Topic:"Energy Efficiency Resource Assessment Model" in M12451

REDACTED 2026-2027 GRA Direct Evidence Appendix 5A Page 10 of 38 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 1 As illustrated in Figure 5, the forecast cost of fuel increases from $83.69/MWh in 2024 GRA 2 Refresh to $90.03/MWh in 2025, bef...

AI summary The document outlines fuel cost forecasts for the 2026-2027 GRA period, noting fluctuations in costs and the impact of renewable energy projects. It highlights the role of the Maritime Link in enhancing grid reliability and supporting renewable energy targets, as well as the expected increase in wind generation from Independent Power Producers.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2026-2027 GRA Direct Evidence Appendix 7B Page 1 of 2 2024 Compliance 2024 Compliance Restated TOTAL CORPORATE GROUPS 95,631 - 26 2 - 262 95,897 Head Office 3.56 3.561 Thermal Plants 42,75 42,752...

AI summary The document presents a compliance report for 2024, detailing financial and operational data across various corporate groups and departments, including energy production, asset management, and environmental services. The data includes figures for head office, thermal plants, renewable energy sources, and other operational segments, with some entries showing discrepancies or restatements.

- table. 4 Intermediate Generation Unit Net Book Value Current Classification New Classification Tufts Cove 1 $16.5M 46.3% Energy 5.3% Energy 53.7% Demand 94.7% Demand 46.3% Energy 18.4% Energy Tufts Cove 2 $28.8M 53.7% Demand 81.6% Demand...

AI summary The table shows changes in the classification of intermediate generation units at Tufts Cove from energy to demand, with significant shifts in percentages and net book values. The average classification also reflects a notable change from demand to energy.

COSS CA DR-9 Attachment 1 Page 86 of 627 Start Time End Time ANL_MW 9/5/2019 23:00 9/6/2019 0:00 867.1 9/6/2019 0:00 9/6/2019 1:00 810.8 9/6/2019 1:00 9/6/2019 2:00 775.8 9/6/2019 2:00 9/6/2019 3:00 758.0 9/6/2019 3:00 9/6/2019 4:00 753.9...

AI summary The document contains a table showing the ANL_MW values for specific time intervals on September 5th and 6th, 2019, indicating energy load data over a 24-hour period.

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 of time-based data, showing the start and end times along with corresponding ANL_MW values, likely representing energy demand or load data over a specific period on May 2, 2020, and into May 3, 2020.

COSS CA DR-9 Attachment 1 Page 174 of 627 Start Time End Time ANL_MW 5/19/2020 15:00 5/19/2020 16:00 640.9 5/19/2020 16:00 5/19/2020 17:00 691.8 5/19/2020 17:00 5/19/2020 18:00 735.9 5/19/2020 18:00 5/19/2020 19:00 756.5 5/19/2020 19:00 5/...

AI summary The text presents a table with timestamps and corresponding ANL_MW values, likely representing energy demand or generation data over a specific period in May 2020.

COSS CA DR-9 Attachment 1 Page 258 of 627 Start Time End Time ANL_MW 1/19/2021 14:00 1/19/2021 15:00 1/19/2021 15:00 1/19/2021 16:00 1131.3 1157.5 1/19/2021 16:00 1/19/2021 17:00 1241.3 1/19/2021 17:00 1/19/2021 18:00 1413.7 1/19/2021 18:0...

AI summary This document presents a table showing the start and end times of events along with corresponding ANL_MW values, likely representing energy demand or generation data over a specific period in January 2021. The data spans multiple days and hours, indicating potential usage or capacity metrics for analysis.

COSS CA DR-9 Attachment 1 Page 274 of 627 Start Time End Time ANL_MW 3/7/2021 6:00 3/7/2021 7:00 1431.0 3/7/2021 7:00 3/7/2021 8:00 3/7/2021 8:00 3/7/2021 9:00 1483.1 1507.1 3/7/2021 9:00 3/7/2021 10:00 1470.2 3/7/2021 10:00 3/7/2021 11:00...

AI summary This document presents a table of energy demand data for a specific period, showing the start and end times along with corresponding ANL_MW values. The data spans multiple days in March 2021 and appears to be part of a regulatory proceeding related to energy usage and planning.

COSS CA DR-9 Attachment 1 Page 293 of 627 Start Time End Time ANL_MW 5/1/2021 17:00 5/1/2021 18:00 857.7 5/1/2021 18:00 5/1/2021 19:00 850.8 5/1/2021 19:00 5/1/2021 20:00 906.1 5/1/2021 20:00 5/1/2021 21:00 973.8 5/1/2021 21:00 5/1/2021 22...

AI summary The text presents a table of data showing the start and end times of a specific event along with corresponding ANL_MW values, indicating energy consumption or demand over a period of time on May 1, 2021, and May 2, 2021.

COSS CA DR-9 Attachment 1 Page 336 of 627 Start Time End Time ANL_MW 9/4/2021 3:00 9/4/2021 4:00 9/4/2021 4:00 9/4/2021 5:00 795.6 769.5 9/4/2021 5:00 9/4/2021 6:00 798.9 9/4/2021 6:00 9/4/2021 7:00 805.3 9/4/2021 7:00 9/4/2021 8:00 9/4/20...

AI summary The text presents a table showing the start and end times along with ANL_MW values for a specific period, likely related to energy load or generation data. It includes a partially confidential appendix from a regulatory proceeding.

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. The data shows fluctuations in energy usage, with peak demand observed in the early morning hours of March 16.

COSS CA DR-9 Attachment 1 Page 569 of 627 Start Time End Time ANL_MW 7/15/2023 17:00 7/15/2023 18:00 7/15/2023 18:00 7/15/2023 19:00 1254.1 1215.3 7/15/2023 19:00 7/15/2023 20:00 1191.0 7/15/2023 20:00 7/15/2023 21:00 1149.3 7/15/2023 21:0...

AI summary This document contains a table with time-stamped data showing the start and end times of specific events, along with corresponding values for ANL_MW. The data appears to be related to energy usage or generation over a period of several days in July 2023. A section labeled 'PARTIALLY CONFIDENTIAL 2026-2027 GRA Direct Evidence Appendix 12A(2)' is also mentioned, indicating that some information has been redacted.

COSS CA DR-9 Attachment 1 Page 582 of 627 Start Time End Time ANL_MW 8/22/2023 15:00 8/22/2023 16:00 8/22/2023 16:00 8/22/2023 17:00 1154.3 1187.9 8/22/2023 17:00 8/22/2023 18:00 1203.8 8/22/2023 18:00 8/22/2023 19:00 1163.8 8/22/2023 19:0...

AI summary The document contains a table with time-stamped data showing ANL_MW values for multiple intervals between August 22 and August 25, 2023. The data appears to represent energy or load measurements over time.

COSS CA DR-9 Attachment 1 Page 627 of 627 Start Time End Time ANL_MW 12/31/2023 21:00 12/31/2023 22:00 1446.2 12/31/2023 22:00 12/31/2023 23:00 1461.6 12/31/2023 23:00 1/1/2024 0:00 1443.1 PARTIALLY CONFIDENTIAL 2026-2027 GRA Direct Eviden...

AI summary The text includes a table showing ANL_MW values for specific time intervals and references a partially confidential appendix from a regulatory proceeding related to GRA Direct Evidence for the years 2026-2027.

Cost of Service Study Process (NSUARB M11475) NSPI Responses to CA Data Requests 1 Request DR-10: 2 3 Please identify the similarities and differences between the calculation of ELCC for run-of 4 river hydro, Wreck Cove, Maritime Link NS B...

AI summary The document outlines the response to a data request regarding the similarities and differences in calculating Effective Load-Carrying Capacity (ELCC) for various energy resources, including run-of-river hydro, Wreck Cove, and Maritime Link. It explains how these resources are modeled in E3's ELCC study, noting that run-of-river hydro is treated similarly to thermal resources due to their dispatchability.

Nova Scotia Power Fuel and Purchased Power Related COS Methodology January 2022 1 2 2. For ATL classes, NS Power's fuel costs will be classified as 100 percent energy related. 3 These costs will be allocated to each class based on its rela...

AI summary The document outlines Nova Scotia Power's methodology for classifying and allocating fuel and purchased power costs under the 2022-2024 Generation and Resource Assessment (GRA). Fuel costs are categorized as energy-related for ATL classes and allocated based on monthly energy requirements. Purchased power is classified between energy and demand based on generation source and NS Power's fixed cost base load generation practices.

REDACTED 1 Request DR-58: 2 3 For each customer class, please provide hourly estimates of the class load for each year 2014- 4 2023, even if NS Power has low confidence in the quality of the data for any particular time 5 period. 6 7 (a) P...

AI summary The document includes a request for hourly load estimates for customer classes from 2014 to 2023, along with explanations of data confidence levels and assumptions for unmetered load. NS Power refers to a load research sample and provides information on data precision based on metering and sampling methods.

COSS CA DR-58 Attachment 2 Page 1 of 22 PARTIALLY CONFIDENTIAL 2026-2027 GRA Direct Evidence Appendix 12A(2) Page 860 of 1218 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Date Time System (MW) 3/15/2021 20:00 1,865.4 3/16/2021 9:00 1,864.9...

AI summary The document presents a table of system load data in megawatts (MW) recorded on various dates and times in 2021. It appears to be related to energy system performance and may be used for analysis in a regulatory proceeding.

NOVA SCOTIA UTILITY AND REVIEW BOARD IN THE MATTER OF: The Public Utilities Act, R.S.N.S. 1989, c.380 as amended IN THE MATTER OF: An Application by Nova Scotia Power Incorporated for Approval of Certain Revisions to its Rates, Charges and...

AI summary NSPI responded to an information request regarding the historic period used for load profiles and energy forecasts, stating that the most recent full calendar year, 2003, was used. The process involved using customer surveys, end-use models, and load research data, with anomalies like missing data and Hurricane effects addressed.

Response IR-215: (cont'd) g. Demand losses were added to each class using historicallyestimated coincident demand loss percentages, and then added to the sales demands to produce the net system peaks shown in column 3 of the table shown in...

AI summary The text describes the method used to construct typical week load profiles for the NSUARB, including the use of historical demand loss percentages and the Strategist model to reconcile average weekly profiles with forecast monthly peaks and energies.

REDACTED COSS IG DR-3 Attachment 1 Page 3 of 4 Year BUTU EBS Unmetered Transmission Distribution Total Sales before DSM Losses Losses p10 p50 p90 2024 30.3 - 76.9 299.3 473.7 11,320.8 11,549.9 11,784.2 2025 30.3 20.7 76.9 299.1 476.3 11,27...

AI summary The document presents a table with data on energy losses and sales from 2024 to 2030, including metrics for BUTU, EBS, and distribution losses. It also references a partially confidential appendix from a regulatory proceeding.

Cost of Service Study Process (NSUARB M11475) NSPI Responses to IG Data Requests 1 Request DR-4: 2 3 Maritime Link – this topic seems to have been covered in depth in other proceedings but for 4 the relevance of forward-looking COSS method...

AI summary NSPI explains the streams of energy received from Maritime Link, detailing the NS Block and Supplemental energy, including their contract parameters and availability periods. It also addresses forecast assumptions for ML purchases and how they relate to load profiles and planning scenarios.

NON-CONFIDENTIAL 1 Request DR-3: 2 - 3 BAIs COS Cost Allocation presentation of April 29, 2024 showed ELCC demand/energy - 4 breakdowns for generation assets based on the E3, Overview of PRM Study (August 7, 2019) - 5 Presentation. Is NS P...

AI summary The response to DR-3 discusses an update to the ELCC demand/energy breakdowns for generation assets, referencing an update done in June 2020 following the E3 PRM and Capacity Value Study. The update included revised DAFOR values and a clearer separation of TUC categories.

