Topic:"Load Management" in M12451

Overview - Planning for Nova Scotia's electricity system requires an estimation of how much power - customers will consume over the course of a year, and load affects both planning and operational - costs: - Total electricity usage determi...

AI summary This section outlines the importance of load forecasting in planning Nova Scotia's electricity system, noting that total consumption and peak demand influence both variable and fixed costs. NS Power updates its load forecast annually, and the 2026-2027 forecast was developed using an updated methodology, as detailed in SR-02 and Figure 4-1.

FAM Tariff and POA Updates to Account for Load Migrations - As part of its Decision and Order in the 2024 FAM AA/BA proceeding, the NSEB directed NS - Power to amend the FAM Tariff to account for customers moving out of the FAM class and b...

AI summary The NSEB directed NS Power to update the FAM Tariff to handle load migrations between FAM and non-FAM classes, including MEU and RTR Market customers. Current processes address MEU migrations but require further consideration for small RTR Market customers. Amendments to Special Condition 3 and the POA are proposed, with potential future updates for RTR-related migrations.

CRITICAL PEAK EVENT PROCEDURE - (1) In the Winter Period, Critical Peak Events exclude all hours on the following holidays: January 1, Nova Scotia Heritage Day, Good Friday, Easter Monday, November 11, December 25 and December 26. If Janua...

AI summary The Critical Peak Event Procedure outlines exclusions for holidays during the Winter Period, criteria for scheduling events (e.g., high energy usage, outages), notification protocols, and rate adjustments during events. Events are limited to 18 per winter season, with specific weekday/weekend restrictions. Customers face higher charges during events and are encouraged to reduce consumption.

SPECIAL CONDITIONS - (1) Metering will normally be at the low voltage side of the transformer. Should the customer's requirements make it necessary for the Company to provide primary metering, then the customer will be required to make a c...

AI summary Special conditions outline customer responsibilities for metering costs, transformer ownership, and load integrity. Customers may incur capital contributions for primary metering, own transformers for non-standard services, and ensure their load doesn't compromise power system integrity. Factors like reliability, harmonics, and voltage flicker are considered in assessing system impacts.

(3) Load Migrations between FAM/Non-FAM Classes

AI summary The section discusses load migrations between FAM and non-FAM classes, involving Nova Scotia Power Inc. (NSPI) and programs like the Fuel Adjustment Mechanism (FAM) and Demand Side Management Cost Recovery Rider (DCR). It focuses on regulatory considerations for managing load shifts across these classes.

Load Following

AI summary The Load Following section of the Nova Scotia regulatory proceeding involves discussions around mechanisms and programs related to energy demand management. Key entities include Nova Scotia Power Inc. (NSPI) and the Nova Scotia Energy Board (NSEB), with references to the Fuel Adjustment Mechanism (FAM) and Demand Side Management Cost Recovery Rider (DCR).

Activation of Reserves When a contingency occurs, the Transmission Provider will activate, at its sole discretion, sufficient reserves from (i) those under contract with the Transmission Provider, (ii) those provided by Transmission Custom...

AI summary The Transmission Provider activates reserves during contingencies from contracted resources, Transmission Customers, or third parties, prioritizing cost minimization and system restoration. Operating Reserve service is available for three hours post-contingency, with Transmission Customers responsible for addressing supply deficiencies. Unscheduled energy withdrawals are classified as Energy Imbalance under Schedule 4.

SPECIAL CONDITIONS - (1) Metering will normally be at the low voltage side of the transformer. Should the customer's requirements make it necessary for the Company to provide primary metering, then the customer will be required to make a c...

AI summary Special conditions outline metering requirements, customer capital contributions for primary metering, non-standard service provisions, load integrity responsibilities, and factors affecting power supply integrity, including reliability, harmonics, voltage flicker, and stability considerations.

Nova Scotia Power Incorporated Page 14 of 23 Open Access Transmission Tariff overall cost of supplying reserves and to return the system to pre-contingency conditions within the time required by NPCC and NERC. Operating Reserve service wil...

AI summary Operating Reserve service is available for the hour of a contingency and the following two hours, adhering to NPCC and NERC standards. The Transmission Customer must address supply deficiencies by the end of this period, with unscheduled withdrawals treated as Energy Imbalance under Schedule 4.

Nova Scotia Power Incorporated Page 16 of 23 Open Access Transmission Tariff This includes, but is not restricted to, NS PIower resources. Typically the activation will be done to minimize the overall cost of supplying reserves and to retu...

AI summary NSPI activates resources to minimize reserve supply costs and meet NPCC/NERC standards. Reserve services are available for the contingency hour and two following hours, with Transmission Customers responsible for addressing supply deficiencies. Unscheduled energy withdrawal is classified as Energy Imbalance per Schedule 4.

Nova Scotia Power Incorporated Page 18 of 23 Open Access Transmission Tariff Reserve services will only be available for the hour in which the contingency occurs and the following two hours. The quality of service will be firm for this tim...

AI summary Reserve services under the Open Access Transmission Tariff (OATT) by Nova Scotia Power Inc. (NSPI) are available for the hour of a contingency and the following two hours, with firm service quality. The Transmission Customer must resolve supply deficiencies by the end of this period, and unscheduled energy withdrawals are treated as Energy Imbalance under Schedule 4.

PR-02 Cost Support for Proposed Regulation Changes Attachment 1 – AMI Opt-out Fee Development Attachment 2 – Miscellaneous Charges Development (Partially Confidential) Regulation 7.3 Schedule of Load Research Monitoring, Reporting and Anal...

AI summary The document outlines attachments related to AMI opt-out fee development and miscellaneous charges, alongside references to Regulation 7.3 concerning load research monitoring, reporting, and analytical charges. It pertains to cost support for proposed regulatory changes in Nova Scotia.

10. Alternative Treatment of Interruptible Loads There were four directives arising from the 2023-2024 GRA which relate to the wholesale market, Open Access Transmission Tariff (OATT) and capacity-based ancillary services. The Board direct...

AI summary The Board directed NS Power to explore alternative treatment of interruptible loads following MEUs' support for the GRA Settlement Agreement and recommendations by Mr. Marshall. NS Power indicated interruptible loads are counted toward reserves when generation resources are insufficient. The Board urged analysis of cost implications for alternative treatments in the next GRA.

3 1.2.12 Extra-Large Industrial Active Demand Control Customer and Impact on Fuel 4 Forecasting 5 - 6 NS Power perfo1med an analysis to dete1mine the total fuel and purchased power costs with the - 7 Extra Large Industrial Active Demand Co...

AI summary NS Power conducted an analysis estimating the impact of the Extra-Large Industrial Active Demand Control (ELIADC) load on fuel and purchased power costs, projecting $65.7 million in 2027. The analysis compared scenarios with and without ELIADC load inclusion.

COSS CA DR-9 Attachment 1 Page 168 of 627 Start Time End Time ANL_MW 5/2/2020 3:00 5/2/2020 4:00 507.5 5/2/2020 4:00 5/2/2020 5:00 558.6 5/2/2020 5:00 5/2/2020 6:00 639.7 5/2/2020 6:00 5/2/2020 7:00 746.7 5/2/2020 7:00 5/2/2020 8:00 838.5...

AI summary The text presents a table with timestamps and corresponding ANL_MW values, likely representing energy load data over a specific period on May 2, 2020, and into May 3, 2020. The data reflects fluctuations in megawatt demand across different time intervals.

COSS CA DR-9 Attachment 1 Page 197 of 627 Start Time End Time ANL_MW 7/25/2020 17:00 7/25/2020 18:00 1121.4 7/25/2020 18:00 7/25/2020 19:00 7/25/2020 19:00 7/25/2020 20:00 1100.8 1036.9 7/25/2020 20:00 7/25/2020 21:00 950.6 7/25/2020 21:00...

