Topic:"Forecasting Methodology" 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.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides projections for electricity demand in Nova Scotia, informing grid planning and resource allocation. Key themes include forecasting methodologies and infrastructure planning to meet future energy needs.

LIST OF FIGURES 1 Figure 1: Historical and Predicted Annual Net System Requirement ............................................ 9 2 Figure 2: Historical and Predicted Annual System Peak ........................................................

AI summary The document lists figures related to historical and projected energy demand, system peak loads, heating and cooling degree days (HDD/CDD), and customer load trends, providing data for analysis in a regulatory proceeding.

.. 27 15 Figure 15: Yearly Change in Customers, Population, and Housing Completions........................ 29 16 Figure 16: Yearly Change in Residential Customers.................................................................... 30 17 F...

AI summary The text lists figures analyzing customer trends, economic drivers (residential, commercial, industrial), energy forecasts (heat pumps, EVs, hybrid heating), and load modeling scenarios. It focuses on data visualization for regulatory proceedings, including residential and commercial energy demand projections.

................................................................ 61 43 Figure 42: Comparison of Forecast to Actuals ............................................................................. 62 DATE: May 15, 2026 Page 4 of 105 REDACTED...

AI summary The document is a redacted 2026 Load Forecast Report, dated May 15, 2026, and appears to be part of a regulatory proceeding. It includes references to forecast comparisons and page numbering, though most content is confidential.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides projections for electricity demand in Nova Scotia, informing grid planning and resource allocation. Key themes include forecasting methodologies and infrastructure planning to meet future energy needs.

1 Figure 43: Historical and Forecast Annual Residential Sales....................................................... 63 2 Figure 44: Building Characteristics and Structural Index................................................................

AI summary The text lists figures depicting historical and forecasted annual sales data across residential, commercial, industrial sectors, and other metrics like NSR. Visuals include breakdowns of sales components, growth trends, and variance analysis for energy sectors in Nova Scotia.

.......................................................................... 81 16 Figure 58: Forecast Components .................................................................................................. 82 17 Figure 59: Average pea...

AI summary The text lists figures related to forecasting components, peak demand analysis, regression models, and demand response. It includes visual representations of forecasted vs. actual peaks, temperature records, peak normalization models, and end-use demand breakdowns, likely supporting regulatory analysis of energy system reliability and efficiency measures.

.............................................................. 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.

1 1. EXECUTIVE SUMMARY 2 3 In accordance with the Nova Scotia Wholesale Electricity and Renewable to Retail Market Rules, 4 Nova Scotia Power Incorporated (NS Power, the Company) is required to provide the Nova Scotia 5 Energy Board (NSEB,...

AI summary Nova Scotia Power (NS Power) is required to submit annual 10-year energy and demand forecasts to the Nova Scotia Energy Board (NSEB). The Independent Electrical System Operator Nova Scotia (IESO-NS), established under the Energy Reform (2024) Act, will oversee electricity demand forecasting. The 2026 Load Forecast considers factors like weather, economic indicators, and energy efficiency programs, acknowledging inherent uncertainties.

tcomes. In electricity 26 forecasting, much of this uncertainty is due to the impact of variations in weather, energy 27 efficiency program activities, the health of the economy, government policy, the impact of 28 electrification, changes...

AI summary NS Power uses Statistically Adjusted End-Use (SAE) models to forecast load, projecting increased Net System Requirement (NSR) due to lower solar generation estimates and higher Electric Vehicle (EV) penetration. Growth is driven by new customers, heating, and EVs, offset by solar, Demand Side Management (DSM), and Renewable to Retail (RTR) initiatives.

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.

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

AI summary The document is a redacted 2026 Load Forecast Report, with confidential information removed. It focuses on energy load projections for Nova Scotia, though key details are obscured.

1 2. INTRODUCTION 2 3 NS Power develops an annual forecast of energy sales and peak demand requirements which is 4 used to assess the effects of end-use and economic factors on the future power system load and 5 load shape. The forecast is...

AI summary NS Power's 2025 Load Forecast Report was reviewed by the NSEB through a paper hearing process, with intervenors including industry groups, advocates, and Energy Storage Canada. The Board acknowledged NS Power's model improvements in response to policy changes affecting electrification and technology adoption, while affirming the value of intervenor input.

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

AI summary The document is a redacted 2026 Load Forecast Report, with confidential information removed. The content is not accessible due to redaction, but the report's existence is noted as part of regulatory proceedings.

