Topic:"Load Management" in M12861

REDACTED (CONFIDENTIAL INFORMATION REMOVED) Nova Scotia Energy Board IN THE MATTER OF The Public Utilities Act, R.S.N.S. 1989, c.380, as amended 2026 Load Forecast NS Power Annual Report May 15, 2026 REDACTED REDACTED (CONFIDENTIAL INFORMA...

AI summary The document outlines NS Power's 2026 Load Forecast Report, part of its Annual Report, discussing stakeholder consultations, forecasting methodologies, and major input factors. It is part of a regulatory proceeding under the Public Utilities Act, focusing on energy load projections and planning.

.......................................................... 80 34 10. PEAK DEMAND .................................................................................................................. 83 35 10.1 Peak Model Modifications ..........

AI summary The document outlines sections of a 2026 Load Forecast Report, including peak demand modeling, 2025 peak analysis, 2026-2036 peak forecasts, peak mitigation strategies, solar impact on peak demand, end-use peak estimates, and sensitivity analysis. It focuses on technical aspects of load forecasting and integrated resource planning.

.............................................................. 97 30 Figure 72: Commercial End-Use Peak Shares .............................................................................. 97 31 Figure 73: Comparison of bottom-up and top-...

AI summary The 2026 Load Forecast Report includes figures analyzing energy demand patterns, peak load forecasts, and system sensitivity. Attachments detail residential and commercial intensity models, demand forecasting methodologies, and peak load inputs, supporting the Integrated Resource Plan (IRP) scenarios discussed in Figure 77.

(CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED LIST OF APPENDICIES Appendix A: 2026 NS Power Forecast Appendix B: Forecast Model Details Appendix C: Forecast Comparison (Partially Confidential) Appendix D: Forecast S...

AI summary The 2026 Load Forecast Report by NS Power includes appendices detailing forecast models, comparisons, sensitivity analyses, and stakeholder presentations. Parts of the document are redacted due to confidentiality, with appendices A, B, E, and portions of C and D containing sensitive information.

M) and Renewable to Retail (RTR) migration offsetting sales. 14 Annual historic and forecast NSR are shown below in Figure 1. 15 16 Figure 1: Historical and Predicted Annual Net System Requirement Net System Requirement 15,000 14,000 13,00...

AI summary NS Power forecasts increasing system peak demand from 2026 to 2036, driven by customer growth, electrification, and EV adoption, offset by DSM and DR programs. The 2026 forecast adjusts for a record peak in January 2026, with the 2025-2026 forecast difference narrowing by 2036.

11,815 0.8 2,689 1.4 2035F 11,939 1.0 2,730 1.5 2036F 12,097 1.3 2,765 1.3 2 DATE: May 15, 2026 Page 11 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The document references a redacted '2026 Load Forecast Report' dated May 15, 2026, with numerical data presented in a table format. The content is partially obscured, focusing on load forecasting metrics for future years.

1 • The economic data used in the medium industrial class, including evaluation of 2 manufacturing employment, has been updated. Please refer to Section 4.4. 3 • The impacts of hybrid heat pumps have been modelled and included in the under...

AI summary Updates to the 2026 Load Forecast include revised economic data, hybrid heat pump modeling, and solar installation updates. NS Power engaged stakeholders, discussing changes like heat pump impacts, EV demand, and renewable-to-retail effects, with references to technical sections.

1 4.2 2025 Data Modifications Due to the Cyber Incident 2 3 NS Power’s billing processes were impacted in 2025 by the cyber incident and estimated monthly 4 billing was implemented for the residential, small general, general demand and mun...

AI summary NS Power adjusted 2025 billing and load forecast data due to a cyber incident. They used 2024 patterns to estimate monthly sales and historical data to estimate peak contributions, ensuring accurate forecasts without anomalies.

2026 Load Forecast Report REDACTED 1 Figure 6: Comparison of Peaks Using Actual and Estimated Large Customer Load 2 3 4 Additionally, the interruptible portion of the large customer load required estimation in order to 5 calculate the firm...

AI summary The report discusses the estimation of interruptible load for large customers to calculate firm peak load, using a historical average of 43.8% during previous system peaks. It also mentions the use of Heating Degree Days (HDD) and Cooling Degree Days (CDD) to account for temperature impacts on electric sales, with a reference temperature of 18°C.

e minimum 19 temperatures 20 21 DATE: May 15, 2026 Page 26 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 13: Trend in combined rolling 12 and 24 hour lagged temperatures 2 3 4 Unlike winter...

AI summary The document discusses summer peak temperature trends, noting that unlike winter peaks, summer peaks do not show a clear trend and are based on the 10-year average. This information is used in the 2026 Load Forecast Report.

75. 24 25 New housing completions for both single-family and multi-unit buildings as forecast by Signal49 26 continue to be used directly in the residential customer forecast. Growth of new customers is 27 expected to remain positive but d...

AI summary The 2026 Load Forecast Report indicates that new housing completions are a key factor in forecasting residential customer growth, with housing data showing a strong correlation to customer count. Population growth is expected to slow after 2024, leading to a decrease in new customer additions over time.

age 30 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report discusses projections for electricity demand in Nova Scotia, providing insights into future load requirements and potential impacts on the energy system.

6 2,891 -10.0 22,836 0.4 16‐25 7.4 2.6 26‐36 -10.0 0.5 2 3 DATE: May 15, 2026 Page 32 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of electricity demand trends, including projections for different age groups and time periods. However, the content is partially redacted, and specific details are confidential.

Page 32 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. It includes detailed forecasts based on various factors such as heating and cooling degree days, as well as the impact of energy efficiency programs and demand-side management initiatives.

50,498 1.2 490 0.3 16‐25 2.1 2.0 26‐36 1.5 0.3 2 3 4 DATE: May 15, 2026 Page 33 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 20: Industrial Economic Drivers

AI summary The document contains a redacted section of the 2026 Load Forecast Report, including a figure related to industrial economic drivers. The content is partially redacted due to confidentiality.

4 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand for the year 2026, including key factors influencing load growth and potential impacts on the electricity system.

1 Figure 21: Economic Forecast Comparison GDP Employment Housing Starts 2026 (%) 2027 (%) 2026 (%) 2027 (%) 2026 2027 Signal49 9 1.3 1.8 0.6 0.2 8181 6771 BMO 10 1.4 1.8 0.5 0.6 8500 8000 RBC 11 1.5 1.6 0.4 0.4 7800 6000 TD 12 1.6 1.2 0.3...

AI summary The document discusses economic forecasts for GDP, employment, and housing starts through 2027, as well as the use of end-use data from NRCan and the EIA to develop load forecasts. Historical data and efficiency estimates are used to model residential and commercial energy consumption trends.

of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of future electricity demand in Nova Scotia. It includes projections based on various factors such as population growth, economic development, and energy efficiency initiatives. The report is part of the Integrated Resource Plan (IRP) process and informs decision-making for energy infrastructure planning.

2028, which is the hybrid heating working group’s current target for program implementation. The 17 development of any associated incentives is part of the ongoing work on a hybrid program. 18 DATE: May 15, 2026 Page 38 of 105 REDACTED (CO...

AI summary The 2026 Load Forecast Report discusses the modeling of residential electric heating load shapes and the potential impacts of a hybrid heating program, which aims to reduce peak and energy demand. The report highlights that peak reductions depend on participation levels and hybrid event trigger scenarios, and that the overall impact may not reach the target program value.

Page 39 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The report is redacted, indicating that confidential information has been removed.

6 -15 2031 -26 -11 -14 -41 -24 -17 2032 -32 -16 -16 -51 -34 -17 2033 -36 -20 -16 -60 -43 -17 2034 -40 -24 -16 -68 -51 -17 2035 -44 -28 -16 -76 -59 -17 2036 -48 -32 -16 -83 -67 -16 15 DATE: May 15, 2026 Page 41 of 105 REDACTED (CONFIDENTIAL...

AI summary This document contains a redacted section of the 2026 Load Forecast Report, focusing on Commercial Hybrid Heating. The table presents data spanning from 2031 to 2036, with values indicating various load-related metrics, though specific details are confidential.

CTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Commercial Hybrid Heating 2 3 Unlike for residential, to date there has been no provincial planning or discussion around a 4 commercial hybrid heating program. On...

AI summary The 2026 Load Forecast Report discusses the lack of provincial planning for commercial hybrid heating programs, using assumptions from E3's hybrid scenario and adjusting the start date from 2026 to 2028. Adjustments are made to the commercial energy forecast based on the hybrid heating scenario, with specific energy adjustment values provided for 2028, 2032, and 2036.

heating 16 scenario Year Energy Adjustment (GWh) 2028 -7 2032 -35 2036 -75 17 18 4.5.3 Water Heaters 19 NS Power anticipates that some customers who convert their oil heating systems to heat pumps 20 will also convert their hot water suppl...

AI summary NS Power projects that the adoption of heat pumps and electric water heaters will increase, leading to a decrease in energy demand by 2036. However, the growth rate is slightly lower than previously forecasted due to fewer heat pump installations. NS Power is collaborating with E1 on a demand response program involving direct control of water heaters.

Page 42 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of future electricity demand in Nova Scotia. The report includes projections based on various factors such as population growth, economic development, and energy efficiency initiatives. It is a critical document for planning and regulatory decision-making.

water heaters, their modelled intensity is 21 set to 40 percent of standard electric water heaters, based on estimates provided by E1. 22 Heat 22 pump electric water heater saturation and overall intensity over the forecast period are incl...

AI summary The document discusses the modelled intensity of heat pump electric water heaters, set at 40 percent of standard electric water heaters based on estimates from E1. References are made to various reports and plans related to demand-side management and load forecasting.

NFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 27: Electric Water Heater Forecast Year Saturation (% of total population) Intensity (kWh/household) 23 Combined Standard Heat Pump Standard Heat Pump Combined Total Total 202...

AI summary The 2026 Load Forecast Report provides projections for electric water heater saturation and intensity, including standard and heat pump models, from 2026 to 2036. It also includes a section on electric vehicles (EVs), indicating the report's focus on future electricity demand forecasting.

1,653 24 1,677 2036 82 3 85 1,661 26 1,687 2 3 4.5.4 Electric Vehicles (EVs) 4 EV sales were higher than forecast in 2025, despite the conclusion of provincial light-duty vehicle 5 EV rebates in May 2025, and the temporary pausing of feder...

AI summary EV sales in Nova Scotia exceeded 2025 forecasts despite the end of provincial rebates and temporary federal incentives. As of 2025, there were approximately 9,600 EVs in the province, leading to an updated 2026 load forecast. The ramp-up in EV adoption is expected to be less steep due to changes in policy, including the cancellation of the EV Availability Standard and a revised federal ZEV mandate.

E3, including the impact to LDV load 16 and peak from both at-home and public charging (assumed to add 10 percent to annual energy and 17 0.2 kW/vehicle to peak based on the E3 load shapes). 18 DATE: May 15, 2026 Page 46 of 105 REDACTED (C...

AI summary The 2026 Load Forecast Report discusses the impact of light-duty vehicles (LDV) on energy load and peak demand, including both at-home and public charging scenarios. It assumes an increase of 10 percent in annual energy use and 0.2 kW/vehicle to peak demand based on E3 load shapes.

Page 46 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand for the year 2026. The report is redacted, indicating that it contains confidential information not disclosed in the provided text.

Page 47 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The report includes key factors influencing load forecasts, such as weather patterns, economic trends, and the impact of energy efficiency programs.

in Figure 8 32 and Figure 33 below. 9 DATE: May 15, 2026 Page 49 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 32: Average Winter Profiles 2 3 4 Figure 33: Average Summer Profiles 5 DATE: Ma...

AI summary The document discusses the 2026 Load Forecast Report, focusing on average winter and summer load profiles presented in Figures 32 and 33, and includes a section on new technologies impacting load forecasting.