AI summary The text presents a table showing the ANL_MW (apparent net load in megawatts) over a period of time from July 25, 2020, to July 28, 2020. It includes start and end times for each interval and the corresponding ANL_MW values. This data likely pertains to electricity demand or generation analysis during this period.

COSS CA DR-9 Attachment 1 Page 242 of 627 Start Time End Time ANL_MW 12/3/2020 22:00 12/3/2020 23:00 1068.9 12/3/2020 23:00 12/4/2020 0:00 1011.9 12/4/2020 0:00 12/4/2020 1:00 954.1 12/4/2020 1:00 12/4/2020 2:00 923.2 12/4/2020 2:00 12/4/2...

AI summary The text presents a table of apparent net load (ANL_MW) values over a 24-hour period on December 3-5, 2020, showing fluctuations in electricity demand at hourly intervals. This data likely relates to grid management and load forecasting.

COSS CA DR-9 Attachment 1 Page 271 of 627 Start Time End Time ANL_MW 2/26/2021 12:00 2/26/2021 13:00 1276.2 2/26/2021 13:00 2/26/2021 14:00 1203.8 2/26/2021 14:00 2/26/2021 15:00 1128.1 2/26/2021 15:00 2/26/2021 16:00 1157.5 2/26/2021 16:0...

AI summary The document presents a table with time-stamped data showing the ANL_MW (apparent load in megawatts) values over a 48-hour period from February 26, 2021, to February 28, 2021. The values fluctuate significantly, indicating variations in electricity demand or generation during this timeframe.

COSS CA DR-9 Attachment 1 Page 291 of 627 Start Time End Time ANL_MW 4/25/2021 21:00 4/25/2021 22:00 923.3 4/25/2021 22:00 4/25/2021 23:00 893.4 4/25/2021 23:00 4/26/2021 0:00 813.4 4/26/2021 0:00 4/26/2021 1:00 724.9 4/26/2021 1:00 4/26/2...

AI summary The text presents a table of apparent net load (ANL_MW) values over time, showing fluctuations in energy demand from April 25 to April 27, 2021. These data points may be used for grid planning, load forecasting, or regulatory analysis related to electricity generation and distribution.

COSS CA DR-9 Attachment 1 Page 295 of 627 Start Time End Time ANL_MW 5/7/2021 13:00 5/7/2021 14:00 5/7/2021 14:00 5/7/2021 15:00 1140.6 1092.8 5/7/2021 15:00 5/7/2021 16:00 1070.8 5/7/2021 16:00 5/7/2021 17:00 1126.9 5/7/2021 17:00 5/7/202...

AI summary This document presents a table of data showing the start and end times of various intervals, along with corresponding ANL_MW values. The data spans from May 7, 2021, to May 10, 2021, and appears to represent energy-related measurements or load values over time.

COSS CA DR-9 Attachment 1 Page 335 of 627 Start Time End Time ANL_MW 9/1/2021 5:00 9/1/2021 6:00 9/1/2021 6:00 9/1/2021 7:00 850.7 934.9 9/1/2021 7:00 9/1/2021 8:00 1028.2 9/1/2021 8:00 9/1/2021 9:00 1116.6 9/1/2021 9:00 9/1/2021 10:00 117...

AI summary The document presents a table with time intervals and corresponding ANL_MW values, likely representing energy demand or load data over a period from September 1, 2021, to September 4, 2021. It also references a partially confidential appendix from a 2026-2027 GRA direct evidence submission.

COSS CA DR-9 Attachment 1 Page 344 of 627 Start Time End Time ANL_MW 9/27/2021 11:00 9/27/2021 12:00 979.9 9/27/2021 12:00 9/27/2021 13:00 926.6 9/27/2021 13:00 9/27/2021 14:00 885.1 9/27/2021 14:00 9/27/2021 15:00 810.6 9/27/2021 15:00 9/...

AI summary This document presents a table of apparent net load (ANL_MW) values over time on September 27-29, 2021, showing fluctuations in energy demand across different hours. The data is likely used for grid planning, load forecasting, or system reliability analysis.

COSS CA DR-9 Attachment 1 Page 489 of 627 11/24/2022 8:00 11/24/2022 9:00 1457.7 11/24/2022 9:00 11/24/2022 10:00 1395.7 11/24/2022 10:00 11/24/2022 11:00 1296.9 11/24/2022 11:00 11/24/2022 12:00 1263.3 11/24/2022 12:00 11/24/2022 13:00 12...

AI summary The text presents a series of timestamps and numerical data points, likely representing energy usage or system performance metrics over a period of time on November 24 and 25, 2022. The data appears to be part of a technical or operational report, possibly related to grid monitoring or load management.

COSS CA DR-9 Attachment 1 Page 527 of 627 Start Time End Time ANL_MW 3/15/2023 5:00 3/15/2023 6:00 989.9 3/15/2023 6:00 3/15/2023 7:00 1081.5 3/15/2023 7:00 3/15/2023 8:00 1185.1 3/15/2023 8:00 3/15/2023 9:00 1227.5 3/15/2023 9:00 3/15/202...

AI summary The text presents a table with time intervals and corresponding ANL_MW values, likely representing energy demand or load data over a 24-hour period on March 15 and 16, 2023. This data may be used for grid planning, demand forecasting, or resource allocation purposes.

COSS CA DR-9 Attachment 1 Page 537 of 627 Start Time End Time ANL_MW 4/13/2023 9:00 4/13/2023 10:00 4/13/2023 10:00 4/13/2023 11:00 1100.2 1029.2 4/13/2023 11:00 4/13/2023 12:00 990.5 4/13/2023 12:00 4/13/2023 13:00 964.2 4/13/2023 13:00 4...

AI summary This document provides a table of apparent net load in megawatts (ANL_MW) over a series of time intervals from April 13 to April 16, 2023. The data reflects fluctuations in energy demand across different hours, indicating patterns in electricity usage.

Cost of Service Study Process (NSUARB M11475) NSPI Responses to IG Data Requests 1 Request DR-3: 2 3 From the 2024 Load Forecast (released recently as part of another proceeding, but for the 4 purposes of supporting analysis in this one):...

AI summary NSPI is responding to data requests related to the 2024 Load Forecast, providing load forecast data for P10, P50, and P90 scenarios by rate class for 2024 and 2030. NSPI notes that demand by rate class is not modeled at the P10/P50/P90 level and that demand forecasts are not split between firm and interruptible for large industrial customers.

Path to 2030 Report Resource Plan Nameplate Anticipated COD Nameplate Anticipated COD Capacity (MW) (Year) Capacity (MW) (Year) Wind & Solar Resources Fuel Conversions at Existing Units Rate Base Procurement 373 2025 Gas Conversion – Point...

AI summary The Path to 2030 Report outlines the Resource Plan, detailing various renewable energy projects, energy storage initiatives, and fuel conversion plans, with capacities and anticipated completion dates provided in a table format. The plan includes wind and solar resources, fuel conversions at existing units, and load management initiatives.

Hypothesis includes greater level of complexity vs. accuracy/precision - Annual losses, 8760 Data vs. load factor calculations - Non-Technical Losses, assumption vs. calculations - Secondary Configurations, sampling vs assumptions - Distri...

AI summary The text discusses the complexity of data and assumptions in various aspects of energy loss calculations, including annual losses, non-technical losses, secondary configurations, and distribution transformer no-load losses, comparing data with assumptions and simulations.

2.1 Load Forecast Model NS Power will develop the Residential and Commercial Sector forecasts using a Statistically-Adjusted End-Use (SAE) model and will develop the industrial sector forecasts using customer surveys in conjunction with ec...

