Topic:"Residential Programs" in M12349

ce Data ................................................................................................................. 51 21 4.5.1 Demand Side Management .....................................................................................

AI summary The text outlines sections of a 2025 Load Forecast Report, including demand-side management, renewable energy integration, and sector-specific analyses for residential, commercial, and industrial/municipal sectors. The document is redacted, with confidential information removed.

............................................. 74 16 Figure 58: Historical and Forecast Annual NSR ........................................................................ 75 17 Figure 59: Forecast Components ..................................

AI summary The text lists figures related to energy demand forecasting, demand response programs, peak load analysis, and the impact of electric vehicles. Topics include system reliability, load management, and integration of renewable energy sources through advanced metering infrastructure.

94 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2025 Load Forecast Report Redacted 1 4.3 Economic Information 2 3 Economic and other provincial statistics used in the load forecast are from the Conference Board 4 of Canada’s 20-year forecas...

AI summary The 2025 Load Forecast Report uses economic data from the Conference Board of Canada's 20-year forecast, including housing completions, to predict residential customer growth. The NSUARB directed a re-evaluation of housing completions due to population growth targets and housing initiatives like the Housing Accelerator.

MOVED) 2025 Load Forecast Report Redacted 1 Figure 14: Yearly Change in Residential Customers 2 3 4 NS Power will continue to monitor any government initiatives that may increase housing supply. 5 In a January 2025 update, 10 the Halifax R...

AI summary The 2025 Load Forecast Report discusses residential customer growth and housing initiatives, including the Halifax Regional Municipality’s Housing Accelerator Fund (HAF), which aims to increase housing development by 2,600 units over three years. The report also mentions the use of population and customer count data to estimate household size in the SAE model.

able that was added in 2020 continues to be used for the years 2020-2024, but 22 has been removed from the forecast years. The variable helps to explain changes in consumption 23 patterns over the 2020-2024 time period, but it is expected...

AI summary The 2025 Load Forecast Report indicates that weather-adjusted sales in 2024 were close to forecast, but warm weather reduced sales by 104 GWh. Load is expected to decline from 2026 to 2033 due to migration to the RTR market and solar adoption, but will increase afterward due to EV load. DSM and efficiency improvements are expected to reduce sales over time.

1 Figure 46 provides a breakdown of the components of the Residential forecast at the system level. 2 Please refer to Appendix B for tables with a detailed breakdown of the changes from 2025 to 3 2035. 4 5 Figure 46: Residential Sales Comp...

AI summary Figure 46 outlines the components of residential electricity sales forecasts from 2025 to 2032, showing the impact of factors like new customer growth, hybrid models, solar energy, EV adoption, RTR, and DSM on total residential sales.

Variable Coefficient StdErr T-Stat P-Value MStructRes.WtXHeat 0.926 0.018 51.423 0.00% MStructRes.WtXCool 1.147 0.185 6.205 0.00% MStructRes.WtXOther 0.925 0.032 29.357 0.00% MSales.AvgEESavingsProfiled -0.414 0.161 -2.577 1.14% MBin.Jan 64...

AI summary The text presents a statistical model summary with coefficients, standard errors, t-statistics, and p-values for various variables in a residential load forecasting model. The table includes variables such as heating, cooling, other usage, energy efficiency savings, and monthly bins, as well as a variable related to the Covid-2020 stepped update.

OVED) 2025 Load Forecast Report Appendix B Page 7 of 34 Residential SAE Model Fit Residential Model 2025-2035 Reconciliation The following tables provide details reflecting the changes between 2025 and 2035 forecast years. Some of the numb...

AI summary The Residential Load – Post Regression table compares residential energy usage between 2025 and 2035, showing changes in average use, new EVs, solar, RTR, hybrid, and DSM. Discrepancies exist due to conversion from monthly to annual data. The change in load factors is also outlined.

8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2025 Load Forecast Report Appendix E Page 9 of 19 Behind the Meter Solar • Small scale solar uptake continues to be strong: as of 2024 approximately 97 MW of solar generation has been installed...

AI summary The document discusses the growth of behind-the-meter solar installations in Nova Scotia, noting increased uptake and legislative changes leading to a higher long-term forecast. It also addresses the Renewable to Retail (RTR) program, with updated forecasts for sales and uncertainty around its impact.

1 2025 Load Forecast Report (NSEB M12349) NSPI Responses to NSEB Information Requests NON-CONFIDENTIAL 1 Request IR-3: 2 3 Page 20 of the application, Weather Data, explains that the heating degree days (HDD) trend 4 is reduced over time t...

AI summary NSPI responds to NSEB's IR-3 and IR-4 requests regarding the 2025 Load Forecast Report. Adjustments to heating degree days (HDD) trends are made from the forecast's start to avoid zero HDD, with unadjusted projections reaching zero HDD in 2257. Residential customer growth is tied to housing completions, expected to decline as population growth slows post-2024 peak.