8 1 4 8 2 2030 10 1 6 8 3 2031 11 1 9 8 3 DATE: May 15, 2026 Page 55 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED Coinc.1 LrgGen SmInd MedInd LrgInd Year Peak (GWh) (GWh) (GWh) (GWh) 2 (MW) 2032 13...

AI summary The 2026 Load Forecast Report provides projected load data for various sectors, including large generation, small industry, medium industry, and large industry, with peak demand figures for the years 2032 through 2036.

gression (via 24 the historic data) and in the projected end-use data. The effect of DSM on non-sales related inputs 25 also makes it unrealistic to add historic DSM into past sales to produce a “without DSM” forecast 26 – the impact of DS...

AI summary The text discusses the challenges of incorporating historical demand-side management (DSM) data into load forecasts, emphasizing the need to avoid double counting and the impact of DSM on non-sales related factors such as price and appliance efficiency. The approach used involves introducing cumulative historical DSM savings into the regression model.

Page 58 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The document presents the 2026 Load Forecast Report, which includes redacted confidential information. It outlines projections and analyses related to future electricity demand in Nova Scotia.

ed to 20 be included in the forecast. 21 22 For the Commercial and Industrial classes, a combined model was created to identify the level of 23 DSM already captured by other variables. DSM impacts are not provided for Commercial and 24 Ind...

AI summary The document discusses the inclusion of Demand-Side Management (DSM) in the 2026 load forecast for Commercial and Industrial classes. A combined model was used to reduce uncertainty in allocating historical DSM savings, with a DSM variable coefficient of -0.539, indicating a 54% adjustment to future load forecasts based on DSM amounts. The model has a high adjusted R-squared value of 0.85 and a low MAPE of 2.68, indicating a strong fit.

Page 59 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The document presents the 2026 Load Forecast Report, which includes confidential information that has been redacted. The report likely outlines projections related to electricity demand in Nova Scotia for the year 2026.

Page 61 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The document includes detailed forecasts and assumptions about future load patterns, though specific data has been redacted due to confidentiality.

ccrued) Forecast Sales 4830 5180 5289 5289 5315 Weather variance -126 -104 +44 +44 Other variance +230 -12 -106 -41 Actual Sales 4934 5064 5227 5292 Weather-adjusted sales 5060 5167 5183 5248 5315 22 23 Actual sales in 2025 were very close...

AI summary The 2026 Load Forecast Report discusses actual sales in 2025, which were close to forecasts but impacted by colder weather, leading to a 44 GWh increase in sales and an 'other' variance of -41 GWh. This was attributed to fewer heat pump installations and fewer new customers than anticipated.

years. These two factors combined lead to a steady average use per new 20 residential customer. Building shell efficiency, floor area and the resulting structural index are in 21 Figure 44. 22 DATE: May 15, 2026 Page 64 of 105 REDACTED (CO...

AI summary The document discusses the 2026 Load Forecast Report, focusing on factors influencing average residential electricity use, including building efficiency, floor area, and structural index, as illustrated in Figure 44.

Page 64 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 44: Building Characteristics and Structural Index Year BSE Heat EIA BSE Heat NS Floor Area (m2) Structural Index (New England) 2026 0.94...

AI summary The text presents a 2026 Load Forecast Report, including figures and tables that outline building characteristics, structural indices, and residential energy forecast adjustments. It references a detailed breakdown in Appendix B and mentions NS Power's modelling for hybrid impact adjustments.

outlined in 7 Section 4.5.2). 8 DATE: May 15, 2026 Page 65 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The document outlines the 2026 Load Forecast Report, which includes confidential information that has been redacted. The report is part of a regulatory proceeding and provides insights into load forecasting for the year 2026.

5,393 -222 -103 2033 5,258 342 -17 -276 302 -49 -152 5,408 -286 -133 2034 5,261 368 -17 -320 406 -49 -185 5,464 -348 -162 2035 5,269 390 -17 -361 529 -49 -216 5,545 -407 -190 2036 5,288 411 -16 -394 653 -49 -246 5,646 -464 -217 2 3 Figure...

AI summary The text discusses the use of regression models and load forecasting methodologies, referencing specific figures and appendices. It highlights the inclusion of heat pump and electric baseboard loads in the Regression Model Output column and notes that the numbers are illustrative, not accounting for DSM impacts.

Page 73 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 7. INDUSTRIAL AND MUNICIPAL SECTORS 2 3 The forecast models for the Small Industrial and Medium Industrial classes are econometric-based 4 mode...

AI summary The 2026 Load Forecast Report discusses econometric-based models for forecasting energy use in the Small Industrial and Medium Industrial sectors, using economic variables such as manufacturing GDP and employment. The report notes that migration to RTR will decrease load in 2027 and 2028 before economic growth leads to a recovery by 2036.

Page 75 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 53: Historical and Forecast Annual Medium Industrial Sales 2 3 4 7.3 Other Industrial Rate Classes 5 6 Other Industrial rate classes inc...

AI summary The 2026 Load Forecast Report discusses the forecasting methods used for Other Industrial rate classes, including Large Industrial and Generation Replacement. Customer surveys and historical data are used to predict load, with some variance due to a major customer's reduced consumption in 2025. Load migration to the RTR market is also mentioned.

Page 76 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 expected to be around 45 GWh by 2028, but this is expected to be offset by additional load from 2 one new customer and operations restarting at...

AI summary The 2026 Load Forecast Report indicates that large industrial annual growth is expected to reach 45 GWh by 2028, though this may be offset by new customer load and operations resuming at existing customers. However, there is uncertainty regarding the timing and scale of future industrial expansions.

Page 79 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The document outlines the 2026 Load Forecast Report, which provides an analysis of future electricity demand in Nova Scotia. Key details have been redacted due to confidentiality concerns.

Page 82 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of expected electricity demand in Nova Scotia for the year 2026, though specific details have been redacted due to confidentiality.

occurred on February 4th 2023, the 2026 peak was not characterised 25 by extremely low temperatures; instead, what made this peak unique was that it coincided with a 26 prolonged cold spell. This is evident from a comparison of 12-hour vs...

AI summary The 2026 peak load was influenced by a prolonged cold spell, as evidenced by the comparison of 12-hour and 24-hour average lagged peak temperatures, with the January 2026 peak standing out historically.

Page 83 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The report is redacted, indicating that sensitive or confidential information has been removed.

1 Figure 59: Average peak lag temperature records Coldest 24-h lag average (Jan 2000 – Jan 2026) Coldest 12-h lag average (Jan 2000 – Jan 2026) Rank Date 24h lag Rank Date 12h lag average ( C) o average (o C) 1 Jan 25th 2026 -15.11 1 Feb 4...

AI summary The document discusses the use of 24-hour lag temperature as a peak-producing weather variable in the peak model, with greater weighting given to the 12-hour lag temperature. Stakeholders requested a sensitivity analysis using 36- and 48-hour lag temperatures to evaluate their impact.

Page 84 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 60: Comparison of modelled 2026 peaks Using peak model from Using improved 2025 Load Forecast, with peak model from updated input data (...

AI summary The 2026 Load Forecast Report updates the peak model used in prior forecasts, adjusting coefficients for peak normalization based on improved input data and weather variables. The report includes a comparison of modelled peaks and actual peaks, with detailed model details provided in subsequent figures.

17 18 The 2025 system peak occurred at hour ending 8am on Thursday, February 6, with a 12-hour (24- 19 hour) lagging average temperature of -12.1°C (-11.0oC) and a daily average windspeed of 7.4 DATE: May 15, 2026 Page 86 of 105 REDACTED (...

AI summary The 2025 system peak demand occurred on February 6 at 8am, with a lagging average temperature of -12.1°C and a daily average windspeed of 7.4 km/h. This information is part of the 2026 Load Forecast Report, which has been redacted due to confidentiality.

Page 86 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The report is redacted, indicating that sensitive or confidential information has been removed.

or the January and December peaks and 18 primarily reflects the much smaller change in lighting demand between 8 am and 6 pm in February. 19 The two series, by month, are shown in Figure 64. 20 DATE: May 15, 2026 Page 87 of 105 REDACTED (C...

AI summary The document discusses the 2026 Load Forecast Report, highlighting a 1.1 percent annual increase in system peak demand from 2026 to 2036, with a 3.1 percent increase in the near term compared to the 2025 forecast. The firm peak, which excludes interruptible and demand response (DR), is expected to rise by 1.0 percent annually.

ON REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 66: Historical and Forecast Firm Peak (including DR) 2 3 4 Forecast peak values, firm peak and interruptible peak information can be found in Appendix A. 5 6 Normalizing the firm peak...

AI summary The 2026 Load Forecast Report includes figures related to historical and forecast firm peak demand, with normalization for temperature, wind, and weekday/weekend factors. Appendix A provides detailed forecast peak values and interruptible peak information.

REMOVED) 2026 Load Forecast Report REDACTED 1 Figure 67: Weather-Normalized Firm Peak (including DR) 2 3 4 Figure 68 below shows the breakdown of the peak forecast by the various components. 5 6 Figure 68: Peak Contribution Components (MW)...

AI summary The 2026 Load Forecast Report provides a detailed breakdown of peak demand contributions by various components, including residential, EV, demand response, and DSM programs, with projections for 2026 and 2036.

of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026, though the content has been redacted and confidential information removed.

1 contribution to peak is expected to be partially mitigated via utility managed charging. The firm 2 peak assuming the current non-coincident residential EV peak value of 0.5kW/vehicle and that 3 commercial charging does not include peak...

AI summary The text discusses the impact of electric vehicle (EV) charging and hybrid heating on peak demand, noting that utility-managed charging and DR programs are expected to mitigate some of the growth in peak demand. It also references the 2026 Load Forecast and the inclusion of DR programs from the 2022 Evergreen IRP, with future DR amounts based on achievable potential.

e 92 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of anticipated electricity demand in Nova Scotia for the year 2026. The document is redacted, indicating that confidential information has been removed.

1 DR forecasts continue to use an effective load carrying capacity (ELCC) of 48 percent to account 2 for the contribution of DR in supporting (or in this case, reducing) the capacity needs on the system 3 to meet the reliability standard (...

AI summary The text discusses the use of Effective Load Carrying Capacity (ELCC) in Demand Response (DR) forecasts, noting that DR contributes 48% to system capacity needs. The ELCC study will reassess this value using data from NS Power’s and E1’s DR programs. Annual DR totals by program are provided in Figure 69, showing increasing participation over time.

of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The report includes detailed projections and considerations for future energy needs, though specific details have been redacted due to confidentiality.

1 available DR capacity at the generator of 8 MW for the 76 participating C&I customers. In the 2 2024/2025 season, DR capacity at the generator was evaluated at 5.941 MW over 158 customers 3 total versus a target of 10.726 MW (45 percent...

AI summary The document discusses the performance of demand response (DR) programs in Nova Scotia, noting that available DR capacity fell short of targets in the 2024/2025 season. It also addresses the impact of solar energy on system peak demand, highlighting the influence of weather and timing on solar production during peak periods.

23 the annual system peak forecast is assumed to occur on a cold January evening after sunset, the 24 coincidence factor impacting the maximum demand is unlikely to change in the near term. 25 45 2025 DSM Programs Evaluation Reports (M1278...

AI summary The document discusses the 2026 Load Forecast Report, which includes a figure detailing peak contribution components and average coincidence factors for each month. The forecast assumes the annual system peak occurs on a cold January evening after sunset, with the coincidence factor expected to remain stable in the near term.

27 August 31 September 24 October 5 November 0 December 0 2 3 10.6 End Use Peak Estimates 4 5 While the Load Forecast is a good statistical fit for the historical data, it presents challenges when 6 trying to assess the contribution of ind...

AI summary The document discusses the 2026 Load Forecast Report, highlighting changes in residential and commercial end-use contributions to peak demand. Electric vehicles (EVs) are expected to increase their share from 0.4% in 2026 to 4.5% by 2035, while electric heating sources will decrease from 68.3% to 65.7% over the same period.

Page 97 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an analysis of projected electricity demand in Nova Scotia for the year 2026. The report includes detailed forecasts and considerations relevant to the energy sector, though specific content has been redacted due to confidentiality.

