N-12024 Load Forecast Report + Appendices - Redacted
8 passages
2024 Heating 2023 Heating Change Year Intensity Intensity (Percentage) (kWh/house) (kWh/house) 2024 2,066 1,511 +37 2025 2,271 1,639 +39 2026 2,454 1,770 +39 2027 2,636 1,899 +39 2028 2,814 2,026 +39 2029 2,973 2,140 +39 2030 3,128 2,250 +...
AI summary The text provides forecasts for heating intensity from 2024 to 2034, showing a steady increase in kWh per house. It also discusses NS Power's expectations regarding customer adoption of heat pumps and electric water heaters, with a joint demand response program involving E1 to manage water heater usage for system benefits.
) 2024 Load Forecast Report REDACTED 1 Figure 27: PV Impact to Energy (cumulative) 2 Total New Year Load (GWh) Peak (MW) Installs 2024 3,019 -33 0 2025 6,361 -70 0 2026 10,062 -111 0 2027 14,163 -158 0 2028 18,708 -209 0 2029 23,746 -267 0...
AI summary The 2024 Load Forecast Report indicates a cumulative impact of photovoltaic (PV) installations on energy load and peak demand, with negative values reflecting reduced load. The report notes that distributed solar and battery storage combinations are not assumed to be significant due to the high cost of home batteries, ranging from $15,000 to $20,000.
and EV forecasts. 25 DATE: April 30, 2024 Page 46 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 29: Residential End-Use Intensities 2 3 4 The intensity trends are similar to those in prior f...
AI summary The 2024 Load Forecast Report discusses residential and commercial end-use intensities, noting trends such as increasing use of heat pumps, decreasing electric baseboard heating, and changes in cooling intensity. The report also highlights the impact of EV sales and PV generation on residential energy use.
2022 2021 20.4 2.6% 9,531 482,771 4,601 4,661 59.5 1.3% 2023 2022 48.9 6.4% 9,641 488,654 4,711 4,822 110.6 2.3% 2024 2023 15.4 1.8% 10,064 495,055 4,982 4,986 3.8 0.1% 6 7 The adjusted heating intensities are expected to result in a small...
AI summary The text discusses forecast adjustments for residential energy consumption, including the impact of the COVID-19 variable and changes in load due to factors like RTR market migration, EV forecasts, and behind-the-meter solar. The adjusted heating intensities are expected to reduce unexplained variance in future years.
sales, while DSM and naturally occurring efficiency improvements will decrease sales over 32 Mean absolute deviation. 33 Mean absolute percentage error. DATE: April 30, 2024 Page 59 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 L...
AI summary The 2024 Load Forecast Report discusses residential electricity sales trends, predicting a 0.2% annual increase in sales from 2024 to 2034. It highlights population growth, new housing construction, and efficiency improvements impacting demand. Single-family homes are expected to use more electricity than multi-unit residences.
REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 41: Residential Sales Components by Year 2 Year Regression New Hybrid Solar EV RTR DSM Total Total Res. DSM Model Cust. Adjust. Impact Impact Sales Adj...
AI summary The document presents a section of the 2024 Load Forecast Report, focusing on residential sales components by year, including data on regression model outputs, customer growth, hybrid adjustments, solar and EV impacts, retail tariff rates, and demand-side management (DSM) adjustments.
(698) (310) Change 9.0% 7.0% 6.0% -8.0% -1.4% -3.4% -6.9% 2.3% to load Res Sales = Existing Customer + New Customer + EV + Solar + RTR + Hybrid + DSM Existing customer load is calculated as Res Average Use (10,468 kWh/customer in 2024, 11,...
AI summary The document discusses the calculation of residential load, including existing customer load, new customer load, EV load, solar load, RTR load, hybrid load, and DSM load. It provides data on residential average use and its components, such as heating, cooling, and other uses, and includes a regression analysis for 2024 and 2034.