1 into the unexplained variance between forecast sales and actual sales for the 2 residential sector. 3 4 The Board finds that NS Power has taken steps to strengthen its forecasting model 5 through targeted adjustments made in response to...

AI summary The Nova Scotia Energy Board acknowledges NS Power's efforts to improve residential sector forecasting by adjusting models in response to government policy changes affecting electrification and technology adoption. NS Power is directed to compare economic forecasts from the Conference Board of Canada with major banks' projections and Statistics Canada data to enhance forecast accuracy.

recast to actual, and Signal49’s forecast has been 27 compared against those produced by Canada’s five major banks. Please refer to Section 28 4.4. 29 • The impact of potential trade tariffs is not included in the economic forecast establi...

AI summary The document references Signal49 Research's (now The Conference Board of Canada) economic forecasts, noting trade tariffs' impact was excluded. NS Power adjusted 2026 housing forecasts based on Signal49's data. Cross-references include M12349 and the NSEB Board Decision 2025 Load Forecast Report.

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.

28 • Peak model updates. 29 DATE: May 15, 2026 Page 14 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 Following the stakeholder session, the 2026 Load Forecast was updated to reflect the Demand Side...

AI summary The 2026 Load Forecast Report was updated following a stakeholder session, incorporating EfficiencyOne’s 2027-2031 Plan Application and NS Power’s 2026/2027 rate changes from their GRA Compliance Filing. These adjustments reflect revised demand-side management and demand response figures.

f 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 3. FORECASTING APPROACH 2 3 NS Power continues to use a set of SAE models for the Residential 5 and Commercial 6 rate classes, 4 an econometric model fo...

AI summary NS Power uses SAE models for residential and commercial classes, econometric models for industrial classes, and customer surveys for large industrial customers. The SAE model combines econometric and end-use methodologies, incorporating factors like efficiency trends, population changes, and economic indicators into forecasts.

and 20 growth. Structural changes are captured in the residential forecast model through the SAE model 21 specifications. Figure 4 shows the general forecast approach used in the SAE models. 22 5 References to the Residential class include...

AI summary The document discusses the 2026 Load Forecast Report, highlighting the use of the Statistically Adjusted End-Use (SAE) model for residential forecasts and structural changes in the model. Figure 4 illustrates the general forecast approach within SAE models.

Page 17 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 4. DISCUSSION OF MAJOR INPUTS 2 3 4.1 Historical Class Sales and Energy Data 4 5 The Load Forecast is developed using NS Power’s “billed” sales...

AI summary The 2026 Load Forecast Report discusses the use of 'billed' sales data over 'accrued' sales for forecasting, noting discrepancies due to billing delays. It outlines reliance on Advanced Metering Infrastructure (AMI) data to improve accuracy, with a transition to AMI-based accrued sales pending sufficient historical data. Monthly billed sales from 2016–2024 and system hourly load data from 2016–2025 are used for forecasts.

l system monthly energy and monthly demand data is 22 derived from system hourly load data for the period January 2016 to December 2025. Large 23 customer peak demand is forecast separately. 24 DATE: May 15, 2026 Page 18 of 105 REDACTED (C...

AI summary The document outlines that monthly energy and demand data is derived from hourly load data spanning January 2016 to December 2025, with large customer peak demand forecasted separately. This forms part of the 2026 Load Forecast Report, though specific details are redacted.

load consistent with the process used in previous years. 24 • The non-PHP large customer load at peak hour was averaged by month across the 10-year 25 period. 26 27 The resulting estimated average monthly large customer coincident peak loa...

AI summary The 2026 Load Forecast Report estimates large customer coincident peak loads by averaging monthly data from 2015-2024. Actual 2025 peak loads show strong correlation (R²=0.98) with these estimates, validating the methodology for forecasting future load patterns.

Page 21 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED 1 CDD, as shown in Figure 7 below, are calculated using 10 years of actual weather data covering 2 the period January 2016 to December 2025. The...

AI summary The 2026 Load Forecast Report analyzes heating degree days (HDD) and cooling degree days (CDD) trends using 10 years of weather data (2016-2025). It identifies a warming trend with HDD decreasing by ~15/year and CDD increasing by ~1.4/year, applying regression analysis to project future load requirements.

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

AI summary The document is a redacted 2026 Load Forecast Report, with confidential information removed. The content is not accessible due to redaction, but the report's existence is noted as part of regulatory proceedings.