1 in the commercial sector also drives an increase in the relative contribution to peak from electric 2 heating sources, growing from 39.8 percent in 2026 to 41.2 percent in 2035. Apart from office 3 equipment, which sees a fractional rise...

AI summary The text discusses changes in peak demand contributions from different sectors, noting an increase in electric heating and a decrease in lighting. It also outlines NS Power's method for forecasting system peak demand using interval data and growth factors to estimate class-level peak demand.

coincident peak for each class to produce class‑level peak 24 forecasts by year. The resulting class forecasts were aggregated to form an initial bottom‑up 25 estimate of coincident system peak demand. In alignment with the top‑down system...

AI summary The document discusses the comparison of bottom-up and top-down methodologies for forecasting system peak demand, noting differences in growth rates and convergence over time. The bottom-up approach shows a higher growth rate and divergence from the top-down estimate due to structural factors.

Page 100 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Secondly, the bottom‑up estimate is derived from a single historical peak event. As such, the 2 forecast is inherently sensitive to the specif...

AI summary The document discusses the limitations of a bottom-up load forecasting method, which relies on a single historical peak event, making it sensitive to specific conditions. In contrast, the top-down method uses ten years of data, offering greater statistical stability. The bottom-up approach will be refined to improve its reliability and complement the top-down method in future forecasting.

Page 101 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 11. SENSITIVITY ANALYSIS 2 3 The sales and peak forecasts are fundamentally uncertain and depend on many variables, including 4 economics, wea...

AI summary The 2026 Load Forecast Report discusses the uncertainty in sales and peak forecasts, influenced by factors such as economics, weather, distributed generation, electricity rates, and DSM. A P10/P90 probability analysis using Monte Carlo simulations is employed to estimate the probable distribution of future load, showing a range of approximately 488-584 GWh over a 10-year period.

Type for a particular year y, EffyType is the efficiency of an end-use of given Type for a particular year y, and EI15Type is a reference year (2020) calibration weight per end-use Type. The factors: 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 �𝑆𝑆𝑆𝑆𝑆𝑆𝑦𝑦 /𝐸...

AI summary The document describes the calculation of efficiency factors and the impact of DSM programs on residential load forecasting. It includes the use of a binary variable to account for the effects of the COVID-19 pandemic on load patterns, which was later removed from the forecast period.

-19.8% 18.4% 5.8% 1.1% -0.3% -5.9% 0.0% -0.7% to load XHeat = (Efurn + HP Heat + Secondary Heat + Furnace Fans) x HeatUseVariable x Coeff Note that because these factors are multiplicative, the growth rate for the intensities is multiplied...

AI summary The text discusses load forecasting calculations for residential heating and cooling demand, including variables such as Efurn, HP Heat, and CoolUse, with coefficients applied to calculate overall impacts on load. It provides numerical data for 2026 and 2036, showing changes in intensities and coefficients.

NTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 11 of 34 Variable Coefficient StdErr T-Stat P-Value MStructSmlGen.WtXHeat 0.789 0.038 20.962 0.00% MStructSmlGen.WtXCool 0.308 0.041 7.481 0.00% MStructSmlGen.WtXOther 0....

AI summary This section presents statistical data from a load forecast model, including coefficients, standard errors, t-statistics, and p-values for various variables. It includes data on heating, cooling, and other factors affecting load forecasting, as well as seasonal and yearly bin variables.

CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 12 of 34 Small General Model Statistics Model Statistics Iterations 21 Adjusted Observations 120 Deg. of Freedom for 109 Error R-Squared 0.942 Adjusted R-Squared 0...

AI summary This section presents statistical details for the Small General Model used in the 2026 Load Forecast Report. It includes metrics like R-squared, AIC, BIC, and others, as well as a reconciliation of the model for the 2026-2036 period. Adjustments for commercial and industrial growth, PV, EV, RTR, and DSM are included outside the regression.

VED) 2026 Load Forecast Report Appendix B Page 18 of 34 General Service Model Statistics Model Statistics Iterations 20 Adjusted Observations 120 Deg. of Freedom for 107 Error R-Squared 0.916 Adjusted R-Squared 0.906 AIC 17.583 BIC 17.885...

AI summary The text presents statistical model outputs from a load forecast report, including metrics such as R-Squared, Adjusted R-Squared, AIC, BIC, and other statistical indicators. The report also includes a reconciliation section for general demand from 2026 to 2036.

% 12.7% -6.6% -6.4% -1.2% to load Gen Sales = Sales + Model alignment (2025 actuals vs forecast) + RTR + EV Load + Solar Load + Hybrid + DSM General Demand Sales –Regression XHeat XCool XOther Binaries ARMA Sales (GWh) 2026 559,305 124,865...

AI summary The text presents load forecast data and input variables for general demand, including heat, cooling, and other factors, with comparisons between 2026 and 2036. It discusses the calculation methodology, including multiplicative factors and growth rates for intensities.

(CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 21 of 34 General Demand Input Variables – XCool Intensity Econ + Regression Structural Cooling CoolUse Coefficient Scaling Total Variable Factor Xcool 2026 363,06...

AI summary The text presents demand input variables for XCool and XOther, including intensity factors, scaling factors, and load forecasts for 2026 and 2036. It outlines the calculation methodology for XCool and XOther based on various demand components and coefficients.

INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 22 of 34 Industrial Econometric Model Details Small Industrial model SmlInd_Salesm = MBin.Janm + MBin.Febm + MBin.Marm + MBin.Aprm + MBin.Maym + MBin.Junm + MBin.Julm + MBin.Au...

AI summary The document discusses the Small Industrial model used in the 2026 Load Forecast Report. It includes a binary variable for October 2022 to account for billing delays after Hurricane Fiona and another for June 2025 to address billing issues due to a cyber incident. The model uses a combination of monthly binary variables and economic indicators to forecast sales.

s after hurricane Fiona and for June 2025 to account for billing issues due to the cyber incident. Variable Coefficient StdErr T-Stat P-Value MBin.Jan 19263.382 1445.250 13.329 0.00% MBin.Feb 16286.911 1447.459 11.252 0.00% MBin.Mar 16722....

AI summary The text presents statistical data from a load forecast report, including coefficients, standard errors, t-statistics, and p-values for various months and economic indicators. The data appears to be part of a larger analysis related to energy demand forecasting.

FIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 23 of 34 Small Industrial Model Statistics Model Statistics Iterations 1 Adjusted 120 Observations Deg. of Freedom for 105 Error R-Squared 0.832 Adjusted R-Squared 0....

AI summary This document contains statistical and model fit details for small and medium industrial load forecasts, including metrics such as R-squared, AIC, BIC, and error statistics, as well as information on model assumptions and fit quality.

fit compared to the formulation of previous years (R2 increased to 0.894 compared to 0.688 in the 2025 Load Forecast). Variable Coefficient StdErr T-Stat P-Value MBin.Jan 22327.947 2932.687 7.613 0.00% MBin.Feb 22223.607 2936.075 7.569 0.0...

AI summary This section presents statistical data from a load forecasting model, showing coefficients, standard errors, t-statistics, and p-values for various variables, including monthly load bins and economic factors. The R-squared value has increased significantly compared to the 2025 Load Forecast, indicating a better fit of the model.

VED) 2026 Load Forecast Report Appendix B Page 26 of 34 Medium Industrial Model Statistics Model Statistics Iterations 1 Adjusted Observations 120 Deg. of Freedom for Error 104 R-Squared 0.907 Adjusted R-Squared 0.894 AIC 14.793 BIC 15.164...

AI summary This section presents statistical details from the Medium Industrial Model used in the 2026 Load Forecast Report. It includes metrics like R-Squared, Adjusted R-Squared, AIC, BIC, and other statistical indicators that evaluate the model's performance and accuracy.

Prob (Jarque-Bera) 0.3238 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 27 of 34 Medium Industrial Model Fit REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 28 o...

AI summary The text presents a statistical model used for forecasting load demand, specifically focusing on the Medium Industrial Model Fit and a Combined Model for Commercial and Industrial DSM Coefficient. It includes variables, coefficients, standard errors, t-statistics, and p-values associated with the model, as well as binary variables added to address billing issues and improve model fit.

IDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 30 of 34 Peak Forecast (Non-Large Customer Classes 1) The long-term system peak forecast for the non-large customer classes is derived through a monthly peak linear re...

AI summary The document outlines a method for forecasting peak demand for non-large customer classes using a linear regression model that incorporates heating, cooling, base load, and wind variables. The model uses coefficients from sales forecast models for different customer classes to estimate heating and cooling load requirements.

asses” was used instead. REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix B Page 31 of 34 In constructing the monthly peak model variables, the heating and cooling load requirements are normalized for the numb...

AI summary The document explains the methodology for constructing monthly peak model variables by normalizing heating and cooling load requirements and using regression coefficients to account for non-weather sensitive load drivers.

herm and GSOtherm are the non-weather dependent portion of the sales model (including embedded DSM). For example, the energy sales model can be written as: ResSales = b1×ResXHeat+b2×ResXCool+ResOther Where b1 and b2 are regression coeffici...

AI summary The document explains how the non-weather dependent portion of the sales model, including embedded DSM, is calculated using regression coefficients. It also describes the normalization of load requirements on an average MW basis and introduces variables like PkWindVarm, which represents the average daily windspeed on monthly peak days.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Appendix C Page 6 of 9 Figure C5: Firm Peak Forecast Accuracy Firm Peak Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecas...

AI summary This table presents the firm peak forecast accuracy over multiple years, showing the forecasted values for each year from 2015 to 2024. It highlights discrepancies between forecasts and actual values, indicating challenges in load forecasting.

2256 2291 2024 2408 Actual System Peak: 2,111 2,018 2,073 2,060 2,050 1,968 2,216 2,455 2,088 2,267 Percent Error 2015 -3.8% 0.9% -1.8% -1.6% -1.7% 1.5% -10.4% -19.6% -4.6% -12.7% 2016 5.6% 4.0% 5.3% 6.3% 11.2% -0.8% -10.3% 5.6% -2.6% 2017...

AI summary The text presents a table with actual system peak values and percent errors from 2015 to 2024, illustrating variations in forecasting accuracy over time. The data shows fluctuations in percent error, indicating the challenges in predicting system peak demand.

4 +/-176 +/-292 +/-196 Price Elasticity of -0.3 (2x -18 -6 -88 -26 current elasticity of -0.15) At this time, any potential impacts of the proposed hydrogen facilities on the NS Power’s Net System Requirement and System Peak are still bein...

AI summary The document outlines the preliminary 2026 Load Forecast, highlighting changes from the 2025 forecast, preliminary results by rate class, and updates to the system and peak forecast models. It also mentions the evaluation of potential impacts from proposed hydrogen facilities on NS Power’s Net System Requirement and System Peak.

Agenda • Summary of changes from 2025 Load Forecast • Preliminary results by rate class • Preliminary system and peak forecast • Discussion of 2026 system peak and peak model updates 3 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Loa...

AI summary The document outlines the timeline and key changes in the 2026 Load Forecast Report, including updates to heat pump and EV forecasts, hybrid heating assumptions, and peak model adjustments based on the 2025 Load Forecast decision.

ation, changed class distribution. Peak Model Updated based on analysis of 2026 system peak (25th January). Specific directives from the 2025 Load Forecast 5 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix...

AI summary The 2026 Load Forecast Report notes a significant reduction in heat pump installations, primarily due to the discontinuation of financial incentives such as the Oil to Heat Pump Affordability (OHPA) program and Home Heating System Rebates in 2025. The forecast predicts a decrease of ~4,000 installations per year compared to the 2025 Load Forecast, with corresponding declines in heat pump heating and cooling demand by 2035.

Year d forecast forecast +364 2035 -875 -511 (42%) 8 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E Page 9 of 21 Residential hybrid heating (1) • NS Power modelled the system impact of potential hybrid h...