AI summary NS Power will use a Statistically-Adjusted End-Use (SAE) model for residential and commercial load forecasts, combining bottom-up end-use modeling with statistical economic forecasting. Industrial forecasts will use customer surveys and econometric models. Data sources include Natural Resources Canada and the US Energy Information Administrator, with economic outlooks based on the Conference Board of Canada.

Load Growth through Electrification - Florida has the second highest penetration of EVs in the US - In Nova Scotia, incentives for heat pump adoption are accelerating conversion of home heating from oil to electric

AI summary The document discusses load growth through electrification, highlighting Florida's high EV penetration and Nova Scotia's incentives for heat pump adoption, which are accelerating the shift from oil-based home heating to electric systems.

l Index............................................................. 61 43 Figure 41: Residential Sales Components by Year....................................................................... 62 DATE: April 30, 2024 Page 3 of 100 REDACTE...

AI summary The document is a redacted section of a 2024 Load Forecast Report, focusing on Unmetered Service Rates for Miscellaneous Lighting & Small Loads. It includes a table of contents and a figure reference, but the main content is redacted due to confidentiality.

2025 Load Forecast Report Redacted 1 Figure 43: Historical and Forecast Annual Residential Sales 58 2 Figure 44: Annual Consumption by Building Type 59 3 Figure 45: Building Characteristics and Structural Index 60 4 Figure 46: Residential...

AI summary The document is a redacted 2025 Load Forecast Report containing figures related to historical and forecast annual sales, building characteristics, demand response, peak contributions, and energy sensitivity. It includes data on residential, commercial, and industrial consumption, as well as peak load forecasts and variance analysis.

2025 Load Forecast Report Redacted - 1 Compared to the 2024 Load Forecast, the 2025 Load Forecast shows increased net system - 2 requirement in the near term due to a change in forecast for Renewable to Retail (RTR) sales. - 3 Mid- to long...

AI summary The 2025 Load Forecast Report indicates increased near-term net system requirements due to changes in Renewable to Retail (RTR) sales, but lower mid- to long-term growth due to factors like reduced EV sales, increased RTR sales, and behind-the-meter solar. Long-term energy sales are also expected to decrease due to DSM initiatives and natural energy efficiency improvements.

2025 Load Forecast Report Redacted - 1 supply requirements associated with RTR peak demand) and slightly lower in the long term due - 2 to a revised EV peak impact. As a result, the system peak demand is expected to increase at an - 3 aver...

AI summary The 2025 Load Forecast Report Redacted outlines an expected annual increase in system peak demand of 1.1 percent, influenced by revised EV peak impact and supply requirements associated with RTR peak demand.

2025 Load Forecast Report Redacted 1 These trends are reduced over time (approximately 40 years) such that the average annual HDD is 2 not forced to 0 and the average annual CDD does not increase indefinitely. Figure 9 shows how 3 the HDD...

AI summary The 2025 Load Forecast Report outlines how heating and cooling degree days (HDD and CDD) evolve over a 10-year period, showing a decrease in winter heating load and an increase in summer cooling load for residential and commercial sectors, influenced by leap years in 2028 and 2032.

1 4.2.1 Investigating the impact of cloud data on the Load Forecast 2 3 As requested by the Consumer Advocate, NS Power investigated the impact of cloud cover on 4 energy and peak demand models. Since cloud cover data are not available fro...

AI summary NS Power investigated the impact of cloud cover data on energy and peak demand models. Using an alternative dataset from NASA's Modern-Era Retrospective Analysis, the study found minimal improvements in model performance when including solar radiation data, leading to its exclusion from the 2025 Load Forecast.

2025 Load Forecast Report Redacted - 1 drivers, on an annual basis, used in the 2025 Load Forecast. For financial measures, the variables - 2 have been adjusted to constant dollars, eliminating the inflation effects from the series.

AI summary The text discusses the 2025 Load Forecast Report, highlighting that drivers used in the forecast have been adjusted to constant dollars to eliminate inflation effects from the series.

2025 Load Forecast Report Redacted 1 coincident peak impact is determined to be 0.39 kW for at home charging (again, not including 2 public charging of LDVs). An example of time-of-day variation in EV effect is given in Figure 3 73 .

AI summary The 2025 Load Forecast Report discusses the impact of electric vehicle (EV) charging on load forecasting, noting a coincident peak impact of 0.39 kW for at-home charging and referencing a figure illustrating time-of-day variation in EV effects.

2025 Load Forecast Report Redacted 1 • Other: all other major appliances (stoves, dishwashers, clothes washers and dryers, 2 televisions) as well as smaller appliances such as computers, dehumidifiers, microwaves, 3 etc. This category also...

AI summary The 2025 Load Forecast Report includes a category for other major and smaller appliances, as well as solar generation and EV forecasts, providing a comprehensive overview of energy demand.

2025 Load Forecast Report Redacted - 1 Forecasts by class (including new projects in the Large General and Large Industrial classes) are - 2 shown in Figure 37 . 3

AI summary The 2025 Load Forecast Report provides forecasts by class, including new projects in the Large General and Large Industrial classes, as illustrated in Figure 37.

2025 Load Forecast Report Redacted 1 test the TVP elasticity in the load forecast as the elasticity changes over the course of the TVP Pilot." 24 The TVP Pilot estimates two elasticities: 25 2 3 4 • Own/daily price elasticity captures the...

AI summary The document discusses the estimation of price elasticity in the 2025 Load Forecast Report, focusing on the TVP Pilot. It differentiates between own/daily price elasticity and substitution price elasticity, noting that the former captures changes in overall consumption due to average daily price changes, while the latter reflects customers' substitution of off-peak for peak consumption. These estimates are based on TVP pilot participants and may not be directly comparable to broader population trends or long-term forecasts.

2025 Load Forecast Report Redacted 1 Weather adjusted sales in 2024 were very close to forecast, though the warm weather reduced sales 2 in the class by 104 GWh. 2026 and 2027 are expected to decline as a result of load migrating to 3 the...

AI summary The 2025 Load Forecast Report indicates that weather-adjusted sales in 2024 were close to forecast, with warm weather reducing sales by 104 GWh. Load is expected to decline through 2033 due to migration to the RTR market and increased behind-the-meter solar adoption, though EV load may increase sales after 2033. DSM and efficiency improvements will decrease sales, while new customers and electric heating will increase them.

1 6.1 Small General Service 2 3 Historical and forecast Small General service loads are shown in Figure 49 . Small General service 4 load shows an average annual increase of 1.5 percent compared to an increase of 1.8 percent per 5 year in...

AI summary The document discusses historical and forecasted Small General Service loads, noting a 1.5% annual increase compared to 1.8% in the 2024 Load Forecast. Commercial electrification of heating is offset by DSM and decreased intensity forecasts for ventilation, lighting, and miscellaneous end uses. The total load increase from 2025 to 2035 is projected to be 16.3%.

2025 Load Forecast Report Redacted 1 electricity requirements over the next three-year period. Details on planned production levels or 2 equipment changes help inform expectations on energy sales. In the absence of any survey or 3 general...

AI summary The 2025 Load Forecast Report predicts flat load levels over the next three years, with limited customer input indicating slight increases. One major customer is expected to increase load, and 34 GWh of load migration to the RTR market is anticipated by 2027. Uncertainty remains around new industrial facilities and their impact on load growth.

1 10.0 PEAK DEMAND 2 3 The total system peak is defined as the highest single hourly average demand experienced in a - 4 year. It includes both firm and interruptible loads. Due to the weather-sensitive load component - 5 in Nova Scotia, t...

AI summary The document outlines the methodology used by NS Power for forecasting peak demand, including the use of end-use data and the impact of factors like EV charging and demand response (DR) programs. It also notes the shift in DR capacity estimates from 2025 to 2028 and the ongoing use of an effective load carrying capacity (ELCC) of 48%.