2025 Load Forecast Report (NSEB M12349) NSPI Responses to Solar Nova Scotia Information Requests NON-CONFIDENTIAL 1 Request IR-3: 2 3 The 2025 Load Forecast Report anticipates 930 MW of behind-the-meter solar generation 4 by 2035 (s. 4.4.4...

AI summary NSPI's response to Solar Nova Scotia's IR-3 request details assumptions in the 2025 Load Forecast Report: 74% residential and 26% non-residential behind-the-meter solar by 2035. Current incentives are outlined in the report, with no assumptions about future changes. Behind-the-meter solar contributes to the Renewable Electricity Standard (RES), though the specific percentage is unspecified.

1 Request IR-7: 2 3 COVID-19 Variable (Section 5.0, p. 57; Section 6.0, p. 63; Appendix B, p. 5; Attachment 05 4 EO) 5 6 (a) Please provide an explanation for the statement about the use of the COVID-19 quasi- 7 binary variable in the resi...

AI summary Request IR-7 seeks clarification on NSPI's use of the COVID-19 quasi-binary variable in residential load forecasting models. Questions focus on why the variable becomes unnecessary post-2024, how input values (1, 0.5, 0.13, 0.01) were determined, differences from prior models, and discrepancies between General rate class and residential model historical data capture.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2025 Load Forecast Report Synapse IR-17 Attachment 1 Page 3 of 3 Residential Uptake 50% 25% 10% 5% Battery Peak Impact - No Control (MW) 0 0 0 0 Battery Peak Impact - Optimal DR Control (MW) (1,4...

AI summary The document discusses the 2025 Load Forecast Report and includes responses from NSPI to Synapse Information Requests related to the residential sector, specifically referencing figures and attachments for data and calculations.

reases in heating and cooling are driven by growing use of heat pumps, which contributes to a 33.3 percent increase in the XHeat load intensities and a 25.2 percent increase in XCool load intensities. In total energy terms, Figure 47 of th...

AI summary Heat pump adoption is driving significant increases in residential heating and cooling loads in Nova Scotia, with projections showing 685 GWh additional heating and 102 GWh cooling demand by 2035. NSPI forecasts 80% heat pump saturation by 2035, supported by financial incentives, while noting displacement of electric baseboard heating and fossil fuel use.

tize this effort as it works to refine its modeling of electric heating impacts. 25 2025 LFR Attachment 03 EO – Commercial General Intensities. “Efficiency” tab. 26 2025 Load Forecast, page 90. Synapse Energy Economics, Inc. Evidence Regar...

AI summary Synapse Energy Economics Inc. analyzes Nova Scotia Power’s 2025 load forecast, highlighting assumptions about electric water heater adoption, projected increases in XOther due to water heating usage, and the exclusion of heat pump efficiency improvements despite rebate programs. The analysis emphasizes the need for monitoring these assumptions and their impacts on residential energy demand.

the peak contribution of residential customers based on other comparators (i.e., household income or size, postal code, etc)? If no, why not? If yes, please describe the analysis and results. Thank you for the opportunity to participate in...

AI summary The text presents a question about analyzing residential customer peak contributions based on income, size, or postal code, followed by a brief acknowledgment from Roby Douglas, Chair of the SNS Industry Committee, expressing gratitude for participation in the proceeding.

5: 33 Page 58 of the application discusses how residential sales expectations have been estimated 34 using downward revised population growth estimates of 21,000 and new housing of 58,000 units.

AI summary Page 58 of the application discusses residential sales expectations estimated using revised population growth projections (21,000) and new housing unit estimates (58,000). The analysis focuses on how these demographic and housing data inputs inform residential demand forecasting.

Date Filed: 07/28/2025 Synapse (NSPI) Page 7 of 12 1 Request IR-24: 2 Appendix B: Residential Model 3 a. Please provide in electronic spreadsheet format the data and the statistical model 4 parameters and the full data and results used to...

AI summary The text outlines requests for detailed data and model parameters related to residential and peak forecasts, including factors affecting heat pump usage, model specification changes, and customer heating system distributions. It emphasizes transparency in statistical models and forecast methodologies for regulatory review.

ii. Number of customers for HP, Hybrid, Resistance, Wood, and Fossil Fuel heating 27 systems as indicated in Figure 17. 28 iii. Number of customers using heat pumps as the sole technology 29 iv. Number of customers using heat pumps as prim...

AI summary The text requests data on residential heating technology adoption (heat pumps, oil, gas, etc.) and new customer projections from 2024-2050. It also seeks details on the Province’s 'Path to 2030' hybrid scenario study, including draft materials and scope of work.

M12349 – SBA IRs – July 28, 2025 Page 2 of 4 1 a) Please include the assumed effective dates and associated impacts, if available. 2 3 Request IR-5: 4 Refer to Report, Section 4.4.4, Solar Generation (PV), page 44 of 94 and respond to the...

AI summary The document outlines three information requests (IR-5, IR-6, IR-7) related to net-metering customer statistics, behind-the-meter solar installation projections, and price elasticity data for small businesses. Requests focus on customer distribution, incentive considerations, and program participation metrics, with references to NS Power's reports and forecasting methods.