1 Household Size decreased steadily from 2000 to 2016 as population growth stagnated while new 2 housing continued to increase. From 2016 to 2022, the average household size was steady around 3 2.2, but between 2022 and 2024 household size...

AI summary The text discusses changes in household size over time and the evolution of forecasting models for commercial and industrial sectors, including updates to the medium industrial model based on data from Signal49 and Statistics Canada. The models now use a weighted variable incorporating manufacturing GDP and employment, improving statistical significance.

to the model used 21 for the 2025 Load Forecast (adjusted R squared of 0.894 for 10 years vs. 0.688 for 18 years in the 22 2025 model). Figure 18, Figure 19 and Figure 20 summarize the economic drivers, on an annual 23 basis, used in the 2...

AI summary The 2026 Load Forecast Report discusses the model used for forecasting, highlighting an adjusted R squared value of 0.894 for a 10-year period compared to 0.688 for an 18-year period in the 2025 model. The report includes figures that summarize economic drivers on an annual basis, with financial variables adjusted to constant dollars to eliminate inflation effects.

2.4 -0.5 2 3 The major Canadian banks provide short term (1-2 year) forecast for some of the key economic 4 indicators, and these are provided in Figure 21. Signal49’s forecast is in line with the forecasts 5 from the banks. 6 DATE: May 15...

AI summary The text references economic forecasts provided by major Canadian banks and Signal49, which align with the banks' short-term (1-2 year) projections for key economic indicators. The document is part of a 2026 Load Forecast Report, though it is redacted and contains confidential information.

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.

Page 40 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, based on historical data and forecasting methodologies.

Page 48 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 data on load forecasting methodologies, assumptions, and potential impacts on the electricity system.

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

AI summary The document is a redacted 2026 Load Forecast Report, with confidential information removed. It focuses on energy load projections for Nova Scotia, though key details are obscured.

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

AI summary The document is a redacted 2026 Load Forecast Report, with confidential information removed. The content is not accessible due to redaction, but the report's existence is noted as part of regulatory proceedings.

orecast Current Forecast 18 DATE: May 15, 2026 Page 63 of 105 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026 Load Forecast Report REDACTED

AI summary The 2026 Load Forecast Report provides an updated projection of electricity demand for the year 2026, with details redacted due to confidentiality. The report is part of a regulatory proceeding and includes forecast data relevant to energy planning and resource allocation.

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

AI summary The document is a redacted 2026 Load Forecast Report, with confidential information removed. The content is not accessible due to redaction, but the report's existence is noted as part of regulatory proceedings.

o RTR decreases class load in 2027 and 2028 (13 GWh in 2027, 21 increasing to 15 GWh in 2028), with underlying economic growth driving a recovery to within 1.5 22 GWh of 2026 levels by 2036. 23 DATE: May 15, 2026 Page 74 of 105 REDACTED (C...

AI summary The 2026 Load Forecast Report discusses changes in load forecasts for the RTR market and Medium Industrial class. It highlights declining sales in the Medium Industrial class due to migration to RTR, and notes improvements in forecasting models with updated economic variables and statistical significance.

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 77 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 document includes detailed forecasting methodologies and assumptions used to estimate future load requirements, though specific data has been redacted.

ussed in Section 5, this variable was used to explain the increase in residential load from people working from home during the pandemic and subsequent years, but is removed from the forecast period. Binary shift variables are added to the...

AI summary The text discusses the use of binary shift variables in a linear regression model to explain variations in residential load and sales, including adjustments for anomalies in billing data and residual autocorrelation. These variables were added for specific months to improve model fit and address data irregularities.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Appendix C Page 3 of 9 Figure C3: Firm Peak Demand Figure C4 below provides an overview of the energy forecast accuracy. For these calculations, the load of the...

AI summary The document discusses the accuracy of energy forecasts, noting that the removal of major pulp and paper mill loads reduces variance. On a 5-year basis, the mean absolute percent error (MAPE) averages 2.8% for net system requirements and 5.4% for firm peak load, with accuracy diminishing over longer periods.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Appendix C Page 5 of 9 NSR less mills Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast for: for: for: for: for...

AI summary The document presents forecast statistics for load forecasting, including lead time, number of observations, average percent error, and MAPE across different time horizons. The data shows increasing error rates as the forecast lead time increases.

2105 2119 2024 2259 Actual Firm Peak: 2,014 1,951 1,993 1,949 1,954 1,875 2,061 2,397 2,001 2,180 Percent Error 2015 -6.0% -2.8% -4.8% -3.1% -3.9% -0.8% -10.4% -23.4% -7.3% -15.5% 2016 1.8% 0.8% 3.8% 4.0% 8.9% -0.5% -14.2% 2.9% -5.4% 2017...