AI summary The document discusses NS Power's modeling of residential hybrid heating programs using AMI data, considering various trigger scenarios and participation rates. The 2026 Load Forecast retains E3's peak-mitigation estimate but adjusts the energy reduction estimate to the median modelled outcome of -85 GWh by 2036.

come of -85 GWh by 2036 was therefore used for the 2026 forecast. • Hybrid heating represented as a distinct end-use in residential SAE regression model to reflect these modelled results. 9 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 202...

AI summary The document discusses the modeling of residential hybrid heating and heat pump electric water heaters, using AMI data and SAE regression models. It outlines the methodology for forecasting load based on participation rates and trigger conditions such as CPP events and temperature thresholds.

DACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E Page 11 of 21 Heat Pump Electric Water Heaters • Modelled as a separate end-use to “standard” electric water heaters. Saturation (%) Load (GWh) • Intensity and...

AI summary The document discusses the modeling of heat pump electric water heaters as a separate end-use category, with estimates provided by EfficiencyOne. It also updates the Renewable to Retail load forecast, noting changes in load migration timing and class distribution, particularly a decrease in residential and medium industrial load and an increase in general demand.

asses, especially General Demand). Class 2025 Forecast (GWh) 2026 Forecast (GWh) Residential 117 49 Commercial 176 255 Industrial 128 117 Total 421 421 12 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E P...

AI summary The 2026 Load Forecast Report compares residential electricity demand forecasts for 2025 and 2026. Key factors influencing the change include less solar generation, higher EV sales, less RTR migration, lower heat pump penetration, and a delayed, weaker hybrid impact.

D (GWh) (GWh) +237 2035 5,205 5,442 (4.6%) Growth -0.2% / y 0.4% / y (10y avg) 13 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E Page 14 of 21 Forecast Comparison – Commercial • Similar to the Residentia...

AI summary The 2026 Load Forecast Report compares commercial electricity sales forecasts with the 2025 forecast, noting impacts from increased EV load and decreased behind-the-meter solar production. The forecast shows a slight decrease in growth rates compared to previous years.

D (GWh) (GWh) +105 2035 3,014 3,119 (3.5%) Growth -0.4% / y 0.1% / y (10y avg) 14 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E Page 15 of 21 Forecast Comparison – Industrial • Industrial sales were low...

AI summary The 2026 Load Forecast Report Appendix E discusses industrial electricity sales, noting that 2025 sales were lower than forecast due to reduced load from a single customer. New large customer load is expected in 2027/2028.

D (GWh) (GWh) +61 2035 2,187 2,248 (2.8%) Growth -0.3% / y 0.3% / y (10y avg) 15 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E Page 16 of 21 Forecast Comparison – Energy • 2026 Net System Requirement (N...

AI summary The 2026 Load Forecast Report indicates that the Net System Requirement (NSR) is expected to be higher than the 2025 forecast due to changes in the timing of RTR migration and decreased solar generation, along with increased EV load.

2025 Forecast NSR 11,607 Est. Weather Impact +59 Large Customer New Projects -5 Large Customer Actuals -153 Unexplained Variance -39 2025 Actual NSR 11,469 17 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix...

AI summary The 2026 Load Forecast Report indicates a ~3% increase in system peak forecast compared to the 2025 Load Forecast, primarily due to model adjustments following an all-time peak on January 25th, 2026. However, by the end of the forecast period, the difference is less than 1%, attributed to decreased heating load from fewer forecast heat pump installations.

2025 Fcst 2026 Fcst D (MW) (MW) 2035 2,672 2,693 +21 (0.8%) Growth 1.1% / y 0.9% / y (10y avg) 18 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report Appendix E Page 19 of 21 Peak Model Updates (1) • The system peak on...

AI summary The 2026 Load Forecast Report highlights a record peak system demand of 2459 MW on January 25th, 2026, driven by an extended cold period. This peak is higher than the previous record of 2455 MW on February 4th, 2023, which was caused by an extreme cold snap. The report compares cold periods using 24-hour and 12-hour lag averages.

Date 24h lag Rank Date 12h lag average (o C) average (o C) 1 Jan 25th 2026 -15.11 1 Feb 4th 2023 -21.61 2 Feb 4th 2023 -15.09 2 Feb 15th 2020 -15.84 3 Jan 12th 2022 -14.59 3 Jan 12th 2020 -15.53 4 Feb 5th 2023 -14.26 4 Jan 16th 2017 -15.34...

AI summary The document discusses updates to the peak model used in the 2026 Load Forecast Report. A 24-hour lag temperature has been incorporated as a peak-producing weather variable, reducing unexplained variance in the forecast. The updated model improves accuracy by combining 12-hour and 24-hour lag temperatures.

Using updated peak model 2025 Load Forecast, with from this Forecast (MW) updated input data (MW) 2026 Forecasted Peak 2,442 2,487 Interruptible -42 -42 Weather (-14.9oC 12hr lag avg, +38 +38 -15.1oC 24hr lag avg) Wind (14.1 km/h daily avg...

AI summary The 2026 Load Forecast Report updates the 2025 forecast using new input data, including recent installations of heat pumps, EVs, and solar, as well as policy and incentive changes. A hybrid impact model based on AMI data was incorporated, and heat pump water heaters were introduced as a separate end-use category in the residential model.

ons incorporated into 2026 Load Forecast. Heat Pump Water Heaters Introduced as a separate End-Use in Residential model. RTR Delayed migration, changed class distribution. Peak Model Updated based on analysis of 2026 system peak (25th Janu...

AI summary The text discusses updates to the 2026 Load Forecast, including the incorporation of heat pump water heaters as a new end-use category in the residential model, changes to the RTR migration, and an updated peak model based on the 2026 system peak analysis. These updates are part of the 2026 Load Forecast Report, with attachments filed electronically.

.7 350.2 5533.9 454.8 2303.3 360.5 3118.7 66.0 3184.6 263.7 434.8 99.4 671.6 16.9 2034 5205.2 357.3 5562.5 461.9 2328.1 360.5 3150.6 66.0 3216.5 266.3 436.3 99.4 671.6 16.9 2035 5228.5 364.4 5593.0 469.1 2354.0 360.5 3183.6 66.0 3249.6 269...

AI summary The text contains a table of numerical data and a reference to a 2026 Load Forecast Report Attachment 4, which is marked as confidential and redacted. The data appears to be related to energy forecasting but lacks context or explanation.

hybrid no hybrid difference E3 hybrid pea not captured in our model 2016 1,628 1,628 0.0 0 0.0 2017 1,825 1,825 0.0 0 0.0 2018 1,890 1,890 0.0 0 0.0 2019 1,736 1,736 0.0 0 0.0 2020 1,814 1,814 0.0 0 0.0 2021 1,654 1,654 0.0 0 0.0 2022 1,92...

AI summary The text presents a table showing data from 2016 to 2036, with columns indicating values for each year. There is a mention of a 'hybrid' and 'E3 hybrid pea' not being captured in the model. The document is labeled as a 'REDACTED 2026 Load Forecast Report Attachment 4 Page 7 of 80', indicating it is part of a larger confidential report.

9.0 54.1 60.8 68.4 2036 90.1 16.5 90.1 88.7 85.2 73.4 64.6 60.6 56.2 56.8 60.0 66.2 74.4 83.7 Peak by month 100.0% 98.4% 94.5% 81.4% 71.7% 67.2% 62.4% 63.0% 66.6% 73.5% 82.5% 92.9% REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026...

AI summary The text contains numerical data related to load forecasts and peak demand by month, with percentages indicating varying levels of demand across different months. The document is a confidential attachment from a 2026 Load Forecast Report.

51.5 47.8 48.3 51.0 56.3 42.0 47.3 2036 61.3 10.4 61.3 60.3 58.0 75.1 66.1 62.0 57.5 58.1 61.4 67.8 50.6 57.0 Peak by month 100.0% 98.4% 94.5% 122.5% 107.9% 101.1% 93.9% 94.8% 100.2% 110.5% 82.5% 92.9% REDACTED (CONFIDENTIAL INFORMATION RE...

AI summary The text contains numerical data related to load forecasts and peak demand by month, with percentages indicating variations over time. A portion of the document has been redacted, likely due to confidentiality concerns.

2035 463,364.56 469.08 519.43 494.87 434.87 2036 471,989.70 477.71 537.36 510.24 2.0% 22.1% REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 13 of 80 Small General Sales 550 500 450 G 400 W 3...

AI summary The document contains redacted data from a 2026 Load Forecast Report, including numerical values for different years and a graph comparing actuals, previous forecasts, and current forecasts for Small General Sales. The content is marked as confidential.

0 0.0 0.0 0.0 0.0 0.0 0.0 2034 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2035 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 2036 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 REDACTED (CONFIDENTIAL INFORMATION REMOVED...

AI summary The text contains a redacted section of a 2026 Load Forecast Report Attachment 4, which appears to be part of a regulatory proceeding document. The content is confidential and has been removed, making it difficult to determine the specific discussion or analysis related to load forecasting.

18.0 -35.0 19.4 2033 17.2 16.1 16.0 16.5 16.8 15.9 16.5 16.5 16.1 16.1 16.6 16.5 4.0 18.6 -45.0 20.0 2034 16.9 15.6 15.5 16.1 16.4 15.3 16.1 16.1 15.6 15.5 16.2 16.2 4.0 19.2 -55.0 20.7 2035 16.3 14.7 14.6 15.4 15.8 14.3 15.4 15.5 14.7 14....

AI summary The text presents a series of numerical data points, likely related to load forecasts for various years, with some values redacted due to confidentiality. The data includes years from 2033 to 2036 and associated numerical values, followed by a redacted section indicating a 2026 Load Forecast Report Attachment 4.

,415.08 2,256.26 2,150.21 2036 2,611,238 2,391.0 2,465.60 2,290.25 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 18 of 80 General Demand Sales 2,450 2,400 2,350 2,300 G 2,250 W 2,200 h 2,1...

AI summary The document contains redacted data from a 2026 Load Forecast Report, including tables and graphs showing general demand sales forecasts and actuals. The content is partially redacted due to confidentiality.

.1 0.1 0.1 0.1 0.1 0.1 0.1 2034 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 2035 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 2036 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 REDACTED (CONFIDENTIAL INFORMATION REMOVE...

AI summary The text contains a table with years from 2034 to 2036 and a series of 0.1 values, followed by a redacted section from a 2026 Load Forecast Report Attachment 4, Page 20 of 80. The content appears to be related to load forecasting and is marked as confidential.

268.96 270.20 259.31 260.95 2036 286,488.23 271.61 272.84 261.46 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 22 of 80 Small Industrial Sales 270 260 250 G 240 W 230 h 220 210 200 Actuals...

AI summary The text contains redacted data from a 2026 Load Forecast Report, including small industrial sales figures and forecast comparisons. The content is partially redacted due to confidentiality.

472.75 472.75 472.75 2024 489,266.92 481,961.05 489.27 489.27 489.27 2025 484,116.29 476,410.97 7.7 484.12 484.12 484.12 490.1 2026 483,407.74 488.30 489.49 488.6 462.7 2027 482,919.83 443.42 445.77 441.8 408.6 2028 481,726.30 432.99 436.7...

AI summary The text provides numerical data related to load forecasts and medium industrial sales over multiple years, including actuals, previous forecasts, and current forecasts. The data includes percentages and figures for years 2024 through 2036. The document mentions a '2026 Load Forecast Report Attachment 4' and includes a graph titled 'Medium Industrial Sales.'

2036 38.0 34 6 37 37.3 37.3 37.3 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 26 of 80 Year 2036 PHP 2050 DSMYear 2026 Forecast With Out DSM Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov De...

AI summary The text presents a load forecast report with data for the year 2036, including various categories such as residential, ETS, Res CPP, and Res TOU, with monthly and total values provided. The data is part of an attachment from a 2026 Load Forecast Report.