61 246 9 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix E Page 10 of 18 Small Scale Solar • Small scale solar uptake continues to be strong: as of 2023 approximately 71.7 MW of solar generation has been inst...
AI summary The document discusses the strong uptake of small-scale solar installations in Nova Scotia, with 71.7 MW installed as of 2023, and forecasts increased solar penetration due to legislative changes and rebate programs. It also outlines forecast changes for residential and commercial load, noting the impact of warmer weather, electric heating, and the introduction of Renewable to Retail (RTR).
N-6NSPI (Synapse) RIR-1 to RIR-54 - Redacted
4 passages
1 (c) 2 (i-xi) Please see the following table estimating the number of customers for each 3 category in the forecast: 4 Customers Customers Customers Customers Customers Customers Existing with with Heat with with Electric with Heat with H...
AI summary The text presents a table forecasting the number of customers in various categories, including residential, electric resistance, heat pumps, and others, from 2024 to 2032. The data shows trends in customer distribution across different heating and cooling sources over time.
New New New Customers New Customers New Customers Customers Residential with Heat Pump with Electric with Non Electric with Customers Heat Baseboard Heat Heating Supplementary Year Electric Heat 2024 7,021 4,213 1,755 1,053 2,457 2025 13,6...
AI summary The text provides a table showing the number of new residential customers with various heating types from 2024 to 2034. It also references the 2024 Load Forecast Report (LFR) and Attachment 1 Residential Intensities for calculations related to end-use saturation, particularly heat pump saturation based on annual sales data from installers.
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-8: 2 3 Residential Water Heaters (WH) (Section 4.4, p 35-36) 4 5 (a) Please provide NSPI’s projection of electric resist...
AI summary The document outlines a series of information requests from NSPI to Synapse regarding projections and standards related to electric water heaters, including heat pump water heaters, load control strategies, and program offerings to promote efficiency. These requests cover forecasting, load impacts, efficiency standards, and program evaluations for the period 2024 through 2034.
Customer count and housing New housing usage NSPI and other Programs Before future DSM Year SAE model Historical Increment Cumlative New Cumulative Forecasted New New Structural Forecast RTR Hybrid Electric Solar PV Total Total SAE + Regre...
AI summary The text presents data on customer counts, housing usage, and energy consumption from 2014 to 2016, including information on new housing, structural changes, and energy programs such as Solar PV and Electric Vehicles. The data includes forecasted and historical usage figures.
N-8Evidence of Synapse (BCC)
4 passages
..................................................................................7 1.5. Recommendations from the Previous Forecast Review .....................................................8 2. ENERGY FORECAST .............................
AI summary The document outlines energy and peak demand forecasting methodologies, analyzing residential, commercial, industrial, and municipal sectors. It discusses DSM effects, sensitivity analysis, and provides recommendations for improving forecast accuracy and alignment with demand-side management strategies.
281 -37 -68 4 115 -145 2,670 147 2,851 mitigation) Source: Figure 61 from 2024 Load Forecast NSPI provides the percent error and mean absolute percent error for the firm peak forecast in Figure C5 of Appendix C. In aggregate, the average p...
AI summary NSPI's 2024 load forecast shows under-forecasting trends, with residential load growth driven by EVs and electrification. The forecast's accuracy is questioned due to consistent under-forecasting, while sectoral energy use trends highlight residential dominance. Synapse Energy Economics provides analysis on these issues.
ng gross domestic product and manufacturing employment. A longer regression timescale was used for the industrial models as that produces better statistics. We consider these to be reasonable choices. The forecast now gives more considerat...
AI summary The load forecast incorporates climate change impacts via updated HDD/CDD trends (-17 HDD/year, +1.4 CDD/year) and adjusts peak temperature assumptions. The residential sector (44% of load) is projected to grow 2.3% (2024-2034) with DSM programs, versus 9.1% without them. Synapse Energy Economics provides analysis on these modeling choices.
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.