AI summary The text presents actual firm peak values and percent error for various years, indicating discrepancies between forecasted and actual data. The data spans from 2015 to 2024, highlighting fluctuations in accuracy over time.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Appendix C Page 7 of 9 Firm Peak Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast for: for: for: for: for: for...

AI summary The document presents a load forecast report with statistical data on firm peak forecasts over a 10-year period, including average percent error and MAPE values for different lead times. The data shows varying levels of accuracy across the forecast periods.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast Report Appendix C Page 9 of 9 System Peak Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast for: for: for: for: for: f...

AI summary This section of the 2026 Load Forecast Report discusses a sensitivity analysis using Monte Carlo simulation for economic and weather variables, with regression coefficients exported into Oracle Crystal Ball for the analysis.

: 1. Once the deterministic SAE class regression models are completed, the regression coefficients are exported into the Monte Carlo tool, called Oracle Crystal Ball (MS Excel add-on). 2. The Monte Carlo process assumes that the regression...

AI summary The text describes a forecasting process using deterministic SAE regression models and Monte Carlo simulations with Oracle Crystal Ball. Historical weather and economic data are used to generate probabilistic forecasts, with variations treated as normal distributions. The process involves running 10,000 trials to assess how forecast predictions respond to input variations.

rmal distributed weight, meaning that after 10,000 trials, a histogram of the variable will have an average and standard deviation that coincides with the distribution of the last 20 years. 6. Incorporating variability in the individual en...

AI summary The document discusses the use of Monte Carlo simulations to model variability in load forecasting, incorporating historical data and the impact of heat pumps. It outlines the production of 10,000 forecast points and the use of Normal distributions to derive probabilistic forecasts and sensitivity diagrams.

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.

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.

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.

in ResFcst.NDM modelled to add 2026 0.00 0 0.00 2027 0.00 0 0.00 2028 -3.68 -10 -6.65 2029 -8.97 -21 -11.80 2030 -15.96 -31 -15.26 2031 -24.04 -41 -16.93 2032 -33.67 -51 -16.83 2033 -42.69 -60 -16.96 2034 -50.96 -68 -16.86 2035 -58.98 -76...

AI summary The text presents a table showing projected values for a model (ResFcst.NDM) from 2026 to 2035, with negative figures indicating decreasing values over time. This data may relate to financial or operational forecasting in the energy sector.

0 4,400 4,200 Previous Forecast Current Forecast Peak

AI summary The text presents a comparison between previous and current forecasts, focusing on peak values, likely related to energy demand or capacity planning.

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.

-126.2 -28.7 0.0 0.0 0% 0% 2% 2% 17% 28% 27% 31% 23.90% 5% 0% 0% 2023 shape 0% 0% 1% 1% 10% 21% 35% 33% 39% 5% 0% 0% 2024 shape 0% 1% 2% 3% 24% 35% 20% 28% 9% 6% 0% 0% REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026 Load Forecast...

AI summary The document contains a load forecast report with percentages and shapes for different years, including a redacted section indicating confidential information. It appears to be part of a regulatory proceeding related to energy forecasting.

.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.

Year Month Pred 2029 9 1165.8 2029 10 1247.8 2029 11 1674.1 2029 12 2011.9 2030 1 2328.5 2030 2 2245.5 2030 3 1933.7 2030 4 1512.6 2030 5 1248.3 2030 6 1172.5 2030 7 1261.9 2030 8 1312.5 2030 9 1172.2 2030 10 1253.3 2030 11 1684.6 2030 12...

AI summary The text presents a table of predicted values over several years, showing a pattern of fluctuations in the data, with peaks in the months of November and December and troughs in the months of June and July. The data appears to be related to some form of forecasting or planning.

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.

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.

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.

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.

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.

356.3 1511.8 Historic Sales Previous Forecast Current Forecast Current Forecast Firm Weather Normalized Peak 2031 356.9 1493.9 355.6 1509.6 2700 2032 355.4 1488.6 354.9 1507.5 2033 354.1 1483.6 354.4 1505.6 2500 2034 352.1 1478.8 353.1 150...

AI summary The text presents historical sales, previous and current forecasts for various years, including peak load calculations and weather-normalized peak values, with data spanning from 2031 to 2036 and a peak value of 2700.