2025 Load Forecast Report Redacted Efficient Product Installation Program. 803 controllers were installed in 2024. 33 1 E1 integrated this 2 pilot project into the Eco Shift program for the 2024/2025 season. 3 4 NS Power is also working wi...

AI summary The document discusses the Efficient Product Installation Program and the Eco Shift pilot, highlighting the installation of controllers and the expansion of DR programs. It outlines the results from the 2023/2024 season and ongoing evaluations for the 2024/2025 season. The impact of these programs on load forecasts is noted, with DR capacity expected to influence future projections.

2025 Load Forecast Report Redacted - 1 For the 2025 Load Forecast, as discussed in Section 4.2, the assumed peak temperature inputs use - 2 a lagging 12-hour average as well as windspeed. The coefficients used for peak normalization are -...

AI summary The 2025 Load Forecast Report outlines the methodology for peak temperature and windspeed inputs, using a lagging 12-hour average and the same coefficients as the 2024 forecast, as described in Figure 61.

2025 Load Forecast Report Redacted 1 contributions, and finally DSM. As discussed in Section 4.4 , the EV contribution to peak is 2 expected to be partially mitigated via utility managed charging. The firm peak assuming the 3 current non-c...

AI summary The 2025 Load Forecast Report discusses the impact of electric vehicles (EVs) and space heating on peak load, noting that EVs are expected to add approximately 60 MW to the peak in 2035, while space heating is projected to reduce peak demand by around 46 MW in the same year.

17 Figure 66: Forecast Peak Variance vs Actuals MW 2024 Forecast Peak 2,365 Interruptible -57 Weather (-10.8°C 12hr lag avg) -101 Wind (7.4 km/h daily avg) -31 Morning peak impact (estimated) -121 Unexplained +33 2024 Actual Peak 2,088 18

AI summary Figure 66 compares forecasted and actual peak demand for 2024, highlighting factors such as interruptible load, weather, wind, morning peak impact, and unexplained variance. The forecast peak was 2,365 MW, while the actual peak was 2,088 MW.

2025 Load Forecast Report Redacted 1 compared to their forecast peak load. Note that it is the firm peak that is used for planning 2 purposes, which excludes the interruptible load. 3 4 The impact of a morning vs evening peak, mostly relat...

AI summary The 2025 Load Forecast Report discusses the difference between morning and evening peak loads, estimating a 121 MW shift due to lighting load variations. This analysis uses temperature data from 2024 and linear trend lines to compare peak loads at 8am and 6pm.

1 10.3 End Use Peak Estimates 2 3 While the Load Forecast is a good statistical fit for the historical data, it presents challenges when 4 trying to assess the contribution of individual end uses to peak by class. The overall peak forecast...

AI summary The Load Forecast provides a good statistical fit for historical data but struggles to assess individual end-use contributions to peak demand. The text explains how coincident peak contributions from Residential, Commercial, and Industrial classes are derived from load research data and end-use models to better understand peak demand by end use.

12 10.4 Current Class Coincident Peak Demand Research 13 14 NS Power has been exploring ways of using interval data to understand peak at the class level from 15 a bottom-up perspective, as discussed in prior Load Forecast reports. NS Powe...

AI summary NS Power is using interval data to analyze peak demand at the class level, building on prior Load Forecast reports. System peak is forecasted at the aggregate level and then disaggregated into rate class contributions using historical load factors and other data. The 2024 forecast used AMI interval data, with a more complete dataset than in 2023.

1 11.0 SENSITIVITY ANALYSIS 2 - 3 The sales and peak forecasts are fundamentally uncertain and depend on many variables, including - 4 economics, weather, adoption of distributed generation, electricity rates and DSM. Although each - 5 of...

AI summary The sensitivity analysis discusses the uncertainty in load forecasts, which are influenced by factors like economics, weather, distributed generation, and DSM. A P10/P90 probability analysis using Monte Carlo simulations was developed in 2017 to estimate future load distribution, showing a range of 480-636 GWh over 10 years, mainly impacted by weather and economic factors.

21 DATE: June 27, 2025 Page 94 of 94 2025 Load Forecast Report Appendix A Page 1 of 3 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 95 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Append...

AI summary The text provides a heading and page reference for a 2025 Load Forecast Report, specifically Appendix A, which contains forecast values for NS Power. The content is partially redacted due to confidentiality.

2025 Load Forecast Report Appendix A Page 2 of 3 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 96 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Appendix A – Forecast Values

AI summary This section of the 2025 Load Forecast Report provides forecast values as part of Appendix A, though specific details are redacted due to confidentiality. It is associated with the 2026-2027 GRA BW IR-7 Attachment 1.

Variable Coefficient StdErr T-Stat P-Value MStructRes.WtXHeat 0.926 0.018 51.423 0.00% MStructRes.WtXCool 1.147 0.185 6.205 0.00% MStructRes.WtXOther 0.925 0.032 29.357 0.00% MSales.AvgEESavingsProfiled -0.414 0.161 -2.577 1.14% MBin.Jan 6...

AI summary This table presents statistical data from a load forecast report, including coefficients, standard errors, t-statistics, and p-values for various variables related to residential heating, cooling, and energy savings. The data appears to be part of a larger analysis for forecasting energy demand from 2026 to 2027.

Residential Model Statistics 1 120 105 0.990 0.989 6.375 6.723 #NA #NA -537.77 5,441,438.16 54,852.50 522.40 22.86 16.40 2.05% 1.592 #NA 32.83 0.1078 0.227 4.249 8.828 0.0121 2025 Load Forecast Report Appendix B Page 7 of 34 REDACTED (CONF...

AI summary The document provides a table of residential model statistics, likely related to energy usage or forecasting, and includes a reference to a redacted section of the 2025 Load Forecast Report Appendix B and an attachment from the 2026-2027 GRA BW IR-7 document.

Small General Model Statistics Model Statistics Iterations 14 Adjusted Observations 120 Deg. of Freedom for 109 Error R-Squared 0.954 Adjusted R-Squared 0.950 AIC 7.605 BIC 7.860 F-Statistic #NA Prob (F-Statistic) #NA Log-Likelihood -615.5...

AI summary The text presents statistical details from a small general model, including metrics such as R-squared, AIC, BIC, and error measures, along with load forecast report information that is partially redacted due to confidentiality.

Variable Coefficient StdErr T-Stat P-Value MBin.Jan 20853.444 1440.731 14.474 0.00% MBin.Feb 20342.822 1439.895 14.128 0.00% MBin.Mar 18241.872 1439.059 12.676 0.00% MBin.Apr 19690.529 1438.223 13.691 0.00% MBin.May 18751.767 1437.387 13.0...

AI summary The document presents a statistical analysis of load forecasting data, including coefficients, standard errors, t-statistics, and p-values for various variables related to monthly energy usage and economic factors. The table provides insights into the statistical significance of these variables in forecasting energy demand.

COVID Variables - For 2025 the COVID variables have been updated in both the Residential and Commercial classes. - In Residential, the variable remains in the model for the years 2020-2024 to help explain the change in usage over those yea...

AI summary The document discusses updates to the COVID variables in the 2025 Load Forecast Report for residential and commercial classes. The variable remains in the residential model for 2020-2024 but is removed from the forecast period, while it is entirely removed from the commercial model as other variables sufficiently capture the impact.

- o They do an inspection of the whole system every two years - Just a visual drive-by and making sure everything is good - o Every 7 years, they'll do a detailed inspection of each pole - Just visual inspections at the pole - A lot of que...

AI summary The document discusses pole replacement and overhead conductor retirement reasons, including load growth, new services, voltage conversions, and storm damage. It also mentions inspection schedules and the impact of electrification on infrastructure planning.

ITEM 6: ELECTRIFICATION & LOAD GROWTH Continue to monitor electrification and load growth in Nova Scotia relative to the 2022 and 2023 Load Forecast reports which incorporate electrification impacts. Also, monitor for the addition of large...

