capture customer behavior during peak times. It also mentions the potential of using AMI smart meter data to assess the impact of the pandemic on residential consumption and improve future load forecasts.

to NSUARB IR-3 Attachment 1. 29 30 Date Filed: July 8, 2022 NSPI (CA) IR-2 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer...

AI summary NSPI responds to NSUARB's IR-3 request regarding geographic load data, stating billing data (1-2 months of consumption) is used for forecasting. Load flows are not evaluated for forecasting, and AMI data integration is under review for granular analysis. No geographic disaggregation by transmission zones is currently available.

29 coincident peak time of a weekday evening in January at hour ending 1800, so the 30 difference between the E3 models would be 0.6 kW/vehicle. Not all of the charging will Date Filed: July 8, 2022 NSPI (CA) IR-4 Page 1 of 2 REDACTED (CON...

AI summary NSPI acknowledges challenges in managing EV charging demand during peak hours, noting a 0.6 kW/vehicle difference in peak load scenarios. Temperature impacts EV efficiency and heating/cooling demands, though traffic data analysis for system peaks remains unreviewed. Only 70% of EVs are managed off-peak, with 30% remaining unmanaged.

and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 DailyEnergy = Constant + b1×HDD13 + b2×HDD0 + b3×Lag1HDD13 + 2 b4×Lag2HDD13 + b5×JanHDD13 + b6×FebH...

AI summary NSPI explains its load forecast model, including the DailyEnergy formula incorporating temperature variables and weather normalization factors. The model allocates weather impact to residential (77%), commercial (15%), and municipal (3%) sectors. The normalization factor increased from 20 MW/°C (pre-2016) to 25 MW/°C post-2016 analysis, with a revised figure provided for 2019.

n billed sales and NSR. The loss Date Filed: July 8, 2022 NSPI (CA) IR-15 Page 1 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer A...

AI summary The document discusses the use of load research data to estimate peak losses and allocate system peak to different classes, noting a 10% precision target and challenges with sample degradation due to legacy meters. It also mentions the preference for using AMI data for more accurate estimates.

1 Request IR-2: 2 3 (a) Please describe all electrification research/pilots/programs NS Power is currently 4 planning and/or carrying out. 5 6 (b) Please provide all applicable project schedules, studies and/or reports that have been 7 dev...

AI summary NS Power outlines electrification initiatives, including residential heating solutions with heat pumps and commercial HVAC electrification programs. The response highlights contractor networks, on-bill financing, and a four-year Smart Grid Nova Scotia pilot (M10176) focused on advanced metering infrastructure and building decarbonization studies.

fication rebates and 27 funding programs to offset capital investment. 28 29 (iii) Smart Grid Nova Scotia (M10176): A four-year pilot program focused on studying 30 the effects posed by distributed energy resource (DER) penetration on the...

AI summary The text references the Smart Grid Nova Scotia pilot program (M10176), which studies the impact of distributed energy resources (DER) on the electrical grid, and NSPI's 10-Year Energy and Demand Forecast (NSUARB M10569). These initiatives address grid modernization and energy forecasting, supporting DER integration and long-term planning.

ergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-26: 2 3 With reference to Section 5.0 Residential Sector, page 60 of 98, the application ident...

AI summary NSPI responded to two information requests from the NSUARB regarding the 2022 Load Forecast Report. The first addressed EV penetration rates in the residential sector, noting that the forecast assumes provincial rates without considering current vehicle shortages. The second clarified that billing data used in the analysis was from the CIS system in 2018, before AMI meter installation.

is analysis gathered from the AMI meters in Nova Scotia? 7 8 Response IR-27: 9 10 No, the data was gathered from the CIS billing system in 2018, prior to the installation of AMI 11 meters. Date Filed: July 8, 2022 NSPI (NSUARB) IR-27 Page...

AI summary The response clarifies that data was collected from the CIS billing system prior to AMI meter installation and provides information on house size forecasts, referencing data from Nova Scotia and New England. The forecast assumes slower growth in house size in Nova Scotia compared to New England due to multi-family housing trends.

(SBA) IR-7 Page 1 of 1 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Small Business Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-8: 2 3 Please refer to the Filing, page 7...

AI summary NSPI has not identified a third-party aggregator to perform managed charging responsibilities. Instead, NS Power is developing this capability as part of its Smart Grid Nova Scotia program, working with multiple vendors to determine the most effective managed charging approach.

to NSUARB IR-3 Attachment 1. 29 30 Date Filed: July 8, 2022 NSPI (CA) IR-2 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer...