2031 2032 2033 2034 2035 2036 2031 2,351 9 44 - 24 - 5 3 108 - 63 2423 146 2,593 2593 2032 2,369 10 62 - 34 - 4 4 109 - 75 2441 145 2,620 2620 Historic WN Firm Peak Previous Forecast 2033 2,390 11 84 - 36 - 4 4 109 - 87 2471 145 2,652

AI summary The text presents a table with numerical data spanning the years 2031 to 2033, including values such as 2,351, 9, 44, and others. The data appears to represent some form of forecasting or historical comparison, with columns labeled 'Historic WN Firm Peak' and 'Previous Forecast'.

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.

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.

(c) Please refer to CA IR-1 part (f). Hybrid event trigger scenario Event hours 9 scenarios modelled by NS Power. 10 11 Response IR-4: 12 13 Please refer to Synapse IR-8, Attachment 1. 1 Request IR-5: 2 3 Given the purpose of the Net Zero...

AI summary The text discusses the Net Zero Atlantic (NZA) Hybrid Heating Study, referencing participation ranges and a 2028 program launch date as working assumptions. It also requests evidence for a 50% residential participation target and asks for examples of jurisdictions with similar programs.

8 Response IR-3: 9 10 (a) Manufacturing employment numbers used in the forecast are provided in Figure 20. 11 Attachment 9 contains the indexed and weighted variable (manufacturing GDP plus 12 manufacturing employment) that is used in the...

AI summary The response discusses the methodology used by NS Power in forecasting, specifically the weighting of manufacturing GDP and employment data. The weighting is 0.2 for GDP and 0.8 for employment, with both indexed to 2005. Calculations are done in Metrix ND software and not included in attachments.

participation assumptions. 1 Request IR-5: 2 3 In the 2025 Load Forecast Report M12349, Board IR-22(b) noted that the IRP had 4 underestimated the 2024 and 2025 energy demand between 165 and 364 GWh for NSR and 5 between 217 and 209 GWh fo...

AI summary The 2025 Load Forecast Report (M12349) indicated that the Integrated Resource Plan (IRP) underestimated energy demand for 2024 and 2025. NS Power responds that the 2026 load forecast and IRP reference case are aligned, noting small differences in forecasted values for 2036 firm peak and net system requirement (NSR).

2 (c) The factors listed were not considered explicitly in the adjusted forecast. Please refer to 3 Synapse IR-5 for additional information on the new housing estimates. 1 Request IR-4: 15 (a) 16 (i-ii) The results of the study described i...

AI summary The text discusses the validity of the 2025 Load Forecast Report and mentions that charging behavior for vehicles is relatively static, with updates to forecast values occurring on a regular basis. It also references specific exhibits and reports for further analysis on temperature lag weighting and sensitivity studies.

REDACTED 2026 Load Forecast Report Synapse IR-1 Attachment 1 Page 20 of 196 REDACTED (CONFIDENTIAL INFORMATION REMOVED) CPI HouseholdIncome Household Income (mil $2002) % change SFCompletions MUCompletions HousingCompletions % change GDP M...

AI summary The document presents a table containing economic and demographic data from 2025 to 2033, including metrics such as CPI, household income, GDP, employment, and housing completions. The data reflects trends and changes in these indicators over time.

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 load forecast, with updated model from this load input data (MW) forecast (MW)...

AI summary The document contains a redacted 2026 load forecast report with data on load forecasts, interruptible loads, weather impacts, wind effects, and unexplained variations. It includes tables showing forecasted and actual peak loads, along with temperature and wind data for specific dates.

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 Issued 2016 2017 20...

AI summary The document presents a load forecast report with historical data from 2015 to 2025, along with percent error and statistical information such as lead time and number of observations. It provides a detailed analysis of forecast accuracy over time.

5 Peak forecast (MW) Peak forecast error (MW) Peak forecast error (%) Peak model stats Feb-23 Jan-26 Feb-23 Jan-26 Avg Feb-23 Jan-26 Avg R2 MAPE Actual peak 2,455 2,459 n/a n/a n/a n/a n/a n/a n/a n/a LFR 20261 C1 = 0.8, C2 = 0.2 2,436 2,4...

AI summary The text presents a table comparing peak forecast data and model statistics for different weighting scenarios and lag times. It includes actual peak values, forecast errors, and model performance metrics such as R2 and MAPE for various configurations.

2026 Load Forecast Report (NSEB M12861) NSPI Responses to Synapse Energy Economics Inc. Information Requests 1 (d) Not necessarily. Analysis performed on the January 2026 peak, presented in Section 10 of 2 the Report, suggests that sustain...