AI summary The document suggests continuing to monitor electrification and load growth in Nova Scotia in relation to the 2022 and 2023 Load Forecast reports, which include electrification impacts, and to watch for the addition of large industrial customers that may affect resource requirements.

The Path to 2030 - 2024 Update 1 TABLE OF CONTENTS 2 3 1.0 EXECUTIVE SUMMARY 5 4 2.0 INTRODUCTION 9 5 3.0 2030 DECARBONIZATION GOALS 11 6 3.1 80 Percent Renewable Electricity Sales 11 7 3.2 Coal Phase Out 12 8 3.3 Proposed Clean Electricit...

AI summary This document outlines Nova Scotia's 2030 Clean Power Plan, including goals for renewable energy, coal phase-out, and resource development. It details various projects such as wind and solar resources, battery storage, and reliability tie initiatives.

7 7.2 Hybrid Peak / Load Management / Demand Response 8 9 As a component of NS Power's development of its electrification strategy report, it worked with 10 its consultant Energy and Environmental Economics (E3) to prepare load and system...

AI summary NS Power is developing a hybrid peak load management program involving mini-split heat pumps and existing backup heating sources to reduce system peak load requirements. The program is part of the Evergreen Integrated Resource Plan and was discussed in the 2023 Load Forecast Report. NS Power plans to participate in a study to assess the cost impacts of the program.

28 22 The Economics of Electrification in Nova Scotia (nspower.ca) 1 In the first half of 2024, NS Power met with NRR on their approach to a Hybrid Peak study as part 2 of the Load Management initiative of the Clean Power Plan. Net Zero At...

AI summary NS Power is collaborating with NRR on a Hybrid Peak study as part of the Load Management initiative under the Clean Power Plan. They are also advancing demand response (DR) programming to achieve 75 MW of peak load reductions and have received approval for new time-of-use (TOU) pilot tariffs. Stakeholder engagement and recruitment for these initiatives are ongoing.

(b) Work for the 2026-2027 GRA proceeding began before the 2025 Load Forecast was finalized, so an updated version of the 2024 Load Forecast, with assumptions updated based on available data at the time work for the GRA proceeding began, w...

AI summary The 2026-2027 GRA proceeding used an updated version of the 2024 Load Forecast due to the work beginning before the 2025 Load Forecast was finalized. No further updates were made to ensure efficiency and minimize confusion in the regulatory process.

(f) The NSR and Net System Peak values from the 2024 and 2025 Load Forecast are confirmed. However, the NSR values given for the GRA Load Forecast are incorrect, as addressed in response to NSEB IR-023. This has been corrected in the compl...

AI summary The NSR and Net System Peak values from the 2024 and 2025 Load Forecast are confirmed, but the NSR values for the GRA Load Forecast are incorrect and have been corrected in Table 4, as addressed in response to NSEB IR-023.

4 RTR sales have decreased by 102 GWh for 2026 and have increased by 175 GWh for 2027 5 between the 2024 and 2025 Load Forecasts, increasing net system requirement for 2026 6 and decreasing net system requirement for 2027 and beyond. 7 8 (...

AI summary RTR sales have decreased by 102 GWh for 2026 and increased by 175 GWh for 2027 compared to the 2024 and 2025 Load Forecasts, affecting net system requirements for those years.

- o They do an inspection of the whole system every two years - Just a visual drive-by and making sure everything is good - o Every 7 years, they'll do a detailed inspection of each pole - Just visual inspections at the pole - A lot of que...

AI summary NSPI conducts regular inspections of poles and overhead conductors, with replacements driven by storm damage, load growth, new services, voltage conversions, and third-party damage. Load growth and electrification trends are increasing the need for infrastructure upgrades and capacity planning over the next 20 years.

ITEM 6: ELECTRIFICATION & LOAD GROWTH Continue to monitor electrification and load growth in Nova Scotia relative to the 2022 and 2023 Load Forecast reports which incorporate electrification impacts. Also, monitor for the addition of large...

AI summary The document highlights the need to continue monitoring electrification and load growth in Nova Scotia, referencing the 2022 and 2023 Load Forecast reports, and emphasizes the importance of tracking the addition of large industrial customers that may affect resource requirements.

NSPI, "2025 Maritime Link Benefits Report Q3 PARTIALLY CONFIDENTIAL," November 10, 2025 ("Q3 Maritime Link Report"), page 5 lines 26-27. 1 margin."91 Note that NSPI filed a capital application at the Board in May 2024 seeking to 2 spend ju...

AI summary NSPI submitted a capital application in May 2024 to spend approximately $1.66 million for safe operations and firm capacity during the fall and winter of 2023–2024. However, the anticipated sustaining capital of nearly $21 million over the GRA period is considered a significant increase and requires additional narrative support from NSPI. The document also discusses the assessment of NSPI's load forecast, which was updated in September 2024 as part of the GRA Forecast.

(Company evidence: load forecast, cost allocation, and rate design) 2020 • Hydro Ottawa, 2021-2026 Custom IR Application (Company evidence: cost allocation and rate design) • Lakeshore Communities, LTC and Phase II Applications for new nat...

AI summary The document lists various utility companies and their applications related to cost of service, load forecasting, cost allocation, and rate design, including evidence submitted by companies such as Hydro Ottawa, Lakeshore Communities, and Burlington Hydro, among others, between 2017 and 2021.

POTENTIAL ADAPTATION MEASURES - Install lines with higher operating limits or lower thermal expansion. - Install more effective cooling mechanisms in substations. - Educate customers about the importance of reducing energy consumption duri...

AI summary The text outlines potential adaptation measures for managing energy systems, including improving infrastructure, customer education, and increasing system redundancy to address challenges such as thermal expansion and energy demand during peak periods.

Issue 2) For what length of time should the load data be collected? The Working Group recommended that at least 12 months of load data be collected. The Board directs that 12 consecutive months of usable load data be collected.

AI summary The Working Group recommended collecting at least 12 months of load data, and the Board directed the collection of 12 consecutive months of usable load data.

Issue 3) In order to ensure reliability of the load data gathered, what sampling methodologies are appropriate? The Working Group recommended that any of the statistically-verifiable sampling methodologies discussed in the leading North Am...

AI summary The Working Group recommends using statistically-verifiable sampling methodologies from the AEIC's Load Research Manual for load data collection. The Board supports this and suggests that Ontario distributors may adopt a common methodology to facilitate data sharing. The Board also advocates for a province-wide sampling program to achieve cost efficiencies and ensure data reliability.

Issue 9) Should the same load data collection rules apply to all Ontario electricity distributors? The Working Group recommended that all cost allocation studies should be prepared with the same high quality load data. The Board accepts th...

AI summary The Working Group recommends that all cost allocation studies use high-quality load data. The Board agrees and directs Ontario electricity distributors to develop load profiles meeting a 10% accuracy target at 90% confidence level, allowing for province-wide data collection approaches.

ovincial data to be collected into distributor-specific load profiles. An Appendix to the Working Group Report explains how a specific party proposes to use its expertise and software to do this task. The Board expects that, whatever metho...

AI summary The Board supports the collection of provincial load data into distributor-specific load profiles, emphasizing the need for statistically-reliable results with an accuracy of ±10% at 90% confidence. A methodology outlined in the Report's Appendix is deemed acceptable for achieving this.

3. Load Data Requirements The Chapter sets out the Directions on load data requirements for the cost allocation filings.

AI summary This section outlines the Directions regarding load data requirements for cost allocation filings, which are essential for regulatory proceedings related to energy costs and distribution.

3.1.1 Filing Question If there is a significant change in the relative load profiles for a historic test year filer (e.g. introduction of battery mats for USL loads, addition or loss of a major large user), a distributor should identify th...