AI summary NSPI responds to NSUARB's request regarding geographic load data, stating that load flows are not used in forecasting, billing data introduces uncertainty if disaggregated, and AMI data integration is under review for granular analysis.

n billed sales and NSR. The loss Date Filed: July 8, 2022 NSPI (CA) IR-15 Page 1 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer A...

AI summary The text discusses the use of load research data to estimate peak losses and allocate system peak to different classes, noting that the methodology has a 10% precision target. It also highlights the degradation of sample quality since 2018 due to legacy meters and the potential for AMI data to improve accuracy.

evaluated load flows used 24 for transmission planning as possible inputs, and that it is reviewing how to integrate AMI 25 data in order to provide more granular analysis. 16 NS Power has hourly substation load data 26 from the areas repr...

AI summary NS Power is evaluating load flows for transmission planning and integrating AMI data for granular analysis. John D. Wilson recommended focusing on peak load and using multi-hour average temperatures instead of single-hour measures, along with considering wind speed and cloud cover.

able traffic data associated with peak load events in recent years. This qualitative 19 indication of vehicle use during peak load events could inform assumptions regarding EV 20 charging demand during peak load events. 21 Fourth, it is un...

AI summary NS Power's Load Research Sample (LRS) model has a degraded dataset prior to 2017 and was reliable only from 2018. Line loss estimates remain unchanged since 2013, and AMI implementation rates are 78% for industrial, 84% for commercial, and 89% for domestic customers. Heat pump water heater forecasts have not been updated since 2020, raising concerns about future demand.

John D. Wilson • Resource Insight, Incorporated Page 7 2019 Georgia PSC Docket Nos. 42310 and 42311, direct testimony with Bryan A. Jacob in Georgia Power’s 2019 integrated resource plan and demand side management plan on behalf of Souther...

AI summary The text outlines testimony provided by John D. Wilson and Paul Chernick in various regulatory proceedings in Georgia and Nova Scotia. These testimonies cover topics such as integrated resource planning, demand side management, capital expenditure plans, and infrastructure projects, with a focus on cost classification, decommissioning, and project justification.

testimony with Paul Chernick in Nova Scotia Power’s application for the Advanced Distribution Management System Upgrade on behalf of the Nova Scotia Consumer Advocate. Need for the ADMS and integration with the Distributed Energy Resources...

AI summary Paul Chernick provided testimony in multiple regulatory proceedings, including Nova Scotia Power’s ADMS Upgrade, 2020 Load Forecast, and San Diego Gas & Electric’s EV Charging Program. His testimony focused on ensuring equitable and effective program implementation, budget controls, and evaluation processes.

as supplemental heat, and gas heating 11 systems as supplemental heat, would have a different impact on load and would likely have a 12 different combination of system investment requirements. 13 14 Given that the 2022 Load Forecast indica...

AI summary The text discusses the impact of heating technologies on load forecasting and grid flexibility, emphasizing the need for peak load management in a net-zero grid. It references the 2022 Load Forecast and the RAP paper 'Heating Without the Hot Air,' which highlights principles for efficient and flexible heat decarbonization.

2 Page 5 of 25 2022 Load Forecast Report Rebuttal NON-CONFIDENTIAL 1 2.0 RESPONSE 2 3 As outlined below, the evidence from Synapse, the CA, and E1, as well as the SBA’s submission 4 are primarily focused on the following issues: 5 6 1. Fur...

AI summary The 2022 Load Forecast Report rebuttal highlights three key areas: electrification's impact on energy/peak demand, new technologies (smart grid, time-variable rates), and weather normalization improvements. NS Power acknowledges the need for further investigation and will incorporate data from initiatives like the Integrated Resource Plan and Smart Grid Nova Scotia into future forecasts.

red through various ongoing initiatives (the Integrated Resource Plan (IRP) 26 Action Plan and Smart Grid Nova Scotia (SGNS) in particular), they will be incorporated in future 27 forecasts. 28 DATE FILED: September 26, 2022 Page 6 of 25 2...

AI summary The document references the integration of the Integrated Resource Plan (IRP) Action Plan and Smart Grid Nova Scotia (SGNS) into future forecasts. It is part of the 2022 Load Forecast Report Rebuttal, filed on September 26, 2022, as page 6 of 25.

FILED: September 26, 2022 Page 18 of 25 2022 Load Forecast Report Rebuttal NON-CONFIDENTIAL 1 3.2.5 Recommendation 5: 2 3 “NS Power should update those same load forecast models to 4 reflect the findings from Itron with respect to real-wor...