AI summary NS Power explains that the January 2026 peak was influenced by very cold conditions and that the peak model has high explanatory power. They also clarify that the system peak forecast uses an aggregate regression model incorporating class-level sales forecasts to account for structural changes in customer behavior.

NON-CONFIDENTIAL 1 forecast is therefore not derived by aggregating class-level peaks but rather reflects system-2 level demand informed by bottom-up drivers. This is the system peak forecast. 3 4 To determine individual class contribution...

AI summary The text discusses forecasting methods for demand, focusing on system-level and class-specific models. It explains that the system peak forecast is derived from bottom-up drivers, while class contributions are determined through historical load factors. Two models—System Model and Class-Tailored Model—are evaluated for their accuracy in forecasting class-level coincident peak demand.

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

AI summary This document outlines the 2026 Load Forecast Report (NSEB M12861) and includes NSPI's responses to information requests from Synapse Energy Economics Inc. It pertains to forecasting energy demand and related responses.

25 (f) Generally, NS Power has made no assumptions regarding non-PHEV ICE LDVs in forecast 26 year 2036. 27

AI summary NS Power has not made any assumptions about non-PHEV ICE LDVs in their 2036 forecast.

NON-CONFIDENTIAL 1 Request IR-12: 2 3 Solar Generation (PV) (Section 4.5.5, p. 47-50) 4 5 (a) Please provide supporting data for the average capacity and capacity factor for the 6 PV installations used in the forecast. 7 8 (b) How was the...

AI summary The response to Request IR-12 discusses the supporting data for solar generation forecasts, including average capacity and capacity factor, adjustments for lower solar installations in 2025, and the use of AMI data for validation. The response refers to attachments and reports for detailed calculations and methodology.

2026 Load Forecast Report Synapse IR-19 Attachment 1 Page 1 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Year Actuals p10 p50 p90 2016 2,111 2017 2,018 2018 2,073 2019 2,060 2020 2,050 2021 1,968 2022 2,216 2023 2,455 2024 2,088 2025 2...

AI summary The document presents a 2026 Load Forecast Report with tables showing historical and projected load data, including actuals and probabilistic forecasts (p10, p50, p90) for various years. It also includes a request for clarification on the XHeat variable and its underlying factors driving changes in HP Heat percentages.

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.

ategies LLC and Brattle Group, with Rob Gramlich, Richard Seide, Yorgos Raskovic, J. Michael Hagerty, Joe DeLosa III, and Johannes Pfeifenberger, for submission in FERC Docket No. AD24-9, August 2024. "Independent Transmission Construction...

AI summary The text lists various reports and studies prepared by Grid Strategies LLC and other entities, including analyses on power demand forecasts, transmission construction monitoring, and reliability assessments, submitted to different organizations and regulatory bodies.

- "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.

rid Nova Scotia Project on behalf of the Nova Scotia Consumer Advocate. Cost classification, decommissioning costs, justification for software vendor selection, and suggested changes to project scope. Nova Scotia UARB Matter No. M09499, di...

AI summary The text outlines various regulatory matters where Paul Chernick provided expert testimony on behalf of the Nova Scotia Consumer Advocate and Small Business Utility Advocates. Topics include capital expenditures, decommissioning, cost classifications, load forecasting, and evaluation of electric vehicle charging programs.

3.1. General Updates and Major Drivers While the forecast methodologies differ by class, a few updates and standing treatments affect the forecast broadly and are best addressed before turning to the individual sectors. NS Power continues...

AI summary NS Power uses a 20-year economic forecast from Signal49 Research and benchmarks it against major banks. RTR migration is reducing forecast energy demand, but peak demand remains unchanged. DSM programs continue to reduce load, with data drawn from current and pending agreements, and historical adjustments applied to avoid double-counting savings.

Relative to the 2025 forecast, growth in this year's residential forecast is flatter. In the 2025 forecast, modeled average use for existing customers rose by 5.8 percent over the forecast period, driven largely by heat pump electrificatio...

AI summary The residential electricity forecast for this year shows flatter growth compared to the 2025 forecast, with reduced heat pump adoption and the winding down of the Oil to Heat Pump Affordability program. NS Power adjusted its housing completion forecasts based on Signal49's data, but the adjustment is viewed as somewhat arbitrary.

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.

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.

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.

NS Power Response: Please refer to Synapse Recommendation 2. As outlined in the response to Synapse IR-9, the adjustment to the new housing forecast aligns future completions with historic averages. In terms of sensitivity, adjusting the n...