AI summary The document states that if there is a significant change in the relative load profiles for a historic test year filer, such as the introduction of battery mats for USL loads or the addition or loss of a major large user, the distributor must identify this in its Filing Summary.

3.3 Information Required for Completion of Utility-specific Load Profiles A large group of distributors earlier gathered province-wide load data for the residential and GS>50 kW rate classifications. This load data has been analysed by the...

AI summary The document outlines the process for creating utility-specific load profiles for residential and GS>50 kW rate classifications. It requires distributors to provide specific information, such as appliance saturation surveys or estimates, and specifies that most distributors will use the Hydro One Load Data Team for this task.

3.3.1 Filing Questions Any distributor who is not using the Hydro One Load Data Team to prepare its utility-specific load profile must provide the following in its Filing Summary: - 1) The name of its service provider and its relevant qual...

AI summary Distributors not using Hydro One's Load Data Team must provide details on their service provider, data sources, and methodology for creating utility-specific load profiles in their Filing Summary.

3.4.3 Filing Question Any distributor who is not using the Hydro One Load Data Team must confirm that the Hydro One methodology was used to weather normalize its load profile.

AI summary Distributors not using the Hydro One Load Data Team are required to confirm that the Hydro One methodology was used for weather normalizing their load profile.

3.6.2 Load Profile for Run 3 Distributors may file a Run 3 of the filing in which the load data for the separate LDG rate classification is modeled by an alternative method of adding the actual, or estimated if actual not available, metere...

AI summary The document discusses the method for modeling load data in Run 3 filings, specifically addressing the inclusion of load displacement generation (LDG) and the consideration of diversity among LDG customers. Stakeholders have expressed varying opinions on the availability of data and the need to account for diversity in load displacement generation.

3.7 Load Profile for Separate Unmetered Scattered Load Class Where USL[9](#page-26-0) is to be treated as a separate rate classification in the model (e.g. Run 2), the combined load profile must be calculated as follows: Step 1) Non-Photo-...

AI summary This section outlines the methodology for calculating the load profile for Unmetered Scattered Loads (USL) when treated as a separate rate classification. It specifies that non-photo-sensitive loads use a deemed load profile based on combined load shapes, with flat profiles for most types of non-photo-sensitive unmetered loads.

Step 3) Photo-sensitive Loads The total kWh consumption of each type of unmetered scattered load for purpose of development of the utility-specific load shape and demand allocators will be the kWh consumption estimate used by the distribut...

AI summary This section outlines how the distributor will estimate kWh consumption for unmetered scattered loads, using flat load profiles for non-photo-sensitive loads and the Board-approved load profile for photo-sensitive loads like street lighting.

Step 4) Combining Results The resulting load shapes under steps 1), 2) and 3) will be combined to create a single separate USL load profile.

AI summary This section outlines the final step in the process, where load shapes from previous steps are combined to form a single USL load profile.

6.3.4.1 Background The load data supplied by the distributor's load data service provider will have to be adjusted by the distributor to reflect its split into bulk (if any), primary and secondary. The break out will not be undertaken by t...

AI summary The distributor is responsible for adjusting load data from the load data service provider by splitting it into bulk, primary, and secondary categories. This adjustment must be done by the distributor and input into the model, with a methodology provided and further guidance available in filing instructions.

6.3.4.2 Direction – Adjusting Load Data re Bulk, Primary and Secondary The load data supplied by the distributor's load data service provider will have to be adjusted by the distributor to reflect its split into bulk (if any), primary and...

AI summary The text outlines the process for adjusting load data for bulk, primary, and secondary systems. It defines terms like coincident peak and distribution system coincident peak and explains how to calculate the bulk coincident peak and primary/secondary non-coincident peaks based on load percentages.

11.5.4.1 Background There have been discussions with stakeholders as to what might be the appropriate threshold at which a customer with load displacement facilities would be defined as a LDG customer for capturing in Run 2 of the cost all...

AI summary Discussions with stakeholders are ongoing to determine the appropriate threshold for defining a customer with load displacement facilities as a LDG customer in Run 2 of the cost allocation modeling. Some stakeholders suggest aligning this threshold with the net-metering threshold of 500 kW.

11.5.5.5 Filing Questions - i) If a distributor has an approved administrative charge in respect of standby rates, then it should explain the basis and components of this charge. - ii) If the distributor incurs other extraordinary costs to...

AI summary The document outlines questions for distributors regarding administrative charges, recovery of extraordinary costs for load displacement generators, and methods for estimating distribution benefits and costs from load displacement facilities.

11.5.7 Future LDG Customer Rate Design Issues surrounding the design and implementation of new rates for load displacement customers (including the merits and design of charges for standby distribution service) will be further addressed in...

AI summary The document outlines the upcoming Distribution Rate Design Review to address issues related to future LDG customer rate design, including standby distribution service charges. It highlights the need for stakeholder input and the importance of analyzing cost allocation model runs to inform future rate decisions.

NB: To use 2006 EDR data when assessing rate classification changes Rate Classification Data Requirements 9. Load Displacement Generation – Load displacement customers that displace greater than 500 kWs of load. If modeled as a fully separ...

AI summary The text provides guidance on using 2006 EDR data for assessing rate classification changes, including specific requirements for load displacement, merchant generation, and hybrid classifications. It outlines data requirements, alternative methods, and restrictions on eliminating certain classifications.

Filing Question: Load Displacement Customers - Further Potential Distribution Cost Savings or Burdens When completing Run 1 and Run 2 of the filing, all distributors with load displacement customers should review the below list to ascertai...

AI summary The filing question addresses potential distribution cost savings or burdens associated with load displacement customers. It outlines cost reductions and potential burdens, such as deferred asset commissioning, reduced line losses, and increased system flexibility, as well as unknown impacts like voltage stability concerns.

FOR DECEMBER 2026 (1) MWH SALES (2) ENERGY LINE LOSSES (3) ENERGY REQUIREMENT (4) CLASS NON- COINCIDENT DMD. (KW) (5) SYSTEM COINCIDENT FACTOR (6) SYSTEM COINCIDENT DMD. (KW) (7) DEMAND LINE LOSSES (8) SYSTEM COIN. PEAK DMD. (KW) (9) SYSTE...

AI summary The document presents a summary of energy sales, losses, and demand metrics for December 2026, including subtotals and totals before export. It details energy requirements, system demand factors, and losses across various categories.

FOR DECEMBER 2027 (1) MWH SALES (2) ENERGY LINE LOSSES (3) ENERGY REQUIREMENT (4) CLASS NON- COINCIDENT DMD. (KW) (5) SYSTEM COINCIDENT FACTOR (6) SYSTEM COINCIDENT DMD. (KW) (7) DEMAND LINE LOSSES (8) SYSTEM COIN. PEAK DMD. (KW) (9) SYSTE...

AI summary The document presents a table with various energy metrics for December 2027, including energy sales, losses, demand, and system factors. It outlines key parameters related to energy generation, distribution, and system performance.

(32) LINE LOSSES - ELIADC (33) LINE LOSSES - BUTU (34) LINE LOSSES - EXTRA LI INTERRUPTIBLE (35) LINE LOSSES - EXTRA LI INTERRUPTIBLE (36) LINE LOSSES - EBS/RTR (37) LINE LOSSES - ESPORT SALES (38) CLASS NON-COINCIDENT DMD DOMESTIC (39) CL...

AI summary The document presents line losses and demand data for various classes and systems, including ELIADC, BUTU, and EBS/RTR, with figures for different years. It includes line losses for different categories and demand data for domestic, small general, and general large classes.

ection is filed under subsection 93.4(4) or (5) of the Act. 4 (1) The Act is amended by adding the following after section 93.3: Definitions 93.4 (1) The following definitions apply in this section. FABI surplus, of a foreign affiliate (re...