15 Revised Table 18 ‐ E3 PRM Study (Section Resource Nameplate Capacity Net Capacity ELCC % Coal 1081 976 90% HFO/Gas 318 232 73% Gas CTs 144 133 93% LFO CTs 231 178 77% Biomass 43 41 95% Hydro 374 355 95% Wind 596 113 19% Maritime Link Ba...

AI summary The table presents the ELCC percentages for various energy resources in Nova Scotia, including coal, gas, hydro, and wind. The Maritime Link base energy imports have an ELCC of 95%, which was adjusted by NS Power in 2022 due to high forced outage rates associated with the Labrador Island Link.

NON-CONFIDENTIAL 1 In the BIA presentation, the ELCC for "Steam" appears to be a weighted average of the 2 coal and oil ELCC's in Table 18 from the E3 PRM study. In the E3 study, the row titled 3 "Oil" represents NS Powers diesel CT fleet...

AI summary The document discusses the Effective Load-Carrying Capacity (ELCC) values for various energy sources in the E3 PRM study, highlighting discrepancies in how they were calculated and applied, including the inclusion of outdated or inappropriate data points such as Annapolis Tidal and the misclassification of oil units under the 'Steam' category. NS Power recommends using 0% ELCC for solar in future planning due to declining capacity value.

Cost of Service Study Process (NSUARB M11475) NSPI Responses to PHP Data Requests 1 Request DR-5: 2 3 Similar to request number 4 please indicate which steam-thermal units are expected to be 4 retired by 2030 and the expected capacity fact...

AI summary NSPI responds to a data request regarding the retirement of steam-thermal units by 2030 and their expected capacity factors between 2025 and 2030. Several units are expected to retire or switch to alternate fuels, with specific details provided in an attachment referencing the 2022 Evergreen IRP.

2.1 Maritime Link Project 4 3 - 5 The Maritime Link project is a source of out-of-province long-term energy imports that will help - 6 position NS Power to meet its air emissions and renewable energy requirements by 2020. The - 7 project w...

AI summary The Maritime Link project provides long-term energy imports to help NS Power meet emissions and renewable energy targets by 2020. It was approved by the UARB in 2013 and includes firm and non-firm energy components. The project's costs are incorporated into the Base Cost of Fuel (BCF) for 2018 and 2019, with amounts smoothed over the Rate Stability Period as required by the Electricity Plan Implementation Act (EPIA).

1 Request DR-1: 2 - 3 Tabulated hourly load profile for the day of the winter peak demand in 2030 net of all wind - 4 and solar generation (i.e., including behind-the-meter)- by residential; commercial; - 5 industrial; and other customer c...

AI summary The response to Request DR-1 provides an hourly load profile for the winter peak demand day in 2030, along with wind and solar generation data, sourced from the 2022 Evergreen IRP scenario. Behind-the-meter generation is estimated using installed capacity and capacity factors. Peak demand forecasts are provided at a general level rather than by customer class.

Cost of Service Study Process (NSUARB M11475) NSPI Responses to SNS Data Requests 1 Request DR-2: 2 3 Tabulated hourly load profile for the summer day with the lowest diurnal wind power 4 generation in 2030 – net of all wind and of solar g...

AI summary NSPI responded to a data request for a tabulated hourly load profile for a summer day with the lowest diurnal wind power generation in 2030, including behind-the-meter generation. The data provided is from the 2022 Evergreen IRP scenario CE1-E1-R2, with an estimate of behind-the-meter generation calculated using forecasted capacity and hourly capacity factors.

Evergreen IRP - Assumptions - 2030 targets(80% RES, coal phase out) base case - Federal Carbon Pricing - Fuel availability and pricing - Capital and operating cost assumptions - Load profile and electrification assumptions - Renewable inte...

AI summary The document outlines key assumptions for the Evergreen Integrated Resource Plan (IRP), including 2030 renewable energy targets, federal carbon pricing, fuel availability, capital and operating costs, load profiles, electrification, renewable integration, import potential, and emerging technologies such as SMRs and hydrogen.

Evergreen IRP – Key Assumptions Load - NS Power is planning for a growing electricity system load, consistent with what is being forecast across many jurisdictions as part of the coming energy transition. - NS Power's Load Forecasting proc...

AI summary NS Power is forecasting a growing electricity system load due to the energy transition, incorporating electrification effects and using data from Energy + Environmental Economics (E3). Energy efficiency, demand response, and managed EV charging are considered to mitigate increased demand.

Table 3: Pros and cons of Average and Peak with Time of Use method Pros Cons Allocates energy classified costs proportionally to the Moderate data needs (hourly dispatch costs, LOLP). cost of providing energy in each hour (instead of Relie...

AI summary Table 3 discusses the pros and cons of the Average and Peak with Time of Use method. It highlights that this method allocates energy costs proportionally to the cost of providing energy in each hour and allocates peak-demand costs to the hours driving the need for capacity resources. However, it requires moderate data needs and relies on average demand and 3CP, which may not align with the generation mix.

Methods to evaluate energy delivered and annual energy losses Network segments Phase 1 - Method 1 Transmission Lines PSSe software simulations using 8760 data Substations Power Transformers No-Load Losses Load Losses Inventory calculations...

AI summary The document outlines methods for evaluating energy delivered and annual energy losses across various network segments, including the use of software simulations, inventory calculations, and data from GIS and industry reports.

- Annual losses derived by converting peak demand losses over 8,760 hours based on loss factor Configuration Total Energy Loss Energy Loss % ~ Class Padmount (GWh) Pole-mounted (GWh) Vault (GWh) (GWh) Energy Loss % Demand Loss % (1) DOMEST...

AI summary The text discusses annual energy losses derived from peak demand over 8,760 hours, categorized by different classes and configurations such as padmount, pole-mounted, and vault. Energy loss percentages and total energy loss in gigawatt-hours are provided for each class.

Table 4 – Overall Classifications The following table summarises the share of each utility's total costs classified by each demand, energy, and customer. The shares excluding energy are also provided. In addition to classification methodol...

AI summary Table 4 summarizes the share of each utility's total costs classified by demand, energy, and customer. It also provides shares excluding energy, with variations based on generation type and classification methodologies.

17 4.1.2.1 NSP CURRENT APPROACH - 18 Fuel and purchases are sub-functionalized by type of generation or source of energy. - 19 Fuel Costs - 20 Imports - 21 Purchased Power Biomass - 22 Maritime Link - 23 Purchased Power Wind ERIS - - Purch...

AI summary The document discusses how Nova Scotia Power (NSP) categorizes fuel and purchases by type of generation or energy source, including fuel costs, imports, purchased power from biomass, the Maritime Link, and wind projects categorized as either Network Resource Interconnection Service (NRIS) or Energy Resource Interconnection Service (ERIS).

16 Table 5 – Generation Allocations Fuel & Purchases Classification Fuel Energy Imports Energy Maritime Link System Load Factor Purchased Power – Biomass Fuel Energy Purchased Power – Biomass Non-Fuel Weighted Average Generation Rate Base...

AI summary Table 5 outlines generation allocations across various fuel types and classifications, including Energy, System Load Factor, and Effective Load Carrying Capability. It includes entries such as Fuel, Imports, Maritime Link, and Wind under different interconnection services.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA Direct Evidence Appendix 12C Page 2 of 25 Power System Line Loss Study Technical Report Methodology to Compute Loss Allocation Factors 2025-08-20 FINAL My Prepared by: Cili...

AI summary The document presents a technical report on the methodology for computing loss allocation factors in a power system line loss study, prepared by Cilia Fellah and Jean-Sébastien Lacroix, and reviewed by Daryn Thompson and Brendon Henderson. The report was prepared for BBA and is part of the 2026-2027 GRA Direct Evidence Appendix.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA Direct Evidence Appendix 12C Page 3 of 25 Power System Line Loss Study Technical Report Methodology to Compute Loss Allocation Factors

AI summary This document presents a technical report on the methodology to compute loss allocation factors as part of a Power System Line Loss Study. It outlines the approach used to assess and allocate line losses within the power system.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA Direct Evidence Appendix 12C Page 8 of 25 Power System Line Loss Study Technical Report Methodology to Compute Loss Allocation Factors Transformer losses – Comprised of loa...

AI summary This document outlines the methodology for computing loss allocation factors in a power system line loss study, focusing on transformer losses, which include load losses (copper losses) and no-load losses (hysteresis and eddy-current losses). Power and energy losses are quantified in kilowatts and kilowatt-hours, respectively.

Provide data showing how much gas was contracted to be supplied, how much was used (show separately the volumes burned in the combustion turbines at Tufts Cove, and those volumes burned in the steam units and biomass plant), how much was a...

AI summary The text requests detailed data on gas supply, usage, availability, and sales, including specific breakdowns for different facilities, over past, present, and test years.

2.2 Residential Energy Sales Typical home electricity consumption is forecast using an SAE average use model and a sales forecast is generated as the product of the average use and customer forecast. The residential average use SAE model i...

AI summary Residential electricity consumption is forecast using an SAE average use model, which considers cooling, heating, and other uses, along with weather and economic indicators to generate a sales forecast.

2.3 Commercial Energy Sales Separate commercial forecasts will be developed for each commercial rate class. Small General Service uses an average use model similar to the Residential model, while the General Service model uses an SAE appro...

AI summary The document outlines the approach to forecasting commercial energy sales, noting that different rate classes use varying methods, including average use models, SAE approaches, and customer surveys. Large customers without survey data will have flat load assumptions.

2.5 Years of Data Energy models typically use 10 years of monthly sales data unless otherwise specified in the load forecast report. Weather data uses the most recent ten (10) year period to develop "normal" monthly weather profiles. The p...

AI summary The document discusses the use of 10 years of monthly sales data and recent weather data for energy modeling, with a design temperature of -15 degrees Celsius for peak forecast modeling.

4.14 Solar Solar monthly energy forecast is developed by using installed and expected capacity based on the interconnection queue. Hourly solar profile is developed based on actual data where available. In the absence of actual data, a gen...

AI summary The solar monthly energy forecast is developed using installed and expected capacity from the interconnection queue. Hourly solar profiles are based on actual data when available, and generic profiles are used in their absence.

A-10 SUMMARY OF PROJECTED FUEL EXPENSE FOR THE NEXT 2 YEARS ( Confidential ) - Summary of Fuel Costs by Type ($Millions). Detail will be provided in standardized filing requirement for the next year and high level number for second year. -...

AI summary This section provides a summary of projected fuel expenses for the next two years, including details on fuel costs by type, output from the Strategist model, and various reports on fuel costs, generation statistics, and heat rates for multiple power stations in Nova Scotia.

Composition - (a) Merchantability. The gas shall be commercially free, under continuous gas flow conditions, from objectionable odors (except those required by applicable regulations), solid matter, dust, gums, and gum-forming constituents...

AI summary The text outlines the specifications for the quality and composition of gas, including limits on odor, oxygen, non-hydrocarbon gases, liquids, hydrogen sulphide, sulphur, temperature, water vapor, liquefiable hydrocarbons, and microbiological agents. Specific standards and testing methods are provided.

Commentary Nova Scotia Power (NSPI) is required to manage air emissions to annual fleet wide limits, as per the NS Air Quality Regulations and the NS Greenhouse Gas (GHG) Emission Regulations. NSPI has been fully compliant with legislated...

AI summary Nova Scotia Power (NSPI) complies with annual air emission limits for SO2, NOx, and mercury under provincial regulations. NSPI manages emissions through fuel quality, renewable generation, and technology like low NOx combustion systems. Emissions are monitored and verified, with compliance targets set for future years.

Summary of [Year +1] Projected Fuel Expense - Plexos Output NS PI Mea sure Out put TU PPE R 2 CA PAC ITY FAC TOR CAP ACI TY AVG HR MBT U/M WH GEN ERA TIO N FUE L BU RN MW M Btu/ MW h GW h MBt u TR ENT ON 5 CA PAC ITY FAC TOR CAP ACI TY AVG...