AI summary NS Power acknowledges the SBA's concerns regarding new housing forecast adjustments and agrees to provide similar calculations in future forecasts. Market conditions such as development delays and financing constraints are acknowledged but cannot be individually accounted for in the forecast due to the large number of projects involved.

oragecanada.org>; MacLean, Monique ; MacMullin, Charlene ; Mark Peachey ; McKayla Cameron ; Melissa Whitten ; Mersey, Janice ; Michael Murphy ; [email protected]; Morgan, Adrienne ; Muhammad Syfuddin Tamim ; Mullins, Naomi ; Munroe,...

AI summary NS Power has uploaded documents related to a 2026 load forecast request for confidentiality and CU under matter M12861. The contact for this matter is Jessie Wallace.

PI to NSEB M12861 2026 Load Forecast Request for Confidentiality and CU 20260519 NSPI to NSEB M12861 2026 Load Forecast Report CU The contact for this matter is Jessie Wallace. Kind regards, Carley Freeman (she/her) Paralegal, Regulatory A...

AI summary Nova Scotia Power (NSP) submitted a 2026 Load Forecast Report to the Nova Scotia Energy Board (NSEB) with a confidentiality request. The contact for the matter is Jessie Wallace, and the email was sent by Carley Freeman of NSP.

Request IR-1: - Figure 3: Historic and Forecast Net System Requirement and System Peak. - a) The Net System Requirement (NSR) forecast percentage change in 2027 is negative. Aside from Renewable to Retail sales, what are the factors that a...

AI summary The document contains several requests for clarification regarding forecasts related to Net System Requirement (NSR) and system peak, as well as employment data sources and discrepancies in manufacturing GDP figures. Questions focus on the factors influencing NSR trends, the accuracy of system peak forecasts, and the rationale for using broader age groups in employment data analysis.

Request IR-6: - Please provide NS Power's EV forecast model in excel format with cells intact and protections removed. - a) Is NS Power's EV forecast based on Ensuring ZEV Adoption in Nova Scotia: Analysis of Policy Options and Possible Ad...

AI summary Request IR-6 seeks NS Power's EV forecast model in Excel format, inquiring if it relies on the March 2023 ZEV adoption analysis and whether it assumes 100% ZEV sales by 2036. The request emphasizes transparency and accuracy of assumptions in load forecasting.

Request IR-8: In the 2025 Load Forecast Report M12349, Board IR-22(b) noted that the IRP had underestimated the 2024 and 2025 energy demand between 165 and 364 GWh for NSR and between 217 and 209 GWh for Firm Peak and asked if NS Power sti...

AI summary The Board IR-22(b) questioned Nova Scotia Power (NSP) about the alignment between the Integrated Resource Plan (IRP) and the 2025 Load Forecast Report (M12349), noting significant underestimations of energy demand in 2024 and 2025. The Board asked whether NSP still considers these forecasts aligned.

Request IR-9: - 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 30, 2025, the MEUs informed...

AI summary The 2025 Load Forecast Report M12349 initially assumed third-party service for municipal load in 2025, but MEUs informed NS Power of continued bundled service in 2026. The request asks NS Power to explain how this change affects their NSR.

Request IR-10: - Appendix D, page 2 states that the historical variation of inputs (predictors, independent variables) - will affect the forecast prediction, in a probabilistic way. Please list the historical variation inputs applied to th...

AI summary The document requests a list of historical variation inputs from Appendix D, page 2, which are used in a probabilistic forecast model to account for variations in predictors affecting forecast accuracy.

Request IR-2: - System Peak - a. Refer to Table 1 in the Board Decision regarding NS Power's 2025 Load Forecast (M12349). Please explain the main factors causing the low accuracy in the peak demand forecast between 2019-2024. - b. Beyond t...

AI summary Request IR-2 focuses on analyzing the accuracy of NS Power's peak demand forecasts from 2019 to 2024 and identifying changes in model specifications between the 2025 and 2026 Load Forecasts. It also asks for quantification of the impact of these changes.

Request IR-9: - Commercial Hybrid Heating (Section 4.5.2, p. 42) - a. Refer to Figure 26 and the following statement on page 42: "As with previous load forecasts, the commercial energy values predicted from the commercial SAE model is high...