AI summary The text outlines an amendment to the Act, specifically adding definitions under section 93.4. It defines FABI surplus in relation to a foreign affiliate, including specific conditions related to taxable surplus calculations under the Income Tax Regulations.

ductible 248(1), but does not include a natural person or a part- par l’effet de la division 95(2)f.11)(ii)(D)) nership. (contribuable) sur le total des sommes dont chacune re- présente : transaction includes an arrangement or event. (opér...

AI summary The text outlines definitions related to tax regulations, including terms such as 'transaction,' 'transferred capacity,' and provisions under subsection 95(2)f.11)(ii)(D). It discusses revenue from interests and financing of affiliated companies and sums included under specific tax subdivisions.

2 the foreign affiliate’s relevant affiliate écrit en vertu de la présente division selon les interest and financing expenses (as de- modalités réglementaires, fined in subsection 18.2(1)) (determined without regard to this clause and subs...

AI summary The text outlines specific financial calculations related to a foreign affiliate's interest and financing expenses, as well as foreign accrual property losses, under a regulatory framework. These calculations are determined without regard to certain subsections of the Income Tax Regulations.

3 les dépenses d’intérêts et de finance- (determined without regard to this clause, ment de la société affiliée pertinentes clause (D) and subsection 18.2(19)) for the (au sens du paragraphe 18.2(1)) de la socié- taxation year, and té étra...

AI summary The text outlines the determination of interest and finance expenses of a foreign affiliate, excluding specific provisions, and references the foreign affiliate's foreign accrual property loss or income for the taxation year.

NCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 444,691 8.19% 481,109 1,030,722 86.6% 892,737 9.61% 978,550 68.29% ( 2) SMALL GENERAL 27,955 8.14% 30,231 57,8...

AI summary The document presents a detailed breakdown of electricity demand, sales, losses, and requirement factors across various customer categories, including domestic, small and large general, industrial, PHP, and municipal. It includes specific percentages and numerical values for each category, with a sub-total at the bottom.

INCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 319,746 7.69% 344,330 650,001 90.3% 587,067 8.34% 636,042 72.76% ( 2) SMALL GENERAL 26,458 7.64% 28,480 59,02...

AI summary The document presents a detailed breakdown of electricity demand, sales, losses, and requirement factors across various customer categories, including domestic, industrial, and municipal sectors. It includes data on peak demand, coincident sales, and losses, with a sub-total for all categories. Specific programs and systems, such as Shore Power and ELIADC, are also listed.

NCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 321,630 7.30% 345,113 652,755 99.9% 652,308 8.56% 708,174 65.50% ( 2) SMALL GENERAL 26,087 7.26% 27,980 55,955...

AI summary The text presents a table with data on electricity demand, losses, and requirements across different customer categories in Nova Scotia, including domestic, industrial, and municipal sectors, along with associated factors and percentages. It includes subtotals and additional categories such as Shore Power and ELIADC.

OINCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 276,088 7.82% 297,673 576,378 93.5% 539,018 8.41% 584,352 70.75% ( 2) SMALL GENERAL 23,021 7.77% 24,810 53,4...

AI summary The document presents a detailed breakdown of electricity sales, losses, and demand across various customer categories, including domestic, industrial, and municipal sectors. It includes metrics such as peak demand, load factor, and losses, with specific data for different classes of users and programs like PHP and ELIADC.

OINCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 602,917 8.30% 652,943 1,344,111 91.7% 1,231,859 14.31% 1,408,115 62.33% ( 2) SMALL GENERAL 34,690 8.25% 37,5...

AI summary The text presents a table with data on sales, losses, and demand factors across various customer categories, including domestic, industrial, and municipal sectors, alongside specific programs like PHP and ELIADC. The data includes figures related to peak demand, losses, and load factors for different segments.

DETERMINATION OF CLASS NON-COINCIDENT KW DEMAND BY VOLTAGE LEVEL FOR THE YEAR ENDING DECEMBER 31, 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) TOTAL SMALL GENERAL SMALL MEDIUM LARGE COMPANY DOMESTIC GENERAL GENERAL LARGE INDUSTRIAL I...

AI summary The document outlines the determination of class non-coincident kW demand by voltage level for the year ending December 31, 2026, with columns indicating various categories of demand and load classifications.

REAL TIME POWER LOAD FOLL. ELIADC BUTU SPILL PRICING EBS RTR OATT TOTAL BTL

AI summary The text presents a real-time power load follow table, including columns such as ELIADC, BUTU, SPILL, PRICING, EBS, RTR, OATT, and TOTAL BTL, indicating various metrics related to power load and generation.

0 0 0 0 0 0 0 0 P-9 (36) DISTRIBUTION -Meters 0 0 0 0 0 0 0 0 0 0 0 P-9 (37) DISTRIBUTION PLANT - Streetlight 4,757 0 0 0 0 0 0 0 0 0 4,757 Direct (38) GENERAL PROPERTY 16,886 11,728 644 3,210 196 366 369 170 0 47 157 P-9 (39) (40) TOTAL D...

AI summary The text presents a table with various distribution and demand-related line items, including meters, streetlights, and general property, along with associated costs and classifications such as 'Direct' and 'P-9'. The table includes totals for the distribution function and demand, with figures spanning multiple years.

update to the rates, which could potentially negatively impact the nature and status of the Settlement Agreement reached by the parties in this proceeding. [Emphasis added] [Exhibit N-35, pp. 14-15] [53] In reviewing NS Power's load foreca...

AI summary The document discusses the use of the September 2024 GRA Forecast by NSPI in its rate update discussions, noting that while the 2025 Load Forecast is more updated, using the 2024 forecast was reasonable to avoid negatively impacting the Settlement Agreement. The forecast differences between 2024 and 2025 are within 1%.

3.4.2.1 Findings [202] John Wiedmayer, of Gannett Fleming, and Mr. Madsen agree that ELG and ALG are both acceptable and appropriate procedures to determine depreciation expense. They also agree that both procedures require the use of sign...

AI summary John Wiedmayer and Mr. Madsen agree that ELG and ALG are both valid depreciation methods with equivalent total recovery over an asset's life. They note ALG's prevalence in the U.S. and ELG's growing use in Canada, citing denied conversion requests in Manitoba, Ontario, and other jurisdictions. ALG's simplicity and ELG's computational ease are highlighted as factors influencing adoption.

3.8.4 Peak Load Carrying Capability Adjustment [617] Ms. Palmer also recommended that a peak load carrying capability adjustment be applied to account for the demand component served by the minimum system, if the basic customer method is n...

AI summary Ms. Palmer recommends applying a peak load carrying capability adjustment to account for the minimum system's load-carrying capacity, citing examples from Ontario, Excel Energy, and National Grid. NS Power agrees with the theoretical capability of the minimum system. A 1.5 kW/customer adjustment is suggested for infrastructure costs classified via the minimum system study.

o. Transmission Customers can purchase each of the Ancillary Services from the Transmission Provider, or they can self-supply the capacity-based ancillary services or purchase them from a third party. [661] The capacity-based ancillary ser...

AI summary The document outlines capacity-based ancillary services, including Regulation, Frequency Response, and Operating Reserves, with specific requirements set by NPCC. NS Power must maintain 32 MW spinning reserve and 136 MW supplemental reserve. LIIR interruptible load, while unsuitable for day-ahead planning, provides real-time value. The 2026-2027 settlement agreement reduces 10-minute supplemental reserve by 35 MW using 50% of LIIR's estimated demand.

Issue Load Forecast for 2026 and 2027

AI summary The issue concerns the load forecast for the years 2026 and 2027, which is critical for planning energy generation, distribution, and demand management strategies in Nova Scotia.