AI summary NS Power agrees to update load forecast models with Itron's findings on heat pump impacts and policy goals for electrification. It acknowledges challenges in heat pump water heater adoption due to cost and cooling effects, and commits to quarterly progress reports on the line loss determination model as per the Board's directive.

ear actual 2 Based on Table A2 in 2022 and 2021 Load Forecast reports and in Table A3 in each annual report from 2015 to 2020 Document: 298717 -3- However, the significant increase in Load for 2022 is mainly attributed to the application o...

AI summary NS Power attributes a 2022 load increase to E3's estimated peak model, planning to validate it with AMI data. Intervenors praised forecast improvements but raised concerns about heat pump adoption, EV growth, new demand-reducing technologies, and peak management via Smart Grid Nova Scotia (SGNS) project outcomes.

mpacts on peak. Synapse asked that NS Power review its peak forecasting methodology and provide a peak sensitivity analysis as well as the assumptions and calculations used. NS Power Reply Submission In its Reply, NS Power addressed the co...

AI summary Synapse requested NS Power to review its peak forecasting methodology and provide sensitivity analyses. NS Power agreed to incorporate multi-hour weather data, refine electrification impact assessments, and evaluate hybrid demand response scenarios while integrating findings from recent studies and projects.

hicles available for sale in Nova 27 Scotia. If not, please explain. 28 29 Request IR-27: 30 With reference to Section 5.0 Residential Sector, page 61 of 98, the application states, “Analysis 31 of billing data showed that new single-famil...

AI summary Request IR-27 questions whether billing data used in the analysis comes from AMI meters in Nova Scotia, referencing residential sector energy usage statistics (16,000 kWh/year for single-family homes, 4,860 kWh/year for multi-unit homes).

ely 16,000 kWh per year on 32 average, while multi-unit homes use 4,860 kWh per year on average”. Is this billing data used in 33 this analysis gathered from the AMI meters in Nova Scotia? 34

AI summary The text questions whether billing data (averaging 16,000 kWh/year for single-unit homes and 4,860 kWh/year for multi-unit homes) used in the analysis originates from Nova Scotia's AMI meters. The focus is on data source validation for energy usage estimates.

Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 10 of 16 1 h. Please provide the data and calculations behind the peak share values in Figures 61 and 2 62 including the actual load values as well as the percentages. Please...

AI summary The document contains regulatory requests for data and explanations related to peak demand analysis, AMI coverage, DSM impacts, and sensitivity analysis variables. Requests include clarifying peak share calculations, AMI coverage levels, loss levels, DSM differences, and the rationale for selected sensitivity analysis variables.

Blackburn Law July 29, 2022 VIA EMAIL Ms. Crystal Henwood Regulatory Affairs Officer/Clerk Nova Scotia Utility and Review Board 1601 Lower Water Street, 3rd Floor Halifax NS B3J 3S3 Dear Ms. Henwood: Re: M10569 - Nova Scotia Power Inc. ("N...

AI summary The Small Business Advocate (SBA) acknowledges improvements in NSPI's 2022 Load Forecast Report, including updated peak temperature assumptions and EV forecasts, but notes that electrification changes may inaccurately signal system growth. The SBA also questions how data from the Smart Grid Nova Scotia Project is incorporated into the forecast.

ear actual 2 Based on Table A2 in 2022 and 2021 Load Forecast reports and in Table A3 in each annual report from 2015 to 2020 Document: 298717 -3- However, the significant increase in Load for 2022 is mainly attributed to the application o...

AI summary NS Power attributes the 2022 load increase to E3's estimated peak model, planning to validate it using AMI data. Intervenors praised forecast improvements but raised concerns about heat pump adoption, EV forecasts, new technologies, and SGNS project outcomes for peak demand management.

EV forecast, investigation of new technologies to reduce energy and peak demand, and the management of peak through the Smart Grid Nova Scotia (SGNS) project results and direct control water heaters. The CA filed evidence prepared by John...

AI summary The document discusses John Wilson's recommendations for NS Power to improve climate change scenario analysis, enhance weather station integration, refine peak load forecasting models, and address modeling errors in residential energy models. Wilson also suggests adjustments to heat pump assumptions and EV usage during peak periods, alongside completing the line loss determination model with quarterly reporting.

ing storm closures at peak periods. Lastly, Mr. Wilson requested that NS Power complete the line loss determination model and report on its progress on a quarterly basis until the project is complete. The SBA raised concerns about the accu...

AI summary Concerns were raised about the accuracy of EV and space heating forecasts, the incorporation of SGNS project data, and the adequacy of demand response (DR) capacity. EOne recommended updating heat pump models and exploring electrification scenarios with electric thermal storage (ETS). Mr. Wilson requested NS Power to complete a line loss determination model and report progress quarterly.