1007.9 2016 10 1126.6 2016 11 1332.8 2016 12 1908.1 2017 1 1825.5 2017 2 1632.6 2017 3 1668.7 2017 4 1372.6 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 30 of 80

AI summary This document presents a table with data spanning from 2016 to 2017, including monthly figures. It is part of a redacted 2026 Load Forecast Report, specifically Attachment 4, Page 30 of 80.

7 1075.1 2021 8 1141.2 2021 9 1078.4 2021 10 1179.4 2021 11 1425.3 2021 12 1802.9 2022 1 1921.0 2022 2 1892.1 2022 3 1857.8 2022 4 1393.1 2022 5 1207.0 2022 6 1086.7 2022 7 1156.1 2022 8 1116.8 2022 9 983.0 2022 10 1268.7 2022 11 1493.0 20...

AI summary The text provides a series of numerical data points, likely representing energy usage or load forecasts for various months from 2021 to 2023. The data is presented in a structured format, with years and months listed alongside corresponding values. A redacted section indicates that confidential information has been removed from the document.

9 1144.3 2027 10 1228.6 2027 11 1646.9 2027 12 1976.3 2028 1 2299.0 2028 2 2211.2 2028 3 1904.5 2028 4 1494.8 2028 5 1235.8 2028 6 1161.1 2028 7 1238.9 2028 8 1284.9 2028 9 1155.7 2028 10 1238.8 2028 11 1661.2 2028 12 1994.8 2029 1 2316.0...

AI summary The text provides a series of numerical data points, likely representing load forecasts for different years and months, followed by a redacted section indicating that confidential information has been removed from the 2026 Load Forecast Report Attachment 4.

11 1715.3 2033 12 2077.0 2034 1 2411.2 2034 2 2324.1 2034 3 2004.0 2034 4 1551.1 2034 5 1271.5 2034 6 1189.9 2034 7 1303.5 2034 8 1363.4 2034 9 1197.9 2034 10 1275.3 2034 11 1726.1 2034 12 2094.2 REDACTED (CONFIDENTIAL INFORMATION REMOVED)...

AI summary The text presents a series of numerical data points, likely related to load forecasting for the year 2034, with values corresponding to different months. The data appears to be part of a confidential report, specifically Attachment 4 of the 2026 Load Forecast Report.

94.2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 33 of 80 Year Month Pred 2035 1 2432.9 2035 2 2344.9 2035 3 2022.3 2035 4 1561.2 2035 5 1277.8 2035 6 1194.6 2035 7 1314.4 2035 8 1376.5...

AI summary The document contains a table showing load forecasts for the years 2035 and 2036, with monthly predictions for electricity demand in megawatts. The data is part of a 2026 Load Forecast Report and is redacted due to confidentiality.

685,040 1,877,400 1,292,058 0 463,200 604,800 893,825 - 129,888 28,533,774 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 38 of 80

AI summary The text contains a table with numerical data and a redacted page from a 2026 Load Forecast Report, indicating confidential information has been removed.

,999 - 1,503,264 200,460 - - - 238,757 7,339,004 2017-09-01 2017 119,919 - 1,837,584 1,092,240 - - 461,431 360,000 60,535 1,439,999 - 1,448,976 179,303 - - - 214,753 6,785,234 2017-10-01 2017 118,744 - 1,917,168 1,279,440 - - 490,884 364,5...

AI summary The text presents a series of numerical data and a redacted section from a 2026 Load Forecast Report Attachment 4, indicating that the content contains confidential information. The data appears to be related to financial and operational metrics, but the context is not fully disclosed due to redaction.

267,375 8,294,931 Aug-23 2023 172,800 - 1,799,808 1,554,980 - - 250,699 313,849 46,640 1,379,820 1,116,185 1,514,112 215,918 - - 413,858 8,778,669 Sep-23 2023 172,800 - 1,257,504 1,621,480 - - 264,446 369,776 46,535 1,315,239 976,603 1,435...

AI summary The text presents a series of numerical data entries spanning from August to December 2023, followed by a redacted section from the 2026 Load Forecast Report Attachment 4, Page 42 of 80. The data appears to be related to financial and operational metrics, but the content is heavily redacted, making it difficult to determine the exact context or discussion points.

02,917 1,296,648 - 1,649,808 164,128 934,960 1,248,158 2,611,870 - Sep-23 2023 327,200 - - 1,018,136 428,004 - - 1,649,957 1,340,208 181,944 1,284,165 1,338,797 - 1,580,040 154,045 1,098,327 1,084,023 2,609,762 - Oct-23 2023 380,000 - - 1,...

AI summary The text presents a series of numerical data and a reference to a redacted 2026 Load Forecast Report Attachment 4, indicating the presence of confidential information. The numbers appear to be related to financial and operational metrics, but no specific context or discussion is provided.

0 428,400 - - 5,840,000 2,192,900 262,800 - 1,310,179 - 1,715,088 212,742 986,287 2,211,602 2,613,162 - Nov-30 2030 491,568 - - 1,212,400 270,000 - - 5,840,000 1,761,355 223,200 - 1,133,033 - 1,580,976 155,236 934,622 1,008,780 2,610,132 -...

AI summary The text contains a table with numerical data and a redacted section from a 2026 Load Forecast Report Attachment 4, Page 49 of 80, indicating confidential information has been removed.

1,015,119 420,180 461,760 696,188 175,104 4,935,096 603,723 894,912 388,776 1,877,988 - - 588,244 54,444,955 61,883,126 2017-12-01 2017 7,944,059 8,736,000 5,836,404 3,737,329 647,837 583,476 446,400 625,218 186,432 2,368,728 408,943 911,5...

AI summary The text includes a table with numerical data and dates, followed by a redacted section from a 2026 Load Forecast Report Attachment 4, Page 50 of 80. The content appears to be part of a regulatory proceeding, but specific details are confidential and removed.

,480 600,533 765,816 307,248 2,027,046 - - 970,999 54,276,951 62,632,675 Oct-20 2020 8,234,628 9,429,280 6,776,067 3,869,618 878,732 469,428 536,064 928,728 30,492 5,169,456 542,737 862,392 203,640 1,825,656 - 268,987 57,698,785 65,274,225...

AI summary The text contains a table with numerical data and a reference to a redacted 2026 Load Forecast Report Attachment 4, Page 51 of 80. The table appears to present financial or operational metrics across different months and years.

0,560 709,284 - 797,266 268,800 2,127,422 - 50,826,793 57,521,863 Sep-26 2026 6,651,660 8,143,200 6,280,071 2,748,256 866,957 223,200 - - 790,409 732,659 14,400 2,423,520 665,073 - 673,787 336,168 1,336,896 - 45,985,459 52,367,883 Oct-26 2...

AI summary The text presents numerical data related to financial figures and load forecasts for the year 2026, including various metrics and totals. A portion of the document is redacted, indicating confidential information has been removed.

1,553,584 393,864 3,025,894 464,647 282,202 - 1 9,555,934 1,681,204 2017-08-01 2017 257,172 164,482 3,083,067 1,668,499 396,144 3,122,247 468,680 296,829 - 72,755 9,384,367 3,096,278 2017-09-01 2017 224,191 142,212 3,301,112 1,578,484 355,...

AI summary The text contains a series of numerical data entries and a redacted section from a 2026 Load Forecast Report, indicating the presence of confidential information. The data may relate to financial or operational metrics, though the specific context is not provided.

% 5.3% 5.2% 5.2% 5.2% 5.2% 5.4% 4.9% 5.3% 5.3% 5.4% Unmetered 16.3% 15.3% 12.6% 11.1% 9.4% 7.6% 8.7% 8.9% 8.9% 10.3% 13.7% 16.3% Solar Allocation EV Allocation SG 10% 20% GD 90% 80% RTR 2025 2026 2027 2028 21 352 421 Res 11.7% 2.5 41.4 49....

AI summary The text presents percentage data related to unmetered usage and allocations for solar and electric vehicles, along with load forecasts for various categories from 2025 to 2028. The data includes percentages for different categories such as residential, small generation, generation demand, and others.

2,100 2035 11939 1.0% 11939.0 11365 3166.7 3014.4 2170.4 2187.3 2036 12097 1.3% 12097.1 3213.4 2168.2 2,000 4.5% 0.4% Historic Sales Previous Forecast Current Forecast REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast...

AI summary The text contains a table with data related to load forecasts for the years 2035 and 2036, including percentages and numerical values. The content is redacted and labeled as confidential, and it references a 2026 Load Forecast Report Attachment 4.

2100 1.1% 2.2% 1.0% W 1900 1700 1500 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034 2035 2036 Historic Peak Previous Forecast Current Forecast 2026 actual REDACTED (CONFIDENTIAL INFORMATION R...

AI summary The document presents load forecast data, including historical peak values, previous and current forecasts, and a 2026 actual load value. The forecast spans from 2016 to 2036, with percentages and numerical values indicating load trends over time.

REDACTED 2026 Load Forecast Report Attachment 4 Page 71 of 80 As Stated by ENSC Loss Adjustment Commercial Residentia Codes and Residential & Industrial l Residential Commercial Industrial LED Standards Total Total Loss Loss Residential Co...

AI summary The text presents a portion of a 2026 Load Forecast Report, focusing on loss adjustment and incremental values across residential, commercial, and industrial categories. It includes data on codes, standards, and percentages related to energy loss adjustments.

22.8 165.6 10.0% 6.6% 13.5 52.4 6.2 47.0 1.1 16.0 20.8 115.4 2033.0 14.4 72.5 6.2 56.5 1.1 18.3 21.6 187.2 10.0% 6.6% 12.9 65.3 5.8 52.8 1.0 17.1 19.7 135.2 2034.0 13.6 86.1 6.3 62.8 1.1 19.4 21.1 208.3 10.0% 6.6% 12.3 77.6 5.9 58.7 1.0 18...

AI summary The text contains a series of numerical data and a redacted section from a 2026 Load Forecast Report, indicating that the content has been partially removed due to confidentiality. The numbers may relate to load forecasts, energy consumption, or other metrics relevant to the proceeding.

2,289 0.3% 260 0.2% 810 12,097 2032 5,393 0.7% 3,084 0.9% 2,173 0.0% 259 0.0% 780 11,689 2033 5,559 0.9% 3,266 1.2% 2,295 0.3% 261 0.1% 819 12,199 2033 5,408 0.3% 3,101 0.5% 2,173 0.0% 258 -0.1% 782 11,722 2034 5,649 1.6% 3,318 1.6% 2,300...

AI summary The text contains a table with numerical data and percentages, followed by a redacted section from the 2026 Load Forecast Report Attachment 4, Page 74 of 80. The data appears to be related to load forecasting and energy planning for various years.

MOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 77 of 80 Firm Peak End Use with DSM and DR Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov Dec Peak 2026 2346.2 2262.8 1949.1 1534.6 1268.1 1197.0 1276.9 1312.5 1203.0 1295.8 1703.1 2...

AI summary The document presents a load forecast report with data on firm peak end use for the years 2026 to 2036, including demand-side management (DSM) and demand response (DR) considerations. It also includes a section with redacted information and a list of items, such as 'Yes 2000 Residential' and 'No 2001 ETS'.

7 2,590 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 78 of 80 Yes 2000 Residential No 2001 ETS 2002 Small General 2003 General Demand 2004 Large General 2005 Small Industrial 2006 Medium...

AI summary The text lists various customer classes and load forecast categories, including residential, industrial, and municipal classes, as well as specific load categories such as losses and unmetered loads, spanning from 2000 to 2025.

0 2044 0 2045 0 2046 0 2047 0 2048 0 2049 0 2050 0 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Attachment 4 Page 80 of 80 Cumulative Incremental PEAK Peak Peak Jan Feb Mar Apr May Jun Jul Aug Sep Oct Nov...

AI summary The text includes a redacted portion of a 2026 Load Forecast Report and indicates that Attachments 5-10 have been filed electronically. The document contains a table with cumulative incremental peak data for various years, though the content is partially redacted.

1 Request IR-1: 18 cost impacts of the hybrid approach as part of a Department of Energy-funded hybrid 19 heating working group led by Net Zero Atlantic (NZA), involving provincial staff and other 20 stakeholders. The different scenarios w...