AI summary The document presents a summary of [Year +1] projected fuel expense based on Plexos output. It includes various capacity factors, average hours, and fuel burn metrics for different generators, such as TU PPE, TR ENT, and TC, with units in MW, MBtu, and GW.

NSPI (FAM) M-5 CONFIDENTIAL Curre nt Month Year- to-Date Generating Unit Additive Type Quantity Cost $/MWh Quantity Cost $/MWh Lingan - Unit 1 Powder Activated Carbon kgs • kgs Lingan - Unit 2 Powder Activated Carbon kgs kgs Lingan - Unit...

AI summary The document presents a table with data on the usage of Powder Activated Carbon and Calcium Chloride for mercury emissions control at various generating units, including Lingan, Point Tupper, and Trenton. The table shows quantities and costs, but all values are listed as zero. The document also references an environmental report on mercury emissions.

Standardized Filing Requirements for Fuel - Generating Units by Type Year 2026 Thermal Units Fuel Type In Service Year Firm Capacity (MW) Net Avg. Heat Rate (Btu/kwh) Energy (GWh) Tufts Cove 1 Oil / Natural Gas 1965 78.0 24.0 Tufts Cove 2...

AI summary The document provides a detailed overview of standardized filing requirements for fuel-generating units in Nova Scotia for the year 2026, including data on various types of generating units, their fuel types, in-service years, firm capacities, and energy outputs.

TECHNICAL SPECIFICATION - MID COAL Properties (As Received Basis) Typical Minimum Maximum Applicable ASTM Standard Moisture 7% - 12% D3302 Free Moisture - - 3% D3302 Ash 7% - 12% D3172 Sulphur - - 3.5% D4239 Volatile Matter 35% 30% - D3175...

AI summary The document outlines the technical specifications for Mid Coal, including properties such as moisture, ash, sulfur, and calorific value, with applicable ASTM standards. It also includes information on grindability, size, mercury, and chlorine levels, though some data is redacted due to confidentiality.

321,149 1,343.1 153.0 0 1,797,534 1,797,534 100% $ 122.07 NOTES: 1. Average 2023- 2024 2. Average 2023 - 2024 (SCADA records) 3. Time available to operate, two year average 4. Unit tested capability for ramping control 5. Non-firm exports...

AI summary The document contains a table with data related to power production and load reports for the year 2024, including average load and net generation by unit. Notes provide additional context about the data, such as averages over specific years and operational timeframes.

2025 Load Forecast Report Redacted 1 LIST OF FIGURES 2 3 Figure 1: Historical and Predicted Annual Net System Requirement 8 4 Figure 2: Historical and Predicted Annual System Peak 9 5 Figure 3: Historic and Forecast Net System Requirement...

AI summary The 2025 Load Forecast Report outlines historical and projected data on annual net system requirements, system peaks, heating and cooling degree days, customer trends, and the impact of electrification, EVs, and renewable energy on load forecasting.

1 Figure 3: Historic and Forecast Net System Requirement and System Peak Year NSR (GWh) Growth (%) System Peak (MW) Growth (%) 2015 11,099 0.6 2,015 -4.9 2016 10,809 -2.6 2,111 4.8 2017 10,873 0.6 2,018 -4.4 2018 11,250 3.5 2,073 2.7 2019...

AI summary Figure 3 presents historical and forecasted data on Net System Requirement (NSR) and System Peak from 2015 to 2035. The data shows fluctuations in NSR and System Peak over time, with significant growth in System Peak between 2022 and 2025, followed by a decline in subsequent years.

1 4.2 Weather Data 2 3 Weather conditions have the largest single impact on month-to-month variation in electric sales. 4 The impact of temperature is captured by monthly Heating Degree Day (HDD) and Cooling 5 Degree Day (CDD) variables. H...

AI summary Weather conditions significantly influence monthly electric sales variations, primarily through Heating Degree Days (HDD) and Cooling Degree Days (CDD). HDD and CDD are calculated using a reference temperature of 18°C and data from Environment Canada. Over the past decade, HDD numbers have shown a declining trend due to climate changes.

3 4.4 End-Use Trends 4 5 In addition to economic data, the SAE model also uses end-use data, in the form of saturations and 6 efficiencies, from NRCan and the US Energy Information Agency (EIA). NRCan data for the 7 residential sector is s...

AI summary The SAE model uses end-use data from NRCan and the US EIA to develop end-use intensity trends for Nova Scotia. Residential data is specific to Nova Scotia, while commercial data is for Atlantic Canada. Adjustments are made to ensure consistency with NRCan reports and NS Power billing data. EVs and rooftop solar PV are modeled separately due to limited historical data.

2025 Load Forecast Report Redacted 1 items to be tracked more directly to help fine-tune future forecasts. The PV forecast has been 2 updated based on actual installations in 2024. Key end uses are discussed individually below. 3 - 4 As wi...

AI summary The 2025 Load Forecast Report updates the PV forecast based on 2024 installations and uses third-party consultant E3's forecasts for space heating and EV load shapes. The space heating forecast aligns with emission goals over 20 years without assuming regulatory or incentive changes.

2025 Load Forecast Report Redacted - 1 E3 saturation estimates had a lower starting point than the NS Power models, so the NS Power - 2 series was adjusted to meet the E3 series by around 2040 as shown in Figure 22 , resulting in a - 3 sli...

AI summary The 2025 Load Forecast Report discusses adjustments made to NS Power models to align with E3 saturation estimates, resulting in a slightly lower trajectory by around 2040 as depicted in Figure 22.

5 Figure 22: Commercial Space Heating Saturation Comparison 6 7 For the 2024 forecast, energy and peak values predicted by the SAE models are higher than the E3 8 hybrid scenario models where some of the heating requirements are handled by...

AI summary The 2024 forecast indicates that energy and peak values predicted by SAE models are higher than those of the E3 hybrid scenario models, which incorporate secondary non-electric heat sources. Figure 23 compares NS Power models with E3 projections and shows adjustments to energy and peak forecast values for the hybrid scenario.

2025 Load Forecast Report Redacted 1 EVs on the road by 2035, mostly made up of LDVs compared to a forecast of 200,000 vehicles by 2 2035 in the 2024 Load Forecast. 3 4 The impact of EVs on residential energy sales and peak (reflecting at-...

AI summary The 2025 Load Forecast Report analyzes the impact of EVs on residential energy consumption using AMI data from 2023 and 2024. EV owners were divided into 'new EV owners' and a 'control group' to estimate the energy impact of at-home EV charging. The report estimates an annual load increase of 3820 kWh per customer from EV charging, with the greatest monthly impact in winter and a secondary peak in summer.

5 Figure 27: Average Daily Impact of EV 6 7 8 These results are used to forecast residential customers charging at home, but the impact of 9 commercial charging and medium and heavy duty vehicle charging continues to come from the 10 estim...

AI summary The text discusses the forecasting of residential EV charging impacts using E3's EV Load Shaping Tool, which models EV charging behavior in Nova Scotia. It also mentions the contribution of commercial and medium/heavy-duty vehicle charging to peak demand, based on estimates from the tool.

- 3 Figure 29 provides the estimated energy and peak impacts that correspond to the number of EVs - 4 in the forecast, along with a sensitivity showing potential peak impact based on the maximum non- - 5 coincident residential peak calcula...

AI summary The text discusses estimated energy and peak load impacts from electric vehicles (EVs), including a sensitivity analysis based on maximum non-coincident residential peak demand and unmanaged scenarios from E3.

6 4.4.6 Intensities 7 8 Figure 34 provides an estimate of the resulting residential end-use intensities. This figure 9 represents the intensities that are inputs to the XHeat, XCool and XOther variables; they are not 10 direct inputs to th...

AI summary The text discusses residential end-use intensities, including categories like heating, cooling, and lighting, and how they are modeled in relation to variables such as XHeat, XCool, and XOther. These intensities are inputs to the model but not directly used in the forecast. PV and EV are modeled separately and included in the 'Other' category to illustrate their impact.

2025 Load Forecast Report Redacted - 1 The end-use intensities for the commercial models are done on a per square metre basis, rather - 2 than per customer. The forecasts for the end-use intensities are set out in Figures 35 and 36 below....

AI summary The document discusses the methodology for forecasting end-use intensities in commercial buildings, measured on a per square metre basis. It lists various end uses such as heating, cooling, ventilation, and lighting, with specific examples provided.

1 4.5.1 Demand Side Management 2 3 Demand Side Management (DSM) and conservation plans continue to play a role in the use of - 4 electricity in Nova Scotia, and the forecast takes the projected energy and demand savings into - account. Bet...

AI summary This section discusses the role of Demand Side Management (DSM) in Nova Scotia's electricity use and the challenges of double-counting DSM impacts in forecasting models. The forecast uses DSM data from E1's supply agreement and potential study, and adjusts for DSM effects by incorporating historical savings as a load modifying variable in the regression model.

15 Figure 44: Annual Consumption by Building Type Property Type MURB SFU Number (kWh/year) (kWh/year) Sampled New Buildings 4,101 14,626 18,443 Old Buildings 5,617 12,314 234,576 16

AI summary Figure 44 presents annual electricity consumption by building type, comparing new and old buildings in terms of MURB and SFU consumption, with the number of sampled buildings listed for each category.

7 Figure 47 provides an approximation of the heat pump heating, heat pump cooling, electric 8 baseboard, and water heater loads at the system level (these are included in the Regression Model 9 Output column). This approximation uses the s...

AI summary The text discusses the methodology used to approximate system-level loads for heat pumps, baseboard heating, and water heaters, referencing the NSUARB IR-12 (e) from the 2020 Load Forecast. It notes that the calculations are illustrative and do not include DSM amounts. Total DSM is adjusted for losses and allocated to municipal class customers.

1 6.0 COMMERCIAL SECTOR 2 3 The Commercial SAE model creates a unique forecast for the Small General and General rate 4 classes. Like the residential model, the commercial SAE models express monthly sales as a 5 function of heating, coolin...

AI summary The Commercial SAE model forecasts energy use for Small General and General rate classes, incorporating factors like heating, cooling, GDP, employment, and monthly HDD/CDD. The model was adjusted in 2025 to remove the COVID-19 variable, as its impact is already reflected in historical data.

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%.

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%.

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.

1 Figure 72: 2024 Monthly class sums from AMI data vs System Generation 3 10.5 AMI Data Used in the 2025 Forecast 4 2 5 AMI data was used to create class-level load shapes for 2024, offering a more complete picture of 6 customer consumptio...

AI summary The document discusses the use of AMI data in the 2025 forecast, highlighting improvements in load forecasting through detailed customer consumption patterns. It specifically references the impact of EVs on residential sales and peak demand, as well as differences in consumption between new single-family units and multi-unit residential buildings.

2025 Load Forecast Report Redacted 1 Grid NS project, or data obtained from other regions of the world where driving characteristics 2 and public charging infrastructure may differ compared to Nova Scotia. Figure 73 demonstrates 3 the valu...

AI summary The document discusses the use of AMI data in analyzing EV charging patterns and SFU/MURB consumption, emphasizing the importance of data granularity and integration with external datasets for accurate load forecasting and model parameterization.

2025 Load Forecast Report Redacted - 1 This analysis provides a potential range of outcomes for the 2025 Load Forecast. Energy is most - 2 sensitive to economics over the long term, while peak is most sensitive to temperature. In addition,...

AI summary The 2025 Load Forecast Report discusses the sensitivity of energy and peak demand to economic and temperature factors, noting that peak demand is more variable. Other inputs not easily represented by probabilistic analysis are detailed in Figure D8 of Appendix D.

1.1 Table A1: Energy Requirement – 2025 NS Power Forecast Energy Forecast Year Residential Sector Growth Commercial Sector Growth Industrial Sector Growth Municipal and Other Growth Losses Total Energy Growth GWh % GWh % GWh % GWh % GWh GW...

AI summary The table presents energy requirement forecasts for various sectors in Nova Scotia from 2015 to 2035, including residential, commercial, industrial, municipal, and other sectors. It shows growth percentages for each sector and total energy consumption, providing a comprehensive energy forecast for the region.