94285BCC-Synapse (NSPI) IR-1 to IR-54
8 passages
most appropriate indicator in the near term.” Given that the Board directed NSPI in its 35 2023 Decision in Matter 11108 to “re-evaluate the use of housing completions for the near-
AI summary The Board directed NSPI to re-evaluate the use of housing completions, referencing its 2023 Decision in Matter 11108.
y Trends (Section 4.4, pp 30-50) 24 a. Please provide in electronic spreadsheet format the end-use data in the form of 25 saturations and efficiencies from NRCan and U.S. EIA used for the residential and 26 commercial models. 27 b. Please...
AI summary The text contains regulatory requests for data on residential and commercial energy modeling, including end-use efficiency data from NRCan and U.S. EIA, adjustments to align with NS Power billing data, and questions about the E3 scenario's net-zero emissions targets and load forecasting methods.
9 c. Refer to Figure 17. Please provide for all the forecast years: 10 1. Total number of residential customers, 11 2. Number of customers for HP, Hybrid, Resistance, Wood, and Fossil Fuel heating 12 systems as indicated in Figure 17. 13 3...
AI summary The document requests detailed data on residential and commercial heating technologies, including heat pump adoption rates, customer segmentation, and forecasted numbers. Specific focus is on heat pump saturation (44% in 2024), customer class breakdowns, and alignment with figures 17 and 18.
ciencies (in terms of coefficient of 8 performance) assumed for new residential heat pumps from 2024 through 2034. 9 e. Please provide a table of NSPI’s heat pump forecast for commercial heat pumps, 10 equivalent to Figure 21. 11 f. Please...
AI summary The text contains detailed requests for data on NSPI's heat pump and water heater projections, including efficiency metrics, heating intensity estimates, and peak load impacts for residential and commercial systems from 2024 to 2034. It also seeks clarification on methodology for adjusting heat pump intensity calculations based on weather dependencies.
Date Filed: May 29, 2024 Synapse (NSPI) Page 7 of 24 1 systems and separately for electric resistance water heaters and heat pump water 2 heaters. 3 d. What are the existing or proposed standards for improving hot water efficiency? 4 e. Pl...
AI summary The document outlines requests for information regarding NSPI's programs for heat pump water heaters, load control strategies, impact evaluations, and EV scenario assumptions. It seeks data on program offerings, load management impacts, jurisdictional comparisons, and EV forecasting methodologies.
Date Filed: May 29, 2024 Synapse (NSPI) Page 10 of 24 1 Introduction (Section 2.0, citing to Board Decision concerning 2023 Load Forecast). Please 2 explain in detail how NSPI has addressed the Board’s direction to include/address each of...
AI summary The Board requests NSPI to address specific aspects in its 2024 Load Forecast, including IRP outcomes, carbon emission assumptions, historical load analysis, elasticity evaluation from the TVP Pilot (M11267), and residential model robustness. It also inquires about providing multiple forecasts based on the IRP.
Date Filed: May 29, 2024 Synapse (NSPI) Page 12 of 24 1 Request IR-19: 2 Demand Side Management Adjustment (Section 4.6, pp 54-56) 3 a. Please provide the details of the data and statistical analysis that was used to develop the 4 coeffici...
AI summary The document outlines requests for detailed data and statistical analysis related to Demand Side Management (DSM) coefficients in residential and commercial/industrial sectors, as well as residential solar and new customer adjustments. It seeks clarification on methodological changes, statistical measures, and historical/forecasted DSM values for each sector.
gure 69 between 24 the Residential coincidental peak load with and without DSM. Please also explain the 25 relationship between these differences and the DSM values in Figure 35 and the demand 26 response values in Figure 56. 27 f. How is...
AI summary The text includes several requests for information related to sensitivity analysis, forecasting, and modeling in an integrated resource plan. It asks for data and explanations regarding the impact of demand-side management, model robustness, and the variables used in forecasts and residential models.