AI summary The text discusses the cost impacts of a hybrid heating approach modeled by a working group led by Net Zero Atlantic (NZA), involving provincial staff and stakeholders. It mentions the use of a midpoint impact forecast due to the absence of established hybrid heating programs as of the 2026 Load Forecast. The modeling work was shared with NZA and used for system capacity modeling to assess potential system benefits of hybrid heating programs.

- (x by number of hybrid HP installs). 1 Request IR-2: 2 3 Reference: Exhibit N-1, p. 41. 4 5 (a) Please provide the system-coincident unmanaged peak impact per vehicle for 2025 in 6 the same format as the response in Exh. N-2, Matter M111...

AI summary The document discusses a request for information regarding the system-coincident unmanaged peak impact per vehicle for 2025 and assumptions about managed charging participation rates. NS Power states that the data is no longer being collected, and references Synapse IR-11 for assumptions on managed charging participation rates for medium and heavy-duty vehicles.

Direct Load Control (DLC) Load Forecast Report: 2021 2022 2023 2024 2025 Actual Demand Reduction (DLC) Year 2021 0 0.0 2022 4 0 0.0 2023 12 4 4 0.1 2024 24 12 12 0 0.1 2025 36 24 24 4 4 0.9 2026 39 36 36 12 12 2.7 2027 39 39 39 24 24 n/a 2...

AI summary The table outlines the load forecast report and actual demand reduction from Direct Load Control (DLC) from 2021 to 2035. It shows the increasing number of DLC load forecasts and actual demand reductions over time, with a steady increase in demand reduction starting from 2025.

Business, Non-Profit and Institutional (BNI) Curtailment Load Forecast 2021 2022 2023 2024 2025 Actual Demand Report: Reduction (BNI) Year 2021 0 0.0 2022 1 0 0.0 2023 2 1 1 2.4 2024 4 2 2 0 8.0 2025 6 4 4 1 1 5.9 2026 7 6 6 2 2 13.0 2027...

AI summary The document presents a table showing load forecasts and actual demand reduction values for Business, Non-Profit and Institutional (BNI) curtailment from 2021 to 2035. The data is sourced from EfficiencyOne's 2025 DSM Programs Evaluation Reports and Q1 2026 Demand Side Management Report, with a note that 2026 values are tracked but not yet evaluated.

Rank Date Type Weekday/ Hour Load TOU Weekend Ending (MW) Period 1 2/21/2024 Morning Weekday 8:00 AM 2,088 Peak 2 12/22/2023 Evening Weekday 6:00 PM 2,041 Peak 3 2/20/2024 Morning Weekday 8:00 AM 2,029 Peak 4 1/29/2024 Evening Weekday 6:00...

AI summary The table presents load data for various dates and times, showing peak and off-peak load values in megawatts (MW) for different periods. It includes dates ranging from December 2023 to March 2024 and highlights the highest load values during peak hours.

NON-CONFIDENTIAL Request IR-5: Reference: Figures 9 - 14. Please provide the underlying data and charts in an excel workbook, including formulas and any workpapers used to develop Figure 11. Response IR-5: Please refer to Attachment 1. A s...

AI summary The response to Request IR-5 provides a revised version of Figure 11 from the 2026 Load Forecast Report, correcting an error in the CDD series. The original figure used a raw, trended CDD before trend reduction, whereas the revised figure reflects the corrected CDD series used in the forecast. The data and formulas are provided in Attachment 1.

2026 Load Forecast Report CA IR-5 Attachment 1 has been filed electronically. 1 Request IR-6: 2 3 Reference: Section 4.8. NS Power states that its peak forecast is unaffected by the RtR 4 load forecast. With respect to energy, NS Power is...

AI summary The document discusses the 2026 Load Forecast Report and addresses concerns regarding the impact of the RtR (Retail Tariff) load forecast on NS Power's planning and operations. NS Power clarifies that the RtR load forecast does not affect its peak demand forecast, as firm capacity contributions from Licensed Retail Suppliers are considered separately.

NON-CONFIDENTIAL 1 Request IR-1: 2 3 Reference: NS Power 2026 Load Forecast Report, page 40, lines 3-11 4 5 Based on the 2026 Load Forecast report, E1 understands that the hybrid heating 6 participation rate is based on a 50 percent adopti...

AI summary The text requests clarification and explanation from NS Power regarding the assumptions and methodology used in the 2026 Load Forecast Report, particularly concerning hybrid heating participation rates, energy and peak demand reductions, and the use of AMI data for revised estimates.

8 Reduction for Modelled Hybrid Heating in the 2026 Load Forecast. Column: A B C D E F Year Total Peak Reduction (MW) Total Energy Reduction (GWh) Hybrid HP Cumulative Participants Calculated Full Load Hours Unitary demand reduction (kW) U...

AI summary The chunk presents a table outlining projected reductions in peak load and energy usage due to hybrid heating systems from 2028 to 2036, including cumulative participants, calculated load hours, and unitary demand and energy reductions.

(a) Please explain why the modelled hybrid heating program has an average full-load hours reduction in electric space heating of 1,656, and whether this is consistent with the program's intended design? If the intended program design is no...

AI summary The text requests an explanation of the hybrid heating program's modelled average full-load hours reduction in electric space heating and asks about the program's intended design. It also inquires about the expected annual operating hours of hybrid heating systems and the assumptions used in load forecast modelling.

Response IR-2: (a) The "full load hours" metric is not used by NS Power in the hybrid heating modelling or the load forecast. The peak reduction is not achieved every hour of a modelled hybrid event; this is just the reduction at hour of s...

AI summary NS Power clarifies that 'full load hours' are not used in hybrid heating models or load forecasts. Peak reduction is only at the system peak hour, and demand reduction varies by heating intensity. The forecast assumes hybrid heating systems are operational when needed, with no single assumption set reflected in the load forecast. No existing hybrid heating program exists in Nova Scotia.

(c) Please refer to CA IR-1 part (f). Hybrid event trigger scenario Event hours CPP events 72 Temperature < -10o C 225 Top 88 NSR hours 88 1 (d) 2 (i) Based on a residential average use of 10,367 kWh for 2036 (from 2026 Load 3 Forecast Rep...

AI summary The text discusses hybrid event trigger scenarios and their associated event hours, referencing load forecasts and energy usage data. It also includes a request and response related to hybrid heating scenarios in the 2026 Load Forecast and their alignment with the Net Zero Atlantic study.

NON-CONFIDENTIAL 1 Request IR-1: 27 (d) In the 2025 Report, the peak load forecast was informed by NS Power's previously highest 28 peak, which occurred on February 4, 2023. This peak, and the subsequent forecasts, were 29 characterized by...

AI summary The text discusses the 2025 and 2026 peak load forecasts, highlighting the impact of prolonged cold spells and the updating of the peak model. It also mentions variability in year-over-year forecasts due to factors such as EV additions and electrification, and references employment data from Statistics Canada.

participation assumptions. 1 Request IR-5: In the 2025 Load Forecast Report M12349, NS Power assumed that the Municipal load would be served by a third party in 2025. However, as explained by NS Power in response to Board IR-19, on April 3...

AI summary The document discusses changes in participation assumptions related to municipal load forecasting. NS Power initially assumed third-party service for municipal load in 2025 but later learned that municipal entities would continue with bundled service in 2026. This change increased bundled load by 4 GWh and backup/top-up load by 52 GWh. The response also outlines variables used in the sensitivity analysis, including weather and economic factors.

2026 Load Forecast Report SBA IR-2 Attachment 1 has been filed electronically. 1 Request IR-1: 2 3 Refer to M12861, Exhibit N-1, Nova Scotia Power Inc. 2026 Load Forecast Report - Redacted 4 (the "Report") Section 4.1, Historical Class Sal...

AI summary The document outlines a request for Nova Scotia Power Inc. to identify criteria for incorporating AMI-based accrued sales into the Load Forecast and provide a timeline for transitioning to such data. NS Power has not established specific criteria or a timeline, citing disruptions from the 2025 cyber incident.

13 (a) Please find data locations for all figures and tables included in the 2026 Load Forecast 14 Report and appendices in the table below: Figure Location Figure 1-3, 40, 47, 51, 55-58, 65-68 2026 LFR Attachment 4, tab Graphs Figure 5-7,...

AI summary The text requests the identification of data locations for all figures and tables in the 2026 Load Forecast 14 Report and its appendices, with specific references provided in a table format. The 2026 Load Forecast Report is cited as NSEB M12861, and responses from NSPI to Synapse Energy Economics Inc. are mentioned.

PARTIALLY CONFIDENTIAL (Attachment Only) Figure Location Figure 53 2026 LFR Attachment 4, tab Medium Industrial Figure 69 2026 LFR Attachment 4, tab DR Figure 70 Synapse IR-13 Attachment 1 Figure 75-76 Synapse IR-19 Attachment 1 A1 2026 LF...

AI summary The document contains references to various figures and attachments related to the 2026 Load Forecasting Report (LFR) and Synapse energy reports, including regression breakdowns and sector summaries. These materials are part of a partially confidential attachment.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 1 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Average of large customer co incident peak load, 2015-2024 Month (MW) Jan 175 Feb 172 Mar 170 Apr 160 May 153 Jun 161 Ju...

AI summary The document presents a load forecast report with historical data on average incident peak load for large customers from 2015 to 2024, along with peak load values and HDD18 and CDD18 metrics for the year 2006 to 2008. The data includes monthly load values and heating and cooling degree days.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 12 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Year Cust Count Change in Res Customers Population Change in Population Housing Completions Starts Household Size Year...

AI summary The document presents a table showing changes in customer count, population, and household size from 2023 to 2027. It includes data for each month and year, illustrating trends in household size over time.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 24 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) General Demand Small General Residential Year -0.5 3.0 3.1 2026 1.0 3.8 3.9 2027 Year Month Res SmlGen Gen 2016 1 0.124...

AI summary The document presents a load forecast report with tables showing demand data for various years, including General Demand, Small General, and Residential demand, along with monthly load factors from 2016 to 2019. The data is part of a 2026 Load Forecast Report by Synapse IR-1.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 32 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED)

AI summary The document contains a redacted section of a 2026 Load Forecast Report, specifically Attachment 1, Page 32 of 196. A figure (Figure 2) is referenced but not displayed, and the content includes confidential information that has been removed.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 33 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED)

AI summary The document contains a redacted page from a 2026 Load Forecast Report, specifically Attachment 1, Page 33 of 196. It includes a figure labeled 'Figure 2' which is presumably related to load forecasting data, though the content is confidential and has been redacted.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 34 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 2024 2025 billed 2025 accrued 2026 Forecast Sales 4830 5180 5289 5289 5315 Residential Weather variance -126 -104...

AI summary The document presents a load forecast report with data on forecast sales, actual sales, and weather-adjusted sales from 2023 to 2026. It includes monthly residential weather-normalized (WN) energy usage in kWh for various months and years, providing insights into energy consumption trends.

SUMMARY OUTPUT Regression Statistics Multiple R 0.81801092 R Square 0.66914186 Adjusted R Square 0.66905068 Standard Error 143.091653 Observations 14520 df SS MS F Significance F Regression 4 601065795.8 150266449 7338.94 0 Residual 14515...

AI summary The document presents statistical regression analysis with a focus on load forecasting, including coefficients for variables like wind, 12-hour average temperature, and weekdays. It includes forecasted and actual peak loads for 2025 and 2026, as well as temperature and load data for specific dates in 2022.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 189 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Item 2026 NSR Energy (GWh) 2026 Firm Peak (MW) 2036 NSR Energy (GWh) 2036 Firm Peak (MW) 2025 Load Forecast 11,403 2,2...

AI summary The text presents load forecast data for Nova Scotia, including energy consumption (GWh) and firm peak demand (MW) for 2026 and 2036 under various scenarios. It also includes historical load data from 2016 to 2021, detailing interruptible contributions, demand response reductions, and temperature conditions during peak load periods.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 192 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast 2019 5.9% 10.6% 0.8...