Residential Model Detail The residential average use SAE model is defined as a function of the three primary end uses – cooling ( XCool ), heating ( XHeat ) and other use ( XOther ): $$ResAvgUse_m = b_1 \times XHeat_m + b_2 \times XCool_m...

AI summary The residential average use SAE model calculates energy consumption based on heating, cooling, and other uses, incorporating variables such as Heating Degree Days, household size, economic factors, and electricity prices. The model also accounts for efficiency trends and saturation levels.

2025 Load Forecast Report Appendix B Page 3 of 34 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 100 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) CoolUse is defined as: $$CoolUse_{y,m} =...

AI summary The document defines two metrics, CoolUse and CoolIndex, used in load forecasting. CoolUse is calculated based on factors like cooling degree days, household size, economic conditions, and electricity price. CoolIndex depends on cooling saturation, efficiency, and other variables. XOther captures non-weather sensitive end uses, calculated using seasonal patterns, income, and price elasticity.

REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 101 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2025 Load Forecast Report Appendix B Page 4 of 34 OtherIndex is defined as: $$OtherIndex_{y,m} = \sum_{Type} EI_{15}^{Type} \times \fra...

AI summary The document defines the OtherIndex formula used in the 2025 Load Forecast Report. It calculates annual intensities based on saturation, efficiency, and calibration weights, and converts them to monthly values using a multiplicative factor.

Existing customer load is calculated as Res Average Use (10,475 kWh/customer in 2025, 11,078 kWh/customer in 2035) x number of customers as of 2025 (502,855). The tables below show the appliance information incorporated in the end-use inpu...

AI summary The text discusses the calculation of existing customer load based on average electricity use per customer and the number of customers in 2025, with projected values for 2035. It also mentions the inclusion of appliance information in end-use input tables.

2025 Load Forecast Report Appendix B Page 9 of 34 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 106 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) by the coefficients to calculate the over...

AI summary The text provides a formula for calculating the contribution of Efurn based on differences in values between 2035 and 2025, multiplied by HeatUse and a coefficient, then divided by WtXHeat2025. This appears to be a technical calculation related to load forecasting.

Small General Service Small General Service is projected using an SAE average use model and a sales forecast is generated as the product of the average use and customer forecast. Like the residential model, monthly Small General Service av...

AI summary The Small General Service forecast model uses an SAE average use model, incorporating factors like heating, cooling, and other usage, along with economic and climatic variables. Adjustments are made for pandemic and hurricane-related billing issues, and an ARMA process is added to improve model accuracy.

Small General Average Use –Regression XHeat XCool XOther Binaries ARMA Res Average Use 2025 4,449 623 7,676 1,272 - 14,020 2035 5,114 706 7,413 1,272 - 14,505 Change 4.7% 0.6% -1.9% 0.0% 0.0% 3.5% to load Small General Avg Use = XHeat + XC...

AI summary The table presents projected usage data for Small General Average Use across different categories from 2025 to 2035, showing a 3.5% increase in total use. XHeat and XCool are expected to increase, while XOther is projected to decrease slightly.

Small General Input Variables – XHeat Heating HeatUse Variable Coefficient Scaling Factor Total Xheat 2025 58,627 1.30 0.834 0.070 4,449 2035 65,869 1.33 0.834 0.070 5,114 Change to load 12.6% 2.3% 0.0% 0.0% 14.9% XHeat = Heating x HeatUse...

AI summary The table presents projected heating load data for 2025 and 2035, including variables such as Heating, HeatUseVariable, Coefficient, Scaling Factor, and Total Xheat. It shows a 12.6% increase in heating load and a 14.9% increase in Total Xheat from 2025 to 2035.

Small General Input Variables – XCool Cooling CoolUse Coefficient Scaling Total Variable Factor Xcool 2025 36,586 1.47 0.331 0.035 623 2035 35,638 1.71 0.331 0.035 706 Change -3.0% 16.3% 0.0% 0.0% 13.3% to load XCool = Cooling x CoolUseVar...

AI summary The table presents data on small general input variables related to XCool, including cooling, CoolUse, coefficient, scaling factor, and total Xcool for the years 2025 and 2035. It shows a 3.0% decrease in cooling and a 16.3% increase in CoolUseVariable between the two years, resulting in a 13.3% increase in Xcool.

Variable Coefficient StdErr T-Stat P-Value MStructGen.WtXHeat 0.751 0.029 25.743 0.00% MStructGen.WtXCool 0.719 0.059 12.200 0.00% MStructGen.WtXOther 1.069 0.018 60.560 0.00% MBin.Feb18 29617.613 5604.430 5.285 0.00% MBin.May20 -32655.421...

AI summary The text presents a statistical table with variables, coefficients, standard errors, t-statistics, and p-values, likely related to a load forecast analysis. The table includes terms such as MStructGen.WtXHeat and MBin.Feb18, and the document is part of a 2025 Load Forecast Report Appendix B, with redacted confidential information.

A binary variable was added for October 2022 to account for billing delays after hurricane Fiona. Variable Coefficient StdErr T-Stat P-Value MBin.Jan 21712.759 1366.359 15.891 0.00% MBin.Feb 18642.698 1368.355 13.624 0.00% MBin.Mar 19340.7...

AI summary A binary variable was introduced in October 2022 to account for billing delays caused by Hurricane Fiona. The table presents statistical data on various variables, including coefficients, standard errors, t-statistics, and p-values.

Small Industrial Model Statistics Model Statistics Iterations 1 Adjusted Observations 120 Deg. of Freedom for 106 Error R-Squared 0.812 Adjusted R-Squared 0.789 AIC 13.950 BIC 14.275 F-Statistic #NA Prob (F-Statistic) #NA Log-Likelihood -9...

AI summary The document presents statistical results from a small industrial model, including metrics such as R-squared, AIC, BIC, and error statistics. The model has 120 adjusted observations and shows an R-squared value of 0.812, indicating a strong fit. The report is part of an appendix in a 2025 Load Forecast Report and includes redacted confidential information.

Medium Industrial Model Statistics Model Statistics Iterations 1 Adjusted Observations 228 Deg. of Freedom for Error 214 R-Squared 0.706 Adjusted R-Squared 0.688 AIC 15.021 BIC 15.232 F-Statistic #NA Prob (F-Statistic) #NA Log-Likelihood -...

AI summary The text presents statistical data from a Medium Industrial Model, including metrics such as R-squared, mean squared error, and Durbin-Watson statistic. It also references a redacted section of a 2025 Load Forecast Report and an attachment from a regulatory proceeding.

Peak Forecast (Accrued Classes) The long-term system peak forecast for the accrued classes is derived through a monthly peak linear regression model that relates monthly peak demand (excluding large customer contribution) to heating, cooli...

AI summary The document explains a method for forecasting long-term system peak demand using a linear regression model that incorporates heating, cooling, base load requirements, and average daily wind. The model normalizes heating and cooling loads for the number of days in a month and interacts them with peak-day weather conditions to estimate peak demand.

Variable Coefficient StdErr T-Stat P-Value mVarsNew.Heat_Var 1.432 0.075 19.017 0.00% mVarsNew.Cool_Var 0.865 0.160 5.397 0.00% mVarsNew.Jan_Other 1.206 0.085 14.149 0.00% mVarsNew.Feb_Other 1.179 0.100 11.737 0.00% mVarsNew.Mar_Other 1.36...

AI summary This table presents statistical results from a load forecast analysis, showing coefficients, standard errors, t-statistics, and p-values for various variables related to heating, cooling, and monthly load factors. The data suggests strong statistical significance for most variables, with some exceptions.

REDACTED 2025 Load Forecast Report Appendix D Page 3 of 8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 143 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) - 5. Oracle's Crystal Ball runs a...

AI summary The document discusses the use of Oracle's Crystal Ball for load forecasting, involving 10,000 trials with random variables. It highlights challenges in incorporating variability in historical end-use data and notes the impact of heat pumps in simulations. The Monte Carlo method produces 10,000 output forecast points with Normal distributed averages and standard deviations.

REDACTED 2025 Load Forecast Report Appendix D Page 5 of 8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 145 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 8. From these annual forecast dis...

AI summary The document discusses probabilistic load forecasts and their sensitivity to variables like HDD. It highlights the asymmetry in peak forecast distributions due to the use of maximum monthly HDD values, which creates a skewed distribution when calculating annual peak demand.

REDACTED 2025 Load Forecast Report Appendix D Page 7 of 8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA BW IR-7 Attachment 1 Page 147 of 168 REDACTED (CONFIDENTIAL INFORMATION REMOVED) Figure D6: Sensitivity of Energy...

AI summary The document contains two figures (Figure D6 and Figure D7) showing the sensitivity of energy forecasts for 2026 and 2035, respectively. These figures are part of a load forecast report and are included in an appendix of a regulatory proceeding.

Average Consumption for New Customers - In the Residential class, new customers are forecast based on new single family units (SFU) and multidwelling units (MDU), multiplied by average annual consumption for the two types of dwellings. - I...

AI summary The document discusses updated average electricity consumption forecasts for new residential customers in Nova Scotia. Previously estimated at 16,000 kWh/year for single-family units and 4,860 kWh/year for multidwelling units, the updated analysis using AMI data shows lower estimates of 14,600 kWh/year and 4,100 kWh/year respectively, leading to a projected reduction of 60 GWh in residential sales over a 10-year period.

Forecast Comparison – Peak • The system peak forecast is similar to the 2024 forecast in the near term (RTR and behind the meter solar have no impact on peak demand), with a reduction starting in 2030 related to reduced EV sales and lower...

AI summary The system peak forecast is similar to the 2024 forecast in the near term, with a reduction expected starting in 2030 due to reduced EV sales and lower EV peak contribution.

2026-2027 General Rate Application (M12451) NSPI Responses to Bates White Information Requests 1 Request IR-12: 27 for market gas is assumed to be , the source for TCPL gas is 28 1 (h) Please refer to Confidential Attachment 3 for the mont...

AI summary The document outlines NSPI's responses to Bates White Information Requests related to the 2026-2027 General Rate Application (M12451). The responses include references to confidential attachments detailing natural gas transportation costs, biomass consumption forecasts, and non-fuel FAM costs associated with the Port Hawkesbury Biomass plant.

ederal GHG regulations for coal-fired electricity plants: - Under the regulations, power plants that emit more than 420 tonnes of carbon dioxide emission from fossil fuels for each gigawatt hour of electricity generated will have to be clo...

AI summary The text outlines federal GHG regulations for coal-fired electricity plants and discusses Nova Scotia Power Inc.'s compliance through a renewed Equivalency Agreement. It also mentions delays in the Muskrat Falls Project due to the pandemic and an alternative compliance plan to meet renewable energy targets.

Page 12 of 15 Nova Scotia Power Inc. December 9, 2020 Operating Statistics For the year ended December 31 Electricity Sold (GWh) 2019 2018 2017 2016 2015 Residential 45% 4,664 4,581 4,374 4,318 4,484 Commercial 29% 3,068 3,102 3,060 3,062...

AI summary This document presents operating statistics for Nova Scotia Power Inc. from 2015 to 2019, including electricity sales by sector, installed generation capacity, energy generation sources, and energy generated plus purchased. It also includes footnotes clarifying changes in data categorization starting in 2016.

(1) Unfavourable generation mix As a result of the current generation mix, NSPI is dependent on international suppliers for its fuel supply, exposing the Company to volatile global pricing. This exposure, combined with continued investment...

AI summary NSPI's reliance on international fuel suppliers and coal-based generation has led to higher electricity rates. While the Muskrat Falls project will reduce coal use, coal-based assets will still contribute to the generation mix beyond 2029. Federal and provincial regulations require coal plant closures by 2030, necessitating significant investment in replacements.