AI summary Request IR-9 seeks clarification on the discrepancy between the commercial SAE model and E3 hybrid scenario model for commercial hybrid heating, and asks for detailed explanations, supporting documentation, and assumptions used in the 2026 Load Forecast. It also inquires about the validation of E3's assumptions by NS Power.

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.

Request IR-18: - Model Specifications (Appendix B) - b. Please note any changes in the residential model specification relative to the 2025 forecast residential model, and please further quantify the impact of any such changes in specifica...

AI summary Request IR-18 asks for model specification changes relative to the 2025 forecast residential model, and quantification of their impact for residential, commercial, and industrial models.

Request IR-21: ELCC Study - a. Refer to the following statement from the 2025 Load Forecast: "On February 6, 2025, NS Power distributed to stakeholders for review and comment a draft study scope document for the next ELCC study." - i. Plea...

AI summary Request IR-21 seeks information about the timeline for completing the ELCC study and whether its results will be included in the 2027 Load Forecast. The request references a draft study scope document distributed by NS Power in February 2025.

EfficiencyOne Information Requests to Nova Scotia Power, Inc. (NS Power) In the Matter of Nova Scotia Power Incorporated's 2026 Load Forecast Report (M12861) IN THE MATTER OF: The Public Utilities Act - and - IN THE MATTER OF: Nova Scotia...

AI summary EfficiencyOne has submitted information requests to Nova Scotia Power, Inc. (NS Power) regarding its 2026 Load Forecast Report under the Public Utilities Act. The proceeding involves regulatory scrutiny of NS Power's load forecasting methodologies and compliance with legislative requirements.

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 an explanation of the modeled hybrid heating program's average annual energy impact and its assumed 50% residential participation. It also asks about sensitivity analysis, lower participation assumptions, and risks of including the program in forecasts without being fully evaluated.

5 Request IR-07: - 6 (a) How does participation in residential hybrid heating vary with incentives, customer type, 7 technological barriers etc.? If these have not been considered, how confident is NS Power 8 in the accuracy of the hybrid...

AI summary The document requests NS Power to explain how residential hybrid heating participation varies with incentives, customer types, and technological barriers, and how uncertainty in hybrid heating forecasts is incorporated into overall risk assessments.

James R. Gogan Direct +1 (902) 563 5920 [email protected] 1969 Upper Water St., Suite 1300 Halifax, NS Canada B3J 3R7 Tel +1 (902) 563 1000 Fax +1 (902) 563 1113 Our File: 249458 June 15, 2026 Nova Scotia Energy Board Filed via...

AI summary James R. Gogan of McInnes Cooper notifies the Nova Scotia Energy Board of EfficiencyOne's intent to file intervention requests (IRs) in M12861, concerning Nova Scotia Power's 2026 Load Forecast Report. The letter is addressed to Clerk Crystal Henwood and includes a cc to the client.

1 M12861 2 3 NOVA SCOTIA UTILITY AND REVIEW BOARD 4 5 IN THE MATTER OF: The Public Utilities Act 6 7 -and - 8 9 10 11 IN THE MATTER OF: NOVA SCOTIA POWER INCORPORATED's 2026 Load Forecast Report 12 13 14 15 16 INFORMATION REQUESTS 17 18 19...

AI summary The Nova Scotia Utility and Review Board is handling a proceeding under the Public Utilities Act regarding Nova Scotia Power's 2026 Load Forecast Report. The Consumer Advocate has requested information from Nova Scotia Power, with responses due by July 7, 2026. The matter is referenced as M12861.

Request IR-2: Refer to M12861, Exhibit N-1, the Report, Section 4.2, 2025 Data Modifications Due to the Cyber Incident, page 19 of 105, Lines 6-7, and respond to the following: - a) The Report states that 2024 monthly billed sales patterns...

AI summary Request IR-2 seeks information on how NS Power estimated 2025 monthly sales using 2024 data and whether validation was performed. It also asks about additional forecast uncertainty and any sensitivity or scenario analysis conducted.

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.

, Page 29 of 105, Lines 14-21. 3 Exhibit N-7(C)(i), NSPI Response to Synapse IR-1, Attachment 01 - Confidential 4 Exhibit N-1, 2026 Load Forecast Report, Page 29 of 105, Line 17. financing, likelihood of completion, or potential schedule d...

AI summary The Small Business Advocate (SBA) argues that NSPI's 2026 Load Forecast Report does not sufficiently justify the chosen 10% decline rate and highlights housing development as a major source of uncertainty. The SBA recommends that the Board require NSPI to provide a lower-housing sensitivity case and updated development pipeline tracking in future forecasts.