AI summary The document presents a load forecast report with statistical data on forecast accuracy and error percentages over various lead times. It includes historical load forecasts issued from 2015 to 2024 and their corresponding values, along with metrics like average percent error and MAPE.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 196 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Item 2026 Energy (GWh) 2026 Peak (MW) 2036 Energy (GWh) 2036 Peak (MW) Included in Forecast DSM (base case) -116 -19 -...

AI summary The document presents a 2026 Load Forecast Report, highlighting the impact of various factors on energy demand and peak load, including demand-side management, solar PV, electric vehicles, hydrogen production, battery storage, and price elasticity. The report includes multiple scenarios and confidence intervals for the years 2026 and 2036.

2026 Load Forecast Report (NSEB M12861) NSPI Responses to Synapse Energy Economics Inc. Information Requests Request IR-2: System Peak (a) Refer to Table 1 in the Board Decision regarding NS Power's 2025 Load Forecast (M12349). Please expl...

AI summary The 2026 Load Forecast Report (NSEB M12861) discusses the factors affecting peak demand forecast accuracy between 2019-2024, including temperature, wind, timing, and large customer/interruptible load. The report highlights that 2023 had the highest unexplained error due to extreme conditions, while 2020 and 2021 showed deviations due to the impact of the COVID-19 pandemic.

NON-CONFIDENTIAL 1 extreme peaks (while a couple of the variants considered forecast one peak better than the 2 version used in the 2026 Load Forecast, no variant managed to forecast both peaks as 3 closely), and the model stats are not ma...

AI summary The text discusses the limitations of load forecasting models, noting that while some variants predict one peak better than the 2026 Load Forecast, none accurately predict both peaks, and model statistics are not significantly different across variants.

7 (c) The analysis outlined in the Report, and subsequent model tests, provided evidence to 8 suggest that the magnitude of the January 2026 peak was at least in part due to the 9 prolonged period of cold, as opposed to just the temperatur...

AI summary The analysis in the report indicates that the January 2026 peak demand was influenced by a prolonged cold period, not just the 12-hour temperature leading up to the peak. Electrification is expected to increase future peak demand, with its effects incorporated into the peak model through heat use, cool use, and other use variables, as well as growth programs.

NON-CONFIDENTIAL 1 and collect heat pump and total house hourly load data, and measure heat-pump 10 range within which the -48 MW peak mitigation estimate falls, based on NS 11 Power's hybrid heating modelling work. The -48 MW value is con...

AI summary The text discusses NS Power's hybrid heating modelling work, which estimates peak mitigation and energy reduction based on varying customer participation rates. The -48 MW peak mitigation estimate was retained for the 2026 Load Forecast, and the median model result for 50% participation was used for energy reduction calculations.

2026 Load Forecast Report (NSEB M12861) NSPI Responses to Synapse Energy Economics Inc. Information Requests

AI summary This document outlines NSPI's responses to information requests from Synapse Energy Economics Inc. regarding the 2026 Load Forecast Report (NSEB M12861), providing insights into load forecasting and energy planning.

2026 Load Forecast Report Synapse IR-8 Attachment 1 has been filed electronically.

AI summary The 2026 Load Forecast Report Synapse IR-8 Attachment 1 has been filed electronically as part of the regulatory proceeding.

2026 Load Forecast Report Synapse IR-9 Attachment 2 has been filed electronically.

AI summary The 2026 Load Forecast Report Synapse IR-9 Attachment 2 has been filed electronically as part of the regulatory proceeding.

2026 Load Forecast Report Synapse IR-19 Attachment 1 Page 1 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Year Actuals p10 p50 p90 7 8 (b) For the XCool variable please provide the underlying factors (penetration, usage, etc.) 9 driving...

AI summary The 2026 Load Forecast Report discusses heat pump (HP) share forecasts for heating and cooling, noting significant growth from 2026 to 2036. It also mentions that OtherUse variables remain stable over a 10-year period, with factors such as household size, price, seasonal use patterns, and employment compensation influencing these variables.

II. Introduction and Summary - Q: Please summarize the topics you will address in your review of the 2026 Load Forecast Report. - A: My evidence reviews several technical or program-based adjustments to the base load forecast that I find d...

AI summary The review of the 2026 Load Forecast Report identifies several issues with technical and program-based adjustments, particularly the residential heating intensity forecast and forecasts for demand reduction programs. The reviewer recommends immediate corrections and improvements to forecasting practices, including revising forecast workbooks, rejecting the current hybrid heating forecast, and adjusting DLC, TVP, and BNI curtailment forecasts.

Q: Has NS Power used a consistent heating intensity forecast over the past several years? A: No. NS Power's residential heating intensity forecasts have varied considerably over the past several years. In its 2024 Load Forecast Report, NS...

AI summary NS Power has not used a consistent heating intensity forecast over the past several years. Forecasts have varied significantly, with a 40% increase in residential heat pump heating intensity in 2024, followed by a reversal in the 2026 report, where the actual residential heating intensity dropped from 1,849 kWh/house to 1,655 kWh/house.

A: First, looking at NS Power's various forecasts for 2033, it is evident that NS Power's heating intensity forecast in this load forecast has returned almost to the level projected in 2023. The concept that heat pumps were responsible for...

AI summary The analysis discusses NS Power's updated heating intensity forecasts for 2033, noting that they have returned to levels projected in 2023. The initial claim that heat pumps were responsible for unallocated variance in the 2024 report has been omitted by NS Power.

Q: What is your recommendation? A: I will discuss the hybrid heating forecast in more detail in the next section of my evidence. With respect to the data problems, I recommend that the Board direct NS Power to revise its load forecast work...

AI summary The witness recommends that the Board direct NS Power to revise its load forecast workbooks to clearly identify factors used in formulas and their sources or justifications. They emphasize the importance of documentation for transparency and clarity, especially when data-driven models are not feasible.

Q: What is your recommendation to the Board? A: The Board should immediately reject NS Power's flawed residential hybrid heating forecast as unsupported by facts or sound reasoning. Normally, it would be reasonable for the Board to direct...

AI summary The respondent recommends that the Board reject NS Power's residential hybrid heating forecast due to its lack of factual support and sound reasoning. They suggest using NS Power's proposed hybrid heat pump adoption rate and energy savings data as a temporary basis for a more accurate forecast, while urging the use of AMI data for a comprehensive review by 2027.

V. Demand Reduction Forecasts - Q: Please summarize the demand reduction forecasts developed by NS Power. - A: NS Power forecasts demand reduction due to Direct Load Control (DLC), Time Variable Pricing (TVP) and business, non-profit and i...

AI summary NS Power forecasts demand reduction from DLC, TVP, and BNI programs, based on the 2022 Evergreen IRP and updated DSM plans. However, the DLC forecast is criticized for overestimating actual reductions over the past four years, with a recommendation to reduce the 2032 DLC forecast to 4 MW until evidence supports a higher forecast.

1 Table 4: Direct Load Control (DLC) Forecasts from 2021-2026 Reports (MW) Actual 2021 2022 2023 2024 2025 2026 Demand Reduction 2021 0 0.0 2022 4 0 0.0 2023 12 4 4 0.1 2024 24 12 12 0 0.1 2025 36 24 24 4 4 0.9 2026 39 36 36 12 12 5 2.7 20...

AI summary Table 4 presents forecasts for Direct Load Control (DLC) demand reduction from 2021 to 2036, showing increasing DLC capacity over time with some fluctuations in later years.

Q: What do you recommend? - A: Because the trend is not likely to force annual HDD to 0 or cause CDD to increase to unrealistic levels, the damping method should be removed in the 2027 load forecast. It is not supported by any evidence and...

AI summary The respondent recommends removing the damping method from the 2027 load forecast, as it is not supported by evidence and does not address a modeling problem. The trend in HDD and CDD is not expected to reach extreme levels, making the damping method unnecessary.

- "Making the Most of the Power Plant Market: Best Practices for All-Source Electric Generation Procurement," Indiana State Bar Association, Utility Law Section, Virtual Fall Seminar, September 2020. - "Resource Adequacy, Reserve Margin, &...

AI summary The document lists various presentations and seminars related to energy and utility topics, including power plant market practices, resource adequacy, real-time pricing, load forecasting, and energy transition challenges. These events were hosted by organizations such as the Indiana State Bar Association, The Energy Authority, and NERC.

y of Colorado's 2021 general rate case (phase 1) on behalf of Energy Outreach Colorado. Reasonableness of capital project costs, choice of test year, adjustment to load to reflect effects of pandemic. 2022 California PUC Docket A.21-05-017...

AI summary The text outlines expert testimony in various regulatory proceedings, including general rate cases and load forecast reports, focusing on topics such as cost allocation, economic analysis, and alignment with regulatory plans. It highlights involvement in Nova Scotia and California regulatory matters, emphasizing cost controls, program scale, and load forecasting.

Evidence Regarding Nova Scotia Power's 2026 Load Forecast Evidence RE: M12861 Prepared for the Nova Scotia Energy Board July 21, 2026

AI summary This document provides evidence related to Nova Scotia Power's 2026 load forecast, prepared for the Nova Scotia Energy Board on July 21, 2026, and is associated with matter number M12861.

Synapse Energy Economics Inc. (Synapse) presents this evidence to document its review of the 2026 Load Forecast Report [1](#page-2-0) (Report) of Nova Scotia Power, Inc. (NS Power), and to offer recommendations for improvements. Synapse ha...

AI summary Synapse Energy Economics Inc. reviews NS Power's 2026 Load Forecast Report, noting higher net system requirements and peak levels compared to 2025. Key drivers include increased EV load, electric heating, and new customer growth. Changes in heating and cooling efficiency models, along with fewer heat pump installations, also influence the forecast. The peak model now includes a 24-hour lagged temperature variable.

Source: Synapse from Appendix A Table A2, 2025 Load Forecast and 2024 IR Response 1 Table 2. 2026 Peak contribution components (MW) Modeled Peak (MW) Res Heat (MW) EV (MW) DR (MW) Hybrid (MW) C&I Elect. (MW) Large Cust. (MW) DSM (MW) Firm...

AI summary The document presents a table showing the 2026 and 2036 peak contribution components in Nova Scotia, including modeled peak demand, residential heating, EV load, demand response, and DSM impacts. It also highlights the accuracy of NS Power's firm peak forecasts, noting inconsistencies in over- and under-forecasting over the past five years.

Recommendations NS Power should continue to monitor the impact of trade policy and consider explicitly incorporating tariff impacts into its future forecast if they are expected to have a material impact on load growth. Concerning the adju...

AI summary NS Power is advised to monitor trade policy impacts on load growth and incorporate tariff effects into future forecasts. It should also track actual housing completions and consider bank forecasts for potential revisions to load projections.

4. PEAK FORECAST NS Power forecasts the system peak by first producing a modeled peak from historical data and economic and demographic projections, then applying a series of adjustments — residential heating, EVs, demand response, hybrid...

AI summary NS Power forecasts the system peak using historical data, economic projections, and adjustments for factors like heating, EVs, and DSM. The forecast shows a 1.1% annual growth in peak demand from 2026 to 2036. A revised model incorporating a 24-hour lagged temperature variable improved accuracy, reducing unexplained variance from 78 MW to 36 MW for the 2026 peak. However, the model's performance may depend on interactions between variables, suggesting the need for more sophisticated forecasting methods.

Peak charging loads NS Power states that it is not explicitly modeling managed charging for light-duty at-home charging.[15](#page-17-1) In doing so, NS Power is not accounting for any projected changes in managed charging penetration over...

AI summary NS Power is not explicitly modeling managed charging for light-duty at-home charging and uses a coarse assumption that BEV and PHEV peak impacts are the same, which is problematic. It is recommended that PHEV charging be removed from DCFC and workplace L2 peak modeling.

Solar generation NS Power forecasts new PV generation separately from its SAE modeling. Solar generation can either be small-scale at the customer level, or larger utility-scale. The load forecast considers the customer-level impacts of di...