Comment As stated on page 24 of the GRA, the Load Forecast used in the GRA is the 2024 Load Forecast, filed with the Board in April 2024 (M11689) with the three updates noted on page 25. The 2024 Load Forecast was before the Board as a ful...

AI summary NS Power references the 2024 Load Forecast and the ongoing consideration of the 2025 Load Forecast Report by the Board, stating that the GRA outcomes are supported and no further evidence is needed for this issue.

7 Request IR-3: 8 9 What is the annual cost impact of applying the PHP credit to the lower interruptible system 10 coincident demand? 11

AI summary The document poses a question regarding the annual cost impact of applying the PHP credit to the lower interruptible system's coincident demand, focusing on the financial implications for the interruptible system under Nova Scotia Power's regulatory framework.

e. If not provided in part (d), provide a map or illustration of the Company's system demonstrating how the Company's network system design intends "to connect multiple renewable generation sites." f. Does the Company consider its wind gen...

AI summary The document requests detailed information on NSPI's transmission system design, classification of transmission costs under OATT, and the use of SLF in the COSS. It asks about renewable generation connectivity, wind generation classification, system demand's impact on costs, transmission efficiency, and equipment capacity in distribution studies.

Request IR-21: - Reference: Exhibit N-3 GRA Direct Evidence, Section 4 Load Forecast - On page 24 of the application, NS Power notes that its forecast for net energy consumption in the - province over the two-year test period was produced...

AI summary NS Power is being asked to provide an updated version of a load forecast figure, explain why the 2025 Load Forecast was not used, and compare different forecasts regarding renewable energy, electric vehicle adoption, and solar uptake for the 2026-2027 GRA proceeding.

- Reference: Exhibit N-3 GRA Direct Evidence, Section 4 Load Forecast - On page 25 of the application, NS Power states "While migration to RTR [Renewable to Retail] - reduces sales, it has no impact on forecast peak demand, which is expect...

AI summary The document requests clarification on the impact of Renewable to Retail (RTR) on peak demand and load forecasts, including assumptions about customer participation, reasons for forecast increases, and associated MW levels.

Request IR-24: - Reference: Exhibit N-3 GRA Direct Evidence, Section 4 Load Forecast - On page 26, NS Power noted that the four OATT MEUs will be taking a portion of their load - through the Municipal Tariff so load adjustments were made f...

AI summary NS Power adjusted load for the Municipal class and BUTU due to four OATT MEUs taking load via the Municipal Tariff. The inquiry seeks to understand the impact of these adjustments on peak demand and total energy in 2026 and 2027.

Request IR-129: - Reference: Exhibit N-3 GRA Direct Evidence, Section 12.4 PHP COSS Treatment - On page 79 of 99, NS Power stated: In addition, PHP's ATL treatment includes the value of priority interruption service provided, if any. For t...

AI summary NS Power's GRA Direct Evidence (Exhibit N-3, Section 12.4) explains the 10% premium applied to LIIR credit for priority interruption service. Questions seek clarification on differences from current practices, interruption data (2022-2025 YTD), and the rationale for the 10% premium.

1) The PHP Tariff Application Differs from the Settled Terms The wording in the Consensus Agreement in relation to "PHP Treatment" is the lengthiest section and was intentionally drafted. At the time of the negotiation and the filed GRA, t...

AI summary The PHP Tariff Application deviates from settled terms, as the Consensus Agreement's 'PHP Treatment' section was intentionally drafted without a successor rate. NSPI's applied COS model incorporates fuel cost savings and fixed costs but omits quantifying 'active demand control' (ADC), which was intended for negotiation. Clause (f) allows parties to challenge the tariff's alignment with load characteristics, while clause (g) permits NSPI to request a deferral account due to assuming PHP would be ATL in 2026.

lenchus COSS Consultation Report dated April 25, 2025 that was prepared by Mr. Blair and his colleague John Todd and filed as Exhibit N-9, Appendix 12B in this proceeding (pages 1698-1699 of the pdf): "The minimum system method is appropri...

AI summary The document argues that the minimum system method is appropriate for classifying infrastructure costs (poles, fixtures, lines) between demand and customer. Costs are driven by distribution system sprawl and peak demand, with incremental costs tied to meeting peak demand. This approach separates base infrastructure costs from demand-related expenses.

ght in this GRA. [57](#page-31-0) Material variances that may arise include but are not limited to: • The cost of service model applicable to NS Power ATL classes; M12661, ELIDT Application, p 14-15. • The costing and billing determinants...

AI summary The GRA's variances include cost-of-service models for NS Power ATL classes, PHP billing determinants, and tariff constructs. NS Power clarified that Goose Harbour Lake timing impacts PHP Deferral, affecting revenue and deferral amounts based on wind farm implementation timing.

Treatment of Port Hawkesbury Paper as an Above-the-Line Customer Port Hawkesbury Paper is currently served under a below-the-line rate with a term ending on December 31, 2026 (2025 NSEB 16). In the cost-ofservice studies for 2026 and 2027,...

AI summary Port Hawkesbury Paper (PHP) is currently under a below-the-line rate until 2026 but is modeled as an above-the-line customer in 2026-2027 cost-of-service studies. This includes 8 MW firm load at three coincident peaks and 65 MW total load, incorporating projected wind farm supply.

aining cost of the secondary distribution system is a cost which varies continuously (and, perhaps, even more or less directly) with the maximum demand imposed on the system as measured by peak load. But if the hypothetical costs of a mini...

AI summary The text discusses the classification of minimum system costs, arguing they are unallocable as they don't fit into demand or customer cost categories. It critiques FERC's approach and Sterzinger's (1981) recommendation to classify distribution costs as demand costs, noting both methods are nonassignable. The debate centers on cost-allocation methodologies in utility regulation.

3.8.3.1 Findings [616] As with the discussion about the use of the minimum system method or the basic customer method, the Board finds that a more satisfactory resolution of this issue would result from a broader debate about this issue. T...

AI summary The Board directs a comprehensive analysis of distribution system cost classification, emphasizing the need for broader debate beyond jurisdictional scans. It expects issues identified by Ms. Palmer, including primary system usage, residential service at primary voltages, and demand relative to peak, to be thoroughly addressed in the proceeding.

the absence of a specific calculation, recommended that each customer class be credited with 1.5 kW/customer to the non-coincidental peak demands used for determining minimum system demand allocators. [620] Based on her pre-filed evidence...

AI summary Ms. Palmer recommended a 1.5 kW/customer credit as a proxy for peak load carrying capability adjustment until NS Power provides a more accurate calculation. She cited examples from Ontario, Minnesota, South Dakota, and New York, positioning 1.5 kW as a middle-ground approximation.

o. Transmission Customers can purchase each of the Ancillary Services from the Transmission Provider, or they can self-supply the capacity-based ancillary services or purchase them from a third party. [661] The capacity-based ancillary ser...

AI summary The document outlines capacity-based ancillary services (CBAS) requirements, including Regulation, Frequency Response, and Operating Reserves, with specific MW thresholds set by NPCC. NS Power notes that LIIR interruptible load, while unsuitable for day-ahead planning, provides real-time value. The 2026-2027 costing approach uses 50% of LIIR's estimated demand as 10-minute reserve, reducing required supplemental reserves by 35 MW.

1 JONATHAN MacINTOSH, Previously Affirmed: 2 CRAIG FLEMMING, Previously Affirmed: 3 BLAKE WILLIAMS, Previously Affirmed: 4 MICHAEL WILLETT, Previously Affirmed: 5 DRAGAN PECURICA, Previously Affirmed: 6 QUESTIONS FROM MEMBER MURPHY 7 Good...

AI summary Member Murphy questions the significant drop in heat pump installation forecasts from 2024 to 2025 as outlined in the GRA, asking for clarification on the reasons behind the decline, though no definitive answer is provided.