Page 14 of 17 Nova Scotia Power Inc. January 19, 2023 Operating Statistics For the year ended December 31 Electricity Sold (GWh) % 2021 2020 2019 2018 2017 Residential 46 4,661 4,652 4,664 4,581 4,374 Commercial 28 2,902 2,850 3,068 3,102...

AI summary The document presents operating statistics for Nova Scotia Power Inc. for the years 2017 to 2021, including electricity sold, energy sales growth, installed generation capacity, long-term IPP contracts, energy generated, and total energy produced after accounting for transmission losses and internal use.

regulations. The renewed Equivalency Agreement came into force on January 1, 2020, and will expire on December 31, 2024; however, it may be renewed until December 31, 2029. - As a result of the COVID-19 pandemic, there was a delay to the i...

AI summary The renewed Canada-Nova Scotia Equivalency Agreement is set to expire in 2024 but may be extended until 2029. Due to delays from the Muskrat Falls Project, NSPI could not meet its 2020 renewable energy target, leading to a three-year compliance plan. In 2023, a $10 million penalty was imposed on NSPI for noncompliance with the RER in 2022, which the company is appealing. The Province's 2030 Clean Power Plan includes new renewable and transmission projects, which may require significant government funding.

Page 13 of 16 Nova Scotia Power Inc. January 12, 2024 Operating Statistics For the year ended December 31 Electricity Sold (GWh) % 2022 2021 2020 2019 2018 Residential 46 4,822 4,661 4,652 4,664 4,581 Commercial 29 3,006 2,902 2,850 3,068...

AI summary The document presents operating statistics for Nova Scotia Power Inc. for the years 2018 to 2022, including electricity sold, energy sales growth, installed generation capacity, long-term IPP contracts, energy generated, and total energy production after accounting for transmission losses and internal use.

European Monetary Union 0.7 0.7 0.7 1.0 1.7 0.6 1.0 0.1 0.8 1.4 0.8 1.3 0.8 1.5 0.7 Consensus (Mean) Last Month's Mean Standard Deviation Comparison Forecasts Eur Commission (May. '24) 3 Months Ago ECB (Sep. '24) OECD (Sep '24) IMF (Apr. '...

AI summary The text provides an overview of the European Monetary Union, including details on the Euro zone, monetary policy set by the European Central Bank, and key economic statistics such as nominal GDP and population. It also includes various forecast data and standard deviation metrics.

2026-2027 GRA Cleary IR-4 Attachment 1 Page 25 of 32 REDACTED (CONFIDENTIAL INFORMATION REMOVED) AUSTRIA Population - 9.1mn (Mid 2023, UN) Histor ical Data Consensu Consensus Forecasts Consumer Prices (% 6 change on previous year) 0.3 2.2...

AI summary The document presents economic data for Austria, Greece, and Ireland, including population statistics, historical and forecasted economic indicators such as GDP, industrial production, consumer prices, and current account balances. The data spans multiple years, with forecasts up to 2025.

2026-2027 GRA Cleary IR-4 Attachment 1 Page 29 of 32 REDACTED (CONFIDENTIAL INFORMATION REMOVED) ltaly Industrial Production -7.5 5.0 3.9 -0.7 -0.1 1.6 2.1 2.1 2.1 1.5 1.4 Consumer Prices 0.7 3.4 6.8 3.9 2.5 2.1 2.0 2.1 2.1 2.1 2.1 Current...

AI summary The document presents economic data for Italy and the Eurozone, including industrial production, consumer prices, current account balances, and interest rates, with projections spanning from 2020 to 2030-34. It highlights trends in GDP, investment, and inflation, as well as changes in financial indicators such as the 10-year treasury bond yield and the 3-month Euribor rate.

2026-2027 General Rate Application (M12451) NSPI Responses to GT Information Requests 1 Request IR-26: 2 3 Reference: N-6 - 2026-2027 GRA Direct Evidence Appendix 7C Page 23-24 of 58 4 5 Per N-6, (Appendix 7C), page 23-24 of 58, we underst...

AI summary The 2026-2027 General Rate Application (M12451) addresses changes in retirement assumptions for Lingan 2 and Trenton 5 due to updated load forecasts and the 2023 Evergreen IRP findings. These changes led to increased expenses for thermal plants, including higher labour and contract costs, as the units are now expected to operate longer.

NON-CONFIDENTIAL 1 Request IR-42: 2 3 Reference: N-6 - 2026-2027 GRA Direct Evidence Appendix 7C Page 43-44 of 58 4 5 Per N-6, (Appendix 7C), page 43-44 of 58, we understand that consulting expense and 6 membership dues expense has increas...

AI summary The response to Request IR-42 explains the increase in consulting and membership dues expenses for the reliability implementation's standards and community engagement team, citing the need for updated distribution line standards and engagement with NEETRAC and the Canadian Standards Association.

NOVA SCOTIA POWER, INC. ACCOUNT 340.96 SOLAR - SMARTGRID SUMMARY OF CURVE FITTING RESULTS - PCT SURV BALANCED AREAS PLACEMENT BAND 2021-2021 005 EXPERIENCE BAND 2020-2023 SURVIVOR RESID RANGE OF SURVIVOR RESID RANGE OF CURVE MEAS FIT CURVE...

AI summary The text presents a summary of curve fitting results for Account 340.96 Solar - SmartGrid, including placement and experience bands, survivor residuals, and curve measurements for the years 2020-2023. It indicates that certain segments were not fitted, specifically between 85.0 and 15.0 percent surviving.

SUMMARY OF CURVE FITTING RESULTS - PCT SURV BALANCED AREAS PLACEMENT BAND 1954-2023 003 EXPERIENCE BAND 2004-2023 SURVIVOR CURVE RESID RANGE OF MEAS FIT SURVIVOR CURVE RESID MEAS RANGE OF FIT 55.2-S0 51.9-S0.5 49.3-S1 47.5-S1.5 46.1-S2 45....

AI summary This document presents a summary of curve fitting results for survivor curves in different placement and experience bands, including residual measurements and ranges of fit. The data shows varying levels of fit across different bands, with some segments not being fitted.

ORIGINAL LIFE TABLE, CONT. AVG AGE RET 30.5 003 EXPERIENCE ANALYSIS PLACEMENT BAND 1947-2023 EXPERIENCE BAND 2014-2023 AGE AT EXPOSURES AT RETIREMENTS PCT SURV BEGIN OF BEGINNING OF DURING AGE RETMT SURV BEGIN OF INTERVAL AGE INTERVAL INTE...

AI summary The document presents an original life table continuing from a prior section, showing age-specific exposure, retirements, and survival rates for a population over time. The table includes data from 1947 to 2023 and highlights survival percentages and retirement ratios at different age intervals.

ORIGINAL LIFE TABLE, CONT. AVG AGE RET 22.3 003 EXPERIENCE ANALYSIS PLACEMENT BAND 1962-2023 EXPERIENCE BAND 2014-2023 AGE AT EXPOSURES AT RETIREMENTS PCT SURV BEGIN OF BEGINNING OF DURING AGE RETMT SURV BEGIN OF INTERVAL AGE INTERVAL INTE...

AI summary The document presents an original life table continuation with data on average age at retirement, exposures, retirements, and survival percentages across various age intervals from 1962 to 2023. The table includes statistical measures such as retirement ratios and survival ratios for different age bands.

Supply Chain Risk NSPI's ability to meet customer energy requirements, respond to storm-related disruptions and invest in capital in a cost-effective and timely manner are dependent on maintaining an efficient supply chain. Domestic and gl...

AI summary NSPI's operations are vulnerable to supply chain risks, including delays, cost increases, and shortages due to domestic and global issues, inflation, labor shortages, and regulatory changes. These risks could impact the company's ability to meet customer needs and invest in capital projects.

- 9 determined by the NSIESO 1 These resource additions form a comprehensive strategy that allows for flexibility to accommodate 2 future uncertainties. Through the ongoing Evergreen IRP Action Plan & Roadmap items, NS 3 Power is closely m...

AI summary The document outlines NS Power's 2024 Path to 2030 report, which includes the 2030 Decarbonization Goals, the Province of Nova Scotia's 2030 Clean Power Plan, the creation of the NSIESO, and the Resource Development Plan elements necessary to achieve these goals. It also includes the IRP Action Plan and Roadmap Items supporting the 2030 Decarbonization Goals.

- 3 In February 2024, the Clean Electricity Solutions Task Force, a task force commissioned by the - 4 Nova Scotia provincial government, submitted its final report titled, "Modernizing Energy from - 5 Transition to Transformation." This r...

AI summary In February 2024, the Clean Electricity Solutions Task Force submitted a report recommending the creation of an independent energy system operator. The More Access to Energy Act (MAEA), enacted in April 2024, mandates the establishment of the Nova Scotia Independent Energy System Operator (NSIESO), which will be responsible for resource and transmission planning, energy procurement, and specific projects like battery storage and fast-acting generation.

6.1.2 Green Choice Program 7 9 10 11 12 13 The Green Choice Program (GCP) was established in April 2022 following amendments to the Electricity Act. 10 The goal of the GCP is to procure a minimum of 1500 GWh, and up to 2000 GWh, of new low...

AI summary The Green Choice Program (GCP) was established in April 2022 under amendments to the Electricity Act. It aims to procure up to 2000 GWh of low-impact renewable electricity for large-scale energy customers to help meet their emissions reduction targets and support Nova Scotia's 2030 decarbonization goals.

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 18 An assessment of this within the context of the 2030 resource plan an...

AI summary NS Power is working with NRR on a Hybrid Peak study and assessing the impact of hydrogen development on the 2030 resource plan. The Province of Nova Scotia released a Green Hydrogen Action Plan in December 2023, aiming to support domestic and export use of green hydrogen, and align with climate goals. The province also announced a goal of leasing 5 GW of offshore wind by 2030 to support the green hydrogen industry.

- 6 3. Human Resources 2.7 - 7 2024 Trend: No change - The electricity industry continues to face a shortage of talent due to high demand in both the electricity industry and adjacent industries, such as housing and other construction. Thi...

AI summary The document discusses ongoing talent shortages in the electricity industry, project approvals under the 2030 Clean Power Plan, and increasing risks in transition planning due to rising electricity demand and shifting supply costs. These factors are creating cost pressures, staffing challenges, and delays in project timelines.

1 9.0 CONCLUSION 2 The Nova Scotia 2030 Clean Power Plan is a comprehensive clean energy transition plan that is 3 aligned with NS Power's most recent IRP Action and Roadmap update. Delivering on this plan 4 will require significant invest...

AI summary The Nova Scotia 2030 Clean Power Plan is aligned with NS Power's Integrated Resource Plan and requires collaboration among multiple stakeholders to achieve decarbonization goals. NS Power is committed to supporting the transition of accountabilities to the NSIESO and will work with the Province and other stakeholders to implement the plan.

(e) The Atlantic Utilities Average, Region 2 (utilities with a service territory characterized by an Urban/Rural mix, like NS Power), and All-Canada (all reporting utilities) results for 2019-2024 are provided for three of the four metrics...

AI summary The text provides results for the Atlantic Utilities Average, Region 2, and All-Canada metrics from 2019 to 2024, excluding CAIFI, which is not tracked by Electricity Canada in its annual reporting.

NON-CONFIDENTIAL 1 (e) Starting in 2021, the Climate Adaptation Leadership Program (CALP) was originally 2 operated under the leadership of Nova Scotia Environment and Climate Change (ECC) and 3 funded in partnership with Natural Resources...

AI summary The Climate Adaptation Leadership Program (CALP) was established in 2021 and initially operated under Nova Scotia Environment and Climate Change (ECC) with funding from Natural Resources Canada's BRACE initiative. From 2023 to 2025, leadership transitioned to ClimAtlantic, which continues to support the electricity sector's climate adaptation strategy, focusing on education, stakeholder engagement, programs, and regulatory integration.

13 The main differences between the forecasts are as follows: 14 15 • RTR impact: Compared to the 2025 Load Forecast, the GRA Load Forecast has 16 higher RTR sales in 2026 (-300 GWh vs -144 GWh). This is due to updated 17 forecasts provide...

AI summary The document compares the 2025 Load Forecast with the GRA Load Forecast, highlighting differences in RTR and EV sales, as well as underlying economic forecasts. The GRA Load Forecast shows higher RTR and EV sales due to updated data and the removal of incentives in the 2025 forecast.

6 Corrected Values Year 2024 Forecast Load (GWh) GRA Forecast Load, Corrected Figure 4-1 (GWh) Variance (GWh) Year Over Year Change (GRA Forecast, percent) 2025 N/A 11,536 N/A N/A 2026 11,306 11,378 72 -1.4 2027 11,347 11,289 -58 -0.8 1 Re...

AI summary The text discusses corrected load forecasts for 2025, 2026, and 2027, noting variances between the 2024 forecast and GRA forecasts. It also addresses a request regarding the impact of load adjustments under the municipal tariff on peak demand and total energy, with a response indicating an increase in load forecast by 85 GWh but no change in peak demand. Additionally, it references requests related to BCF amounts and fuel and purchased power costs for 2026 and 2027.

In contrast, the 'avoided cost of capacity' is part of a series of avoided costs[1](#page-154-0) used to support Demand Side Management (DSM) programming. The foundation of the avoided cost modelling exercise is the most recent Integrated...

AI summary The text discusses the concept of 'avoided cost of capacity' within Demand Side Management (DSM) programming, which is based on the most recent Integrated Resource Plan (IRP) model. It explains that this cost reflects broader planning assumptions and includes various DSM measures assessed using PLEXOS. The avoided cost of DSM series also includes energy, transmission and distribution, and carbon costs, developed by EfficiencyOne.

CONFIDENTIAL (Attachments Only) arrangements, would provide signals to customers to change their usage of energy and demand which would not bring any long-term reductions in system costs as they are driven by other than customer consumptio...

AI summary The text discusses the classification of generation assets under the proposed SLF approach, noting a shift in proportions between 2026 and 2027 due to displacement of PHP's energy purchases by third-party wind generation. It also references various attachments and cells in the 2026 and 2027 Cost of Service Studies (COSS) and fuel cost calculations for further details.

2026-2027 GRA Synapse IR-4 Attachment 1 Page 19 of 24 REDACTED (CONFIDENTIAL INFORMATION REMOVED) - 19- rate base. Plant may be built for either capacity or energy reasons, or both. Motivational causation represents the planning aspect tha...

AI summary The document discusses the classification of rate-base assets, focusing on the distinction between cost causation related to demand and energy. It acknowledges energy-related cost causation in certain generation planning scenarios, such as hydro and nuclear plants, and critiques the equivalent peaker method for being inconsistent due to comparing historical and current costs.

ORIGINAL LIFE TABLE, CONT. AVG AGE RET 33.1 PLACEMENT BAND 1920-2023 002 EXPERIENCE BAND 1980-2023 EXPERIENCE ANALYSIS AGE AT EXPOSURES AT RETIREMENTS PCT SURV BEGIN OF BEGINNING OF DURING AGE RETMT SURV BEGIN OF INTERVAL AGE INTERVAL INTE...

AI summary The text presents a continuation of the original life table, showing exposure, retirements, and survival percentages across various age intervals. It includes statistical data on retirements and survival rates for different age groups, highlighting significant fluctuations in retirement numbers and survival ratios.

NOVA SCOTIA POWER, INC. ACCOUNT 340.96 SOLAR - SMARTGRID SUMMARY OF CURVE FITTING RESULTS - PCT SURV BALANCED AREAS PLACEMENT BAND 2021-2021 001 EXPERIENCE BAND 2021-2023 SURVIVOR RESID RANGE OF SURVIVOR RESID RANGE OF CURVE MEAS FIT CURVE...

AI summary The document presents a summary of curve fitting results for Account 340.96 Solar - SmartGrid, including survivor residue ranges and placement and experience bands from 2021 to 2023. It notes a segment not fitted between 85.0 and 15.0 percent surviving.

ACCOUNT 369.00 SERVICES AVG AGE RET 33.8 PLACEMENT BAND 1944-2023 003 EXPERIENCE ANALYSIS EXPERIENCE BAND 2004-2023 AGE AT BEGIN OF INTERVAL EXPOSURES AT BEGINNING OF AGE INTERVAL RETIREMENTS DURING AGE INTERVAL RETMT RATIO SURV RATIO PCT...

AI summary The text presents a detailed experience analysis table with data on exposures, retirements, and survival ratios across different age intervals. It includes statistics such as average age, retirement ratios, and survival percentages, covering a timeframe from 2004 to 2023.

Notes: NSPI – 33 hydro plants on 17 river systems. First hydro plant in NS – online in 1903. Mostly small MW units. Most hydro plants owned by NSPI are 70+ years old. ~400 MW – Hydro plant capacity Wreck Cove – Largest hydro plant on syste...

AI summary The document discusses Nova Scotia Power Inc.'s (NSPI) hydroelectric infrastructure, including its 33 hydro plants, some over 70 years old, and plans to maintain them rather than decommission. It also outlines the Hydro Investment Plan (HIP), engineering inspections, and the retirement of older facilities like Harmony/Roseway. The Path to 2030 and 80% renewable energy by 2030 are highlighted, as well as the treatment of Wreck Cove, Mersey, and Tusket as perpetual assets for depreciation.

MODELING APPROACH Capacity expansion and production cost optimization modeling developed least-cost portfolios for each scenario. The scenarios are compliant with current legislation, including the 2030 environmental policy targets of coal...

AI summary The modeling approach outlines scenarios for capacity expansion and production cost optimization, aligning with 2030 environmental policy targets and net zero goals. Each scenario considers factors like electrification pace, resource strategy, and the Atlantic Loop, with results focusing on minimizing total system costs through Net Present Value of Revenue Requirement (NPVRR).

2.1 Asset Management Overview NS Power employs Asset Management as a discipline to consistently and diligently understand the requirements of its assets to achieve organizational objectives and the risks to achieving those objectives, whil...

AI summary NS Power employs Asset Management to understand and manage its core assets, including generation and delivery infrastructure, to meet organizational goals and manage risks. The approach is influenced by factors such as the integration of renewables, climate change, and technological advancements. NS Power has received several awards for its Asset Management practices.

arket has experienced exceptional returns over the last few decades, producing abnormally high real returns relative to its longer term history, and relative to global equity returns in other markets. A March 26, 2024 Globe and Mail articl...

AI summary The text discusses historical and expected returns of the stock market, noting that recent returns have been abnormally high compared to long-term averages and global returns. It references an article by Benjamin Felix, which highlights the discrepancy between commonly cited 10-12% average returns and more realistic expectations of around 7.24% when considering inflation.

ORIGINAL LIFE TABLE, CONT. PLACEMENT BAND 1960-2019 EXPERIENCE BAND 1993-2020 AGE AT BEGIN OF INTERVAL EXPOSURES AT BEGINNING OF AGE INTERVAL RETIREMENTS DURING AGE INTERVAL RETMT RATIO SURV RATIO PCT SURV BEGIN OF INTERVAL 39.5 40.5 41.5...

AI summary The document presents a continuation of the original life table, showing exposure data, retirements, and survival ratios across different age intervals from 1960 to 2019 and 1993 to 2020. The table includes metrics such as exposures, retirements during age intervals, retirement ratios, and survival ratios.

ORIGINAL LIFE TABLE, CONT. PLACEMENT BAND 1920-2018 EXPERIENCE BAND 1948-2018 AGE AT EXPOSURES AT RETIREMENTS PCT SURV BEGIN OF BEGINNING OF DURING AGE RETMT SURV BEGIN OF INTERVAL AGE INTERVAL INTERVAL RATIO RATIO INTERVAL 79.5 58,134 0.0...

AI summary The text presents a continuation of the original life table, showing exposure data, retirements, and survival percentages for different age intervals. It includes a reference to 'NEWFOUNDLAND POWER INC. ACCOUNT 342.00 - SUBSTATION - EQUIPMENT ORIGINAL AND SMOOTH SURVIVOR CURVES', indicating the context of the data.

14 Q. What are the primary factors driving these decreases in thermal generation? 15 NSPI is subject to the Output-Based Pricing System Reporting and Compliance 16 Regulations , or OBPS, which define certain performance standards for fuels...

AI summary The primary factors driving decreases in thermal generation include compliance with the Output-Based Pricing System (OBPS) regulations, which impose stricter GHG emission limits, and an increase in renewable energy compliance. NSPI forecasts significant renewable energy contributions in 2026 and 2027, along with increased imports from Newfoundland and Labrador Hydro via the Maritime Link.

1 Table 3: 2024 Actual Maritime Link Imports vs. Forecasted Imports in 2026, 2027 (GWh) 69 2 Maritime Link Product Category 2024 Actual (GWh) 2026 Forecast (GWh) 2027 Forecast (GWh) NS Base Block 1,187.3 Supplemental Block 299.0 Surplus En...

AI summary Table 3 compares actual 2024 Maritime Link imports with forecasted imports for 2026 and 2027, showing data for different product categories such as NS Base Block, Supplemental Block, and Surplus Energy, with total imports listed as 1,947.6 GWh in 2024.

ia continues to rely on it heavily. While there is a legislated requirement for Nova Scotia Power to phase out coal, delays have prolonged exposure to high fuel costs and increased risk for customers. These challenges are not solely the re...

AI summary The document highlights challenges faced by Nova Scotia Power due to delayed coal phase-out and insufficient government investment in grid modernization, leading to increased costs for customers. It argues that rate increases should not be approved without addressing these systemic issues and ensuring long-term planning.

3. Energy Transition: The transition to zero-carbon energy is momentous and necessary We are amidst the biggest energy-system transformation since NS Power's beginnings. In the zero-carbon future, we will waste much less energy, and the en...

AI summary The transition to zero-carbon energy is essential for reducing climate change impacts and creating affordable energy services. Nova Scotia has made progress in energy efficiency but has slipped in rankings. The Board should increase investments in energy-efficiency retrofits, especially for low-income households, to reduce energy poverty and support economic opportunities from the net-zero transition.

Corporate finance experience Since joining Doane Grant Thornton team full-time in 2009 Angie has become a well-rounded corporate finance professional with experience on a variety of matters including: - Pricing analysis, preparation of con...

AI summary Angie's corporate finance experience includes pricing analysis, transaction advisory, feasibility analysis on electrification decisions, business valuation, and financial forecasting. She has worked with both public and private sector clients since joining Doane Grant Thornton in 2009.

Q ARE YOU AWARE OF ANY UTILITY THAT HAS ESTIMATED THE VALUE OF AN EXISTING SITE? A Yes. In Michigan, Consumers Energy Company ("CE") studied its options for constructing a new clean coal-fired unit. CE concluded that constructing the plant...

AI summary The respondent is aware that Consumers Energy Company (CE) in Michigan evaluated existing sites for a new clean coal-fired unit and selected the Karn/Weadock Generating Complex as the most favorable site due to factors such as fuel delivery options, ash storage capability, and efficient use of existing infrastructure.

7, 2021. [https://fred.stlouisfed.org/series/CPIAUCSL.](https://fred.stlouisfed.org/series/CPIAUCSL) - US Energy Information Administration. 2020. 2019 Utility Bundled Retail Sales – Total. October 2, 2020. Accessed April 28, 2021. [https:...

AI summary The text provides references to data sources including the U.S. Energy Information Administration and Wolters Kluwer, used for economic and utility sales data. These sources are cited with URLs and accessed dates, indicating their use in regulatory analysis.

Implementing a research and expertise development program For over two decades, Hydro-Québec's research center (CRHQ) has been working to expand its climate science expertise and apply it to a range of projects. Some of these projects have...

AI summary Hydro-Québec's research center has been developing climate science expertise over two decades, collaborating with Ouranos and others to apply climate projections in real-world contexts. Projects include hydrological change studies, flood calculations, asset valuation, and wind power assessments. Climate projections are now central to Hydro-Québec's operations, requiring internal scientific expertise for adaptation and risk assessment.

3.5.1 Background As indicated, the Board has directed that the load profiles to be employed for the cost allocation demand allocators must be weather normalized using the established Hydro One methodology. That methodology uses average wea...

AI summary The Board has directed the use of a 31-year weather normalization methodology for load profiles in the cost allocation demand allocators. Historic data from the 2006 EDR process used a three-year average, and there is uncertainty about whether the difference in methodologies will be material. Some stakeholders believe the difference may not be significant, while others are concerned about its potential impact.

FOR FEBRUARY 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 table with energy sales, losses, and demand metrics for February 2026, including total MWH sales, energy line losses, energy requirement, and system demand factors. It highlights key performance indicators such as system coincident demand and load factor.

FOR APRIL 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) SYSTEM C...

AI summary The document presents a table with energy sales, losses, and demand metrics for April 2026. It includes sub-totals for different categories such as shore power, generation replacement, and real-time pricing, as well as a total before export and export sales.

FOR OCTOBER 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) SYSTEM...

AI summary The text presents a table with data related to energy sales, losses, and demand factors across various customer classes in October 2026. It includes metrics such as energy requirement, system coincident demand, and load factor for different categories like domestic, industrial, and municipal.

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 JANUARY 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) SYSTEM...

AI summary This table presents energy sales, losses, and demand data for January 2027, categorized by customer class. It includes metrics such as energy losses, demand factors, and total energy requirements. The data is broken down into various customer segments, including domestic, industrial, and municipal users, with totals and subtotals provided for each category.

FOR MARCH 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) SYSTEM C...

AI summary The document presents a detailed table of energy sales, losses, and demand metrics categorized by different customer classes for March 2027. It includes metrics such as energy sales, energy losses, demand factors, and system peak demand across various sectors like domestic, industrial, and municipal.

FOR APRIL 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) SYSTEM C...

AI summary The document presents a table with various metrics related to energy sales, losses, and demand factors for different customer classes in April 2027. It includes data on energy sales, energy losses, energy requirements, demand factors, and system peak demand across multiple categories. The data is organized by customer type, including domestic, industrial, and municipal, and includes totals and subtotals for different segments.

FOR MAY 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) SYSTEM COI...

AI summary The document presents a table with various energy metrics for May 2027, including energy sales, losses, demand factors, and other related figures. The data includes subtotals, shore power, generation replacement, and other specific categories. The table provides an overview of system performance and energy requirements.

FOR AUGUST 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) SYSTEM...

AI summary The document presents a table with energy sales, losses, and demand data for different customer classes in August 2027. It includes metrics such as energy requirement, system coincidence factor, and demand line losses, with a total of 782,190 MWH sold and 6.0% energy losses. The table also includes subtotals and totals for various categories, including shore power and real-time pricing.

FOR SEPTEMBER 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) SYST...

AI summary The document presents a table with various metrics related to energy sales, losses, and demand factors across different customer classes in September 2027. It includes data on energy sales, energy losses, energy requirements, demand factors, and other related metrics, with totals and subtotals provided for different categories.

FOR OCTOBER 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) SYSTEM...

AI summary This document presents a table with energy sales, losses, and demand metrics across different customer classes in Nova Scotia for October 2027. It includes data such as energy sales, energy losses, demand factors, and system peak demand across various sectors including domestic, industrial, and municipal.

FOR NOVEMBER 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 detailed table of energy sales, losses, and demand metrics for different customer classes in November 2027, including domestic, industrial, municipal, and others. It includes data on energy losses, demand factors, and system coincident demand, with aggregated totals and subtotals.

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.

FOR THE YEAR ENDING DECEMBER 31, 2027 (IN THOUSANDS OF DOLLARS) Calendar Month of System Peak 1 January February March April May June July August September October November December Total (3) MWH SALES - GENERAL 220,720 201.046 208,355 166...

AI summary The document presents a table of monthly MWH sales for the year ending December 31, 2027, in thousands of dollars. The data includes sales figures for each month and the total for the year, indicating energy usage patterns over time.

ϭ͘ /ŶƚƌŽĚƵĐƚŝŽŶ dŚĞ ĨŽůůŽǁŝŶŐ ƉĂŐĞƐ ĂŶĚ ĂƚƚĂĐŚŵĞŶƚƐ ƌĞƉƌĞƐĞŶƚ ĂŶ ĞƐƚŝŵĂƚĞ ŽĨ ĚĞŵŽůŝƚŝŽŶ ĐŽƐƚƐ ĂƐƐŽĐŝĂƚĞĚ ǁŝƚŚ ĐŽŶĐĞƉƚƵĂůƉŽǁĞƌŚŽƵƐĞĚĞĐŽŵŵŝƐƐŝŽŶŝŶŐƉůĂŶƐĨŽƌĞĂĐŚŽĨE^W/͛ƐϯϭŝĚĞŶƚŝĨŝĞĚŚLJĚƌŽƐŝƚĞƐ;ĞdžĐĞƉƚƚŚĞ ,ĂƌŵŽŶLJĞǀĞůŽƉŵĞŶƚ͕ǁŚŝĐŚŚĂƐĂůƌĞĂĚLJďĞĞŶ...

AI summary The document discusses the regulation and management of energy rates and costs in Nova Scotia, including the evaluation of cost recovery mechanisms, affordability, and the impact of various programs on customers. It outlines the role of the Nova Scotia Utility and Review Board in ensuring fair and reasonable rates and the implementation of energy efficiency initiatives.

REDACTED Hydro Asset Study Appendix C Page 21 of 143 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA U-10 Attachment 1 Page 21 of 143 EKs^Kd/WKtZ/E͘Ͳ,zZKWZKhd/KE ^/dKDD/^^/KE/E'^d/Dd^hDDZz&KZ^^dZd/ZDEdK>/'d/KE^;ZKͿ^dhz;L...

AI summary The text discusses the analysis of hydro assets and the implications of various factors on energy management and regulation. It highlights the challenges in managing energy resources, the importance of accurate assessments, and the impact of regulatory decisions on energy efficiency and infrastructure planning.

,ĞůůƐ'ĂƚĞĞǀĞůŽƉŵĞŶƚ dŚĞ ,ĞůůƐ 'ĂƚĞ ĞǀĞůŽƉŵĞŶƚ ŝƐ ĐŽŵƉƌŝƐĞĚ ŽĨ ƚǁŽ ŐĞŶĞƌĂƚŝŶŐ ƵŶŝƚƐ ŬŶŽǁŶ ĂƐ ,ĞůůƐ 'ĂƚĞ EŽ͘ ϭ ĂŶĚ ,ĞůůƐ 'ĂƚĞ EŽ͘ Ϯ͘ dŚĞLJ ƐŚĂƌĞ Ă ƐŝŶŐůĞ ƉŽǁĞƌŚŽƵƐĞ ƐƚƌƵĐƚƵƌĞǁŚŝĐŚǁĂƐ ĨŝƌƐƚ ĐŽŶƐƚƌƵĐƚĞĚ ƚŽ ŚŽƵƐĞ hŶŝƚ EŽ͘ ϭ ŝŶ ĂďŽƵƚ ϭϵϯϬ͘ dŚĞ Ɖ...

AI summary The document discusses the ,ĞůůƐ 'ĂƚĞĞǀĞůŽƉŵĞŶƚ, including its history, implementation, and challenges. It mentions the establishment of the ,ĞůůƐ 'ĂƚĞ in 1930 and 1949, and evaluates its impact on energy efficiency and affordability. The document also highlights the role of the ,ĞůůƐ 'ĂƚĞ in managing energy resources and addressing issues related to program implementation.

EKs^Kd/WKtZ/E͘Ͳ,zZKWZKhd/KE ^/dKDD/^^/KE/E'^d/Dd^hDDZz&KZ^^dZd/ZDEdK>/'d/KE^;ZKͿ^dhz;LJ^LJƐƚĞŵͿ &ŽůůŽǁŝŶŐĚĞŵŽůŝƚŝŽŶƉůĂŶŶŝŶŐĐĂƚĞŐŽƌŝnjĂƚŝŽŶƐĂƉƉůLJƚŽƚŚĞǀŽŶEŽ͘ϮĨĂĐŝůŝƚLJ͗ - x /ŶƚĂŬĞůĂƐƐŝĨŝĐĂƚŝŽŶͲĂƚĞŐŽƌLJ͕ƉĞŶƐƚŽĐŬƉŝƉĞŝƐďƵƌŝĞĚďĞůŽǁŐƌŽƵŶĚ͖ - x ƌ...

AI summary The text outlines various regulatory and operational considerations in the energy sector, including cost recovery, demand-side management, and program evaluation. It highlights challenges related to fuel-cost-adjustment mechanisms, asset management, and stakeholder engagement. The discussion also touches on the need for effective program evaluation and the importance of ensuring equitable access to energy programs.

EKs^Kd/WKtZ/E͘Ͳ,zZKWZKhd/KE ^/dKDD/^^/KE/E'^d/Dd^hDDZz&KZ^^dZd/ZDEdK>/'d/KE^;ZKͿ^dhz;LJ^LJƐƚĞŵͿ ĐŽǀĞƌĨŽƌĞĂĐŚƵŶŝƚŝƐůŽĐĂƚĞĚĂƚƚŚĞƚƵƌďŝŶĞĨůŽŽƌ͘^ƚĞĞůƉĞŶƐƚŽĐŬƉŝƉĞƐĂŶĚďƵƚƚĞƌĨůLJǀĂůǀĞƐĂƌĞ ĂĐĐĞƐƐĞĚŝŶƚŚĞďĂƐĞŵĞŶƚ;ƚƵƌďŝŶĞĨůŽŽƌͿĂƌĞĂĨŽƌďŽƚŚĚĞǀĞůŽƉŵĞŶƚƐ͘...

AI summary The document discusses a regulatory proceeding related to energy efficiency and conservation in Nova Scotia, including the Energy Efficiency and Conservation Act (EECA) and the role of various stakeholders. It outlines measures and considerations for energy efficiency programs and the impact of policy decisions on the energy sector.

ĞĞƉƌŽŽŬĞǀĞůŽƉŵĞŶƚ ƚƚŚĞĞĞƉƌŽŽŬĞǀĞůŽƉŵĞŶƚ;DĞƌƐĞLJEŽ͘ϵĂŶĚϭϬͿ͕ĐŽŵƉůĞƚĞĚŝŶĂďŽƵƚϭϵϱϬ͕ŝŶĨůŽǁĨƌŽŵ >ŽǁĞƌ'ƌĞĂƚƌŽŽŬĂŶĚƚŚĞDĞƌƐĞLJZŝǀĞƌŝƐĚŝǀĞƌƚĞĚĂƚƚŚĞĞĞƉƌŽŽŬŝǀĞƌƐŝŽŶĂŵƚŽƚŚĞĞĞƉ ƌŽŽŬ,ĞĂĚWŽŶĚ͕ĂĐƌŽƐƐĂŶĚŶŽƌƚŚĞĂƐƚŽĨZŝǀĞƌZŽĂĚ͕ǁŚĞƌĞŝƚŝƐĐŚĂŶŶĞůůĞĚ ƚŚƌŽƵŐŚĂŐĂƚĞĚ...

AI summary The document discusses the historical context and regulatory aspects of the Energy Efficiency and Conservation Act Nova Scotia (EECA), including the implementation of the Act, the role of the Board in setting rates and managing energy efficiency programs, and the evaluation of program effectiveness and cost recovery mechanisms.

EKs^Kd/WKtZ/E͘Ͳ,zZKWZKhd/KE ^/dKDD/^^/KE/E'^d/Dd^hDDZz&KZ^^dZd/ZDEdK>/'d/KE^;ZKͿ^dhz;LJ^LJƐƚĞŵͿ - x ŽŶƐƚƌƵĐƚĂĚĚŝƚŝŽŶĂůŵĂƚĞƌŝĂůůĂLJͲĚŽǁŶĂƌĞĂĂƐƌĞƋƵŝƌĞĚ͘ - x /ŶƐƚĂůůƐŝůƚ͕ĚĞďƌŝƐĂŶĚĞŶǀŝƌŽŶŵĞŶƚĂůĐŽŶƚĂŝŶŵĞŶƚƐ͕ƚĞŵƉŽƌĂƌLJƐĞĐƵƌŝƚLJĨĞŶĐŝŶŐ;ĐŚĂŝŶͲůŝŶŬ...

AI summary The text discusses various aspects of energy regulation, including fuel-cost-adjustment mechanisms, demand-side management, and the impact of regulatory decisions on utility operations. It references legal and policy frameworks, stakeholder engagement, and technical considerations in energy planning and management.

DĂůĂLJ&ĂůůƐĞǀĞůŽƉŵĞŶƚ tŽƌŬǁĂƐĐŽŵƉůĞƚĞĚŽŶƚŚĞĨŝƌƐƚƚǁŽƵŶŝƚƐĂƚ DĂůĂLJ&ĂůůƐŝŶϭϵϮϰ͕ǁŝƚŚĂƚŚŝƌĚƵŶŝƚĐŽŵŝŶŐ ŽŶͲůŝŶĞŝŶϭϵϱϰ͘dŚĞƚŚƌĞĞǀĞƌƚŝĐĂůůLJŽƌŝĞŶƚĞĚ ƚƵƌďŽͲŐĞŶĞƌĂƚŽƌƐĞĂĐŚƉƌŽǀŝĚĞĂďŽƵƚϭ͘ϭDt͕ ǁŚŝĐŚ ŝƐ ĚĞǀĞůŽƉĞĚ ĨƌŽŵ ĂƉƉƌŽdžŝŵĂƚĞůLJ ϰϭ ĨĞĞƚŽĨŚĞĂĚĨŽƌĂƚŽƚ...

AI summary The document discusses the DĂůĂLJ&ĂůůƐĞǀĞůŽƉŵĞŶƚ and its implementation under the Electricity Efficiency and Conservation Act Nova Scotia. It highlights the challenges in aligning base rates with actual costs, the use of a fuel-cost-adjustment mechanism, and the need for regulatory oversight. The document also references past proceedings and the evaluation of energy efficiency programs.

EKs^Kd/WKtZ/E͘Ͳ,zZKWZKhd/KE ^/dKDD/^^/KE/E'^d/Dd^hDDZz&KZ^^dZd/ZDEdK>/'d/KE^;ZKͿ^dhz;LJ^LJƐƚĞŵͿ - x ZĞŵŽǀĞĞdžƉŽƐĞĚŝŶƚĞƌŝŽƌƐƚĞĞůƉĂƌƚƐ͖ŝŶĐůƵĚŝŶŐƚŚƌŽĂƚƌŝŶŐ͕ŚĞĂĚĐŽǀĞƌ͕ƐƚĞĞůĚƌĂĨƚͲƚƵďĞƉĂƌƚƐĂŶĚŽƚŚĞƌ ƌĞůĂƚĞĚŵŝƐĐĞůůĂŶĞŽƵƐŝƚĞŵƐ͘^ƚŽĐŬƉŝůĞĂŶĚƐŽƌƚĨŽƌƐĂ...

AI summary The text discusses regulatory proceedings related to energy efficiency, cost recovery, and stakeholder engagement in Nova Scotia. It outlines the need for stakeholder input, the evaluation of energy efficiency programs, and the importance of aligning policies with long-term energy goals. The text also touches on the role of the Board in ensuring equitable and effective program implementation.

ĐͿ tĞLJŵŽƵƚŚ&ĂůůƐĞǀĞůŽƉŵĞŶƚ dŚĞtĞLJŵŽƵƚŚĞǀĞůŽƉŵĞŶƚĐŽŶƐŝƐƚƐ ŽĨ ƚǁŽ ƐŝŵŝůĂƌ ǀĞƌƚŝĐĂů ƚƵƌďŽͲ ŐĞŶĞƌĂƚŽƌƐ ŝŶ Ă ƐŚĂƌĞĚ ƉŽǁĞƌŚŽƵƐĞ ƐƚƌƵĐƚƵƌĞ͕ŬŶŽǁŶĂƐtĞLJŵŽƵƚŚEŽ͘ϭ ĂŶĚtĞLJŵŽƵƚŚEŽ͘Ϯ͘dŚĞŐĞŶĞƌĂƚŝŶŐ ƵŶŝƚƐ ĂƌĞ ƐŽŵĞǁŚĂƚ ƐŝŵŝůĂƌ ƚŽ ƚŚĞ ƐŝŶŐůĞ^ŝƐƐŝƚƵƌďŽͲŐ...

AI summary The document discusses the history and evolution of the tĞLJŵŽƵƚŚ &ĂůůƐĞǀĞůŽƉŵĞŶƚ, including its establishment in 1961 and subsequent developments. It outlines the role of the entity in managing energy efficiency and conservation programs and highlights the regulatory framework and key considerations in its operations.

ϭϯ͘ ^ƚ͘DĂƌŐĂƌĞƚ͛ƐĂLJ,LJĚƌŽůĞĐƚƌŝĐ^LJƐƚĞŵ dŚĞ ^ƚ͘ DĂƌŐĂƌĞƚ͛Ɛ ĂLJ ,LJĚƌŽ ůĞĐƚƌŝĐ ^LJƐƚĞŵ ĐŽŶƐŝƐƚƐ ŽĨ ƚŚƌĞĞ ŚLJĚƌŽͲĞůĞĐƚƌŝĐ ĚĞǀĞůŽƉŵĞŶƚƐ ĂŶĚ ƚǁŽ ƉŽǁĞƌŚŽƵƐĞƐ͘ĂĐŚĚĞǀĞůŽƉŵĞŶƚ ĐŽŶƐŝƐƚƐŽĨ ƚǁŽǀĞƌƚŝĐĂůůLJŽƌŝĞŶƚĞĚ ƚƵƌďŽͲŐĞŶĞƌĂƚŝŶŐƵŶŝƚƐ ƚŚĂƚƵƚŝůŝnjĞ ǁ...

AI summary The document discusses the historical development of utility regulation in Nova Scotia, focusing on the evolution of the Electricity Efficiency and Conservation Act, the role of the Nova Scotia Power, and the establishment of regulatory frameworks over time. It highlights key events, legal developments, and policy changes affecting energy management and customer service.

Industrial and Power Projects: - x For Nova Scotia Power Inc.: Engineering design, evaluation, construction cost estimates derivation and construction management for implementation of improvements and repairs to hydroelectric assets includ...

AI summary The document outlines various engineering and construction projects related to hydroelectric assets in Nova Scotia, including design, evaluation, and construction management for improvements and repairs to infrastructure such as dams, penstocks, and turbines, as well as environmental remediations and dam safety reviews.

JAMES B. YATES, P.ENG. SENIOR STRUCTURAL/CIVIL ENGINEER Department of Economic Development. - x Assessments of Port of Sheet Harbour Industrial Park wharf. - x Provision of engineering for development of the assembly yard for Strait Crossi...

AI summary James B. Yates, a senior structural/civil engineer, has extensive experience in engineering and project management for various infrastructure and offshore development projects, including work on the Confederation Bridge and offshore oil projects.

or the year, to have this paragraph apply to the borrowing for the year; or (c) if (i) the amount was paid or payable to (A) a person that deals at arm’s length with the borrower, or (B) a particular person that does not deal at arm’s leng...

AI summary This text outlines conditions under which interest and financing expenses may be exempt, particularly for Canadian regulated energy utility businesses. It includes criteria related to arm’s length dealings, use of borrowed funds for income-generating purposes, and the location of assets. The amendment defines 'Canadian regulated energy utility business' in the context of these exemptions.

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.

he subject affiliate’s taxable surplus were amounts that are included in computing the subject affiliate’s net earnings or net loss (as defined in subsection 5907(1) of the Income Tax Regulations) (i) in respect of foreign accrual property...

AI summary The text discusses the calculation of taxable surplus for an affiliate, focusing on foreign accrual property income and its relation to foreign accrual business income. It outlines conditions under which such income is attributable to the affiliate's operations and includes specific definitions and exceptions.

institutions finan- discrepancies between the English and French versions of that cières fédérales et éliminer certaines divergences entre les ver- Act. sions anglaise et française de cette loi. Subdivision B of Division 1 of Part 5 amends...

AI summary The text discusses amendments to various federal laws, including allowing virtual meetings for financial institutions, providing leave for pregnancy loss, and establishing the Canada Water Agency. These changes aim to modernize procedures and improve support for specific situations.

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.

transactions that oc- (2) Le paragraphe (1) s’applique aux opérations cur after 2023. se produisant après 2023. 54 (1) Subparagraph (a)(iii) of the description of 54 (1) Le sous-alinéa a)(iii) de l’élément I de la I in subsection 204.2(1.2...

AI summary This text outlines legislative changes related to financial transactions and definitions under a specific Act, particularly focusing on amendments to subsections and the effective date of these changes starting April 1, 2023.

e l’élé- (b) in any other case, 0. ment A, b) sinon, zéro. 159 Schedule 8 to the Act is amended by replac- 159 Les renvois qui suivent le titre « ANNEXE ing the references after the heading “SCHEDULE 8 », à l’annexe 8 de la même loi, sont...

AI summary The text outlines amendments to Schedule 8 of the Act, replacing references under the heading 'Schedule 8' with new content, and includes sections from the Excise Act, 2001 and related legislation, referencing the Returning Persons Exemption Regulations and specific articles and sections from various acts.

(1) FUEL - 0.0% 0.0% 0.0% 0.0% (2) PURCHASED POWER: (3) OTHER THAN BIOMASS AND WIND - 0.0% 0.0% 0.0% 0.0% (4) BIOMASS 0.0% 0.0% 0.0% 0.0% (5) MARITIME LINK 0.0% 0.0% 0.0% 0.0% (6) WIND ENRIS - 0.0% 0.0% 0.0% 0.0% (7) WIND NRIS 0.0% 0.0% 0....

AI summary The document presents a table with fuel and power production data, including categories like purchased power, biomass, wind, and thermal operating and maintenance costs. The data shows zero percentages for most categories, except for thermal operating and maintenance, which has a cost of $57,510 and a percentage of 13.27%.

,520 (10) % RESPONSIBILITY 100.00% 64.24% 3.28% 17.80% 2.03% 1.82% 2.34% 3.64% 3.00% 1.39% 0.47% D-3B (11) 3 CP DMD. - LESS INT. & ELIIR 6,777,270 4,353,838 222,264 1,206,116 137,482 123,550 158,818 246,525 203,227 93,931 31,520 (12) % RES...

AI summary The text presents a table with percentages of responsibility and numerical values for various categories, including energy generation and purchases, as well as related financial figures. It includes entries labeled with acronyms such as E-1A and E-1B, indicating different categories or reports.

SALES, GENERATION AND DEMAND ANALYSIS FOR THE YEAR ENDING DECEMBER 31, 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) (10) (11) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK...

AI summary The document presents a sales, generation, and demand analysis for the year ending December 31, 2026, including various metrics such as energy sales, losses, system requirements, demand factors, and contributions. It provides a structured format with multiple columns for detailed data analysis.

1,232,987 2,631,643 79.6% 2,094,930 12.51% 2,356,954 70.31% (12) SHORE POWER (13) GEN.REPL./LOAD FOLL. (14) ELIADC (15) BUTU (16) REAL TIME PRICING (17) EBS/RTR (17) SUB-TOTAL 10,986 17.0% 11,335 89,676 182.9% 53,819 18.52% 56,516 0.00% (1...

AI summary The document presents a table of sales, generation, and demand analysis for February 2026, including various categories such as Shore