AI summary NS Power forecasts increased solar generation, but at a slower rate than previously projected, due to lower-than-expected installations and the removal of residential incentives. The load forecast includes a net reduction in residential and commercial energy demand. Solar coincidence factors are maintained from the 2025 forecast, pending updated data for the 2027 forecast.

Battery storage Battery storage is not incorporated into the load forecast. Prior load forecast reports have included illustrative estimates showing limited potential peak impacts from batteries, but further analysis is needed to evaluate...

AI summary Battery storage is not currently included in load forecasts, with limited potential for peak shaving. NS Power highlights high costs as a barrier to adoption, though expects this to change as battery technology improves and costs decline.

2026 Load Forecast Report NS Power Rebuttal Evidence September 8, 2026 NON-CONFIDENTIAL

AI summary This document is the 2026 Load Forecast Report, containing NS Power's rebuttal evidence submitted on September 8, 2026. The report is non-confidential and pertains to load forecasting discussions.

the CA. Submissions were filed by the SBA. DATE FILED: September 8, 2026 Page 3 of 23 Nova Scotia Wholesale and Renewable to Retail Electricity Market Rules, effective 2007 02 01, amended 2016 06 01. M12861, NSEB, Hearing Order, 2026, Load...

AI summary NS Power has agreed to intervenor recommendations, including incorporating Advanced Metering Infrastructure (AMI) data into forecasting activities. This is described as a long-term process requiring data assessment and model development. The More Access to Energy Act outlines the IESO-NS's responsibilities in forecasting electricity demand and resource adequacy.

DATE FILED: September 8, 2026 Page 12 of 23 M12861, N-8, John D. Wilson, Direct Evidence of John Wilson on behalf of the Consumer Advocate, NS Power 2026 Load Forecast Report, July 21, 2026, page 3, lines 12-17. appropriate for this additi...

AI summary The document discusses discrepancies in the 2026 Load Forecast Report regarding residential heating intensity values for customers with and without heat pumps. The Consumer Advocate's evidence is reviewed, and clarification is requested for the interpretation of these values in the context of heat pump saturation levels.

NS Power Response: NS Power does not agree with Mr. Wilson's recommendation. - The residential hybrid heating forecast is based on analysis of AMI data for over 20,000 - electrically-heated NS Power customers and a study of actual heat pum...

AI summary NS Power disagrees with Mr. Wilson's recommendation regarding the residential hybrid heating forecast, citing a reasonable basis for the forecast based on AMI data and prior load forecasts. Synapse supports NS Power's methodology, and the NZA Hybrid Heating Working Group agrees it is reasonable. NS Power argues that the forecast should not be rejected and that the IRP process will appropriately assess hybrid heating impacts.

M12861, N-8, John Wilson Evidence, page 8, lines 25-32 and page 9, lines 1-2. on the difference between E3's hybrid and non-hybrid scenarios. This adjustment would allow NSPI to incorporate the mitigating effects of hybrid heating while pr...

AI summary The text discusses recommendations for improving NSPI's load forecasting by incorporating hybrid heating effects and validating assumptions using AMI data. It emphasizes the importance of modeling hybrid electric heating explicitly and using empirical data to enhance forecast accuracy and transparency.

NS Power Response: NS Power agrees that modeling the impact of hybrid heat pumps should be included in the underlying residential intensity calculations and will update the calculations accordingly for 2026. Where possible [emphasis added]...

AI summary NS Power agrees to include hybrid heat pump modeling in residential intensity calculations for 2026 and will use AMI data where possible. They also agree to develop the capability to model hybrid commercial heating in future forecasts but not for 2026. NS Power disputes the claim that their hybrid heating forecast contradicts the Board's directive in the 2025 Load Forecast Report proceeding.

May 15, 2026 Ms. Crystal Henwood Regulatory Affairs Officer/Clerk Nova Scotia Energy Board 1601 Lower Water Street, 3rd Floor P.O. Box 1692, Unit “M” Halifax, NS B3J 3S3 Re: 2026 Load Forecast and 10 Year System Outlook Reports – IESO Nova...

AI summary The letter discusses the transition of responsibility for preparing the 2026 Load Forecast and 10 Year System Outlook (10YSO) reports from Nova Scotia Power Inc. (NS Power) to the newly established Independent Energy System Operator of Nova Scotia (IESO Nova Scotia), noting upcoming submission deadlines and implications for continued ownership of these filing requirements.

2026 M12861 NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The Public Utilities Act IN THE MATTER OF: The Nova Scotia Power Incorporated’s 2026 Load Forecast Report NOTICE OF INTERVENTION OF: K + S Windsor Salt Ltd. CKF Inc. Crown Fibre Tube I...

AI summary The Industrial Group (comprising multiple large/medium industrial companies) intervenes in the Nova Scotia Power Incorporated (NSPI) 2026 Load Forecast Report proceeding under the Public Utilities Act. Their costs are directly impacted by NSPI's application, and they seek to address issues determined by the Energy Board.

Matter No. M12861 NOVA SCOTIA ENERGY BOARD IN THE MATTER OF: The Public Utilities Act, R.S.N.S. 1989, c. 380 as amended – and – IN THE MATTER OF: Nova Scotia Power Incorporated’s 2026 Load Forecast Report NOTICE OF INTERVENTION TO: The Nov...

AI summary Port Hawkesbury Paper LP (PHP) seeks intervenor status in proceedings regarding Nova Scotia Power Inc.'s 2026 Load Forecast Report, citing its interest as a major power purchaser under the ELIADC Tariff. The notice outlines PHP's business operations and contact details for the proceeding.

Matter No. M12861 Nova Scotia Utility and Review Board IN THE MATTER OF: The Public Utilities Act IN THE MATTER OF: NS Power 2026 Load Forecast Report NOTICE OF INTERVENTION: Renewall Energy Inc TAKE NOTICE that Renewall Energy Inc. reques...

AI summary Renewall Energy Inc. intervenes in the NS Power 2026 Load Forecast Report proceeding, focusing on assumptions in the report and interactions between the Renewable to Retail (RTR) market and public utility markets. The intervention highlights concerns about the RTR program's role and its implications for the broader energy market.

2026 M12861 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 Incorporated’s 2026 Load Forecast Report NOTICE OF INTERVENTION OF: SOLAR NOVA SCOTIA To...

AI summary Solar Nova Scotia, a non-profit promoting solar energy and distributed resources, intervenes in Nova Scotia Power’s 2026 Load Forecast Report proceeding. They seek involvement in electricity system planning and distributed energy resource discussions, requesting communication updates via Dave Brushett, their chair.

M12861 NOVA SCOTIA ENERGY BOARD IN THE MATTER OF the PUBLIC UTILITIES ACT -and- IN THE MATTER OF NOVA SCOTIA POWER INCORPORATED’s 2026 Load Forecast Report LIST OF PARTICIPANTS NOVA SCOTIA POWER INC. (NS Power) Jessie Wallace 1223 Lower Wa...

AI summary The Nova Scotia Energy Board proceeding (M12861) involves NS Power's 2026 Load Forecast Report under the Public Utilities Act. Key participants include NS Power, Board Counsel, and Synapse Energy Economics, Inc., with contact details provided for regulatory stakeholders.

- Report Tables and Graphs - a. Please provide in electronic spreadsheet format all tables and graphs with identification of the data source(s) that appear in the load forecast report and appendices, retaining all formulas and calculations...

AI summary The request is for the submission of all tables and graphs from the load forecast report and appendices in electronic spreadsheet format, including data sources, formulas, and calculations. Existing tables and graphs in attachments should be referenced accordingly.

Request IR-8: Residential Hybrid Heating (Section 4.5.2, p. 37-42) - a. Refer to the following statements in the 2026 Load Forecast Report: "The 2026 residential SAE regression model has been updated to include peak and energy reductions r...

AI summary Request IR-8 focuses on residential hybrid heating analysis by NS Power, including data on load shapes, participation rates, modeling approaches, and documentation related to the 2026 Load Forecast Report. It asks for detailed explanations and supporting evidence regarding the impact of hybrid heating programs on energy and peak demand.

Request IR-11: provided by E1." - Electric Vehicles (EVs) (Section 4.5.4, p. 44-47) - a. Please provide the source data and calculations behind Figures 28-30. - b. Please specify the share of EVs in the forecast which are light-duty, non-p...

AI summary Request IR-11 seeks detailed information on Nova Scotia Power's load forecast for electric vehicles, including data sources, methodology, assumptions, and how changes in mandates and incentives have influenced the forecast. It also asks about the inclusion of managed charging and the use of AMI data in future forecasts.

1 (d) If hybrid heating does not achieve the forecast reductions, what is the quantified impact 2 on the Net System Requirement and system peak? Please provide the forecast with and 3 without hybrid heating for each year from 2028 to 2036....

AI summary The text requests explanations regarding the modelled hybrid heating program's impact on energy use, alignment with the Net Zero Atlantic study, and evidence supporting specific assumptions such as participation rates and program launch dates. It also asks for detailed tables outlining various scenarios.

2 Reference: NS Power 2026 Load Forecast Report, Section 4.2 3 - 4 (a) The Load Forecast describes significant data quality issues arising from the NS Power cyber 5 incident, including the need to estimate 2025 billing data and large custo...

AI summary The text raises concerns about data quality in NS Power's 2026 Load Forecast, specifically related to the cyber incident affecting AMI data and the use of outdated 2022 data for load shape analysis, questioning its representativeness given changes in heat pump usage and customer behavior.

20 Request IR-2: 22 Reference: Exhibit N-1, p. 41. - 24 (a) Please provide the system-coincident unmanaged peak impact per vehicle for 2025 in 25 the same format as the response in Exh. N-2, Matter M11108, CA RIR-3. - 27 (b) Please provide...

AI summary Request IR-2 seeks data on system-coincident unmanaged peak impact per vehicle for 2025 and assumptions about managed charging participation rates by vehicle type, referencing Exhibit N-1 and Matter M11108. The request aligns with load management and demand-side management themes.

9 Request IR-4: 11 Reference: Exhibit N-1, Section 10.7. - 13 (a) NS Power states that the relationship between peak load and sales does not hold for 14 non-residential classes due to "weather sensitivity and more heterogeneous load 15 pro...

AI summary The proceeding questions NS Power about the relationship between peak load and sales, the impact of AMI data on analysis, and the feasibility of using multiple peak events for better baseline estimates. It challenges NS Power's claim that non-residential load profiles are weather-sensitive and heterogeneous, suggesting residential load timing may distort peak load-sales correlations.

Refer to M12861, Exhibit N-1, Nova Scotia Power Inc. 2026 Load Forecast Report - Redacted (the "Report") Section 4.1, Historical Class Sales and Energy Data, page 18 of 105, Lines 10-13 and respond to the following: a) Please identify and...

AI summary The document requests Nova Scotia Power to identify the criteria, thresholds, and data requirements for determining a sufficient historical dataset of AMI-based accrued sales for the Load Forecast and to provide the expected timeline for transitioning to AMI-based accrued sales.

Request IR-6: Refer to M12861, Exhibit N-1, the Report, Section 4.5.4, Electric Vehicles (EVs), page 46 of 105 and respond to the following: a) Please explain the basis for retaining the same per-vehicle energy consumption, charging behavi...

AI summary The document requests explanations regarding the assumptions used in the 2025 Load Forecast for electric vehicles and the weighting scheme for temperature lags in a peak model. It also asks for the results of sensitivity analyses using longer temperature lags.

2 Refer to M12861, Exhibit-N1-Nova Scotia Power Inc. 2026 Load Forecast Report (filed May 15, 3 2026) (the "Report"), Figure 37, and respond to the following: - 4 - 5 a) Figure 37 shows cumulative industrial electrification of only 14 GWh...

AI summary The text requests clarification on Nova Scotia Power Inc.'s 2026 Load Forecast Report regarding industrial electrification levels and their alignment with net-zero goals and federal strategies. It questions the consistency of the forecast with environmental legislation and the impact of industrial electrification on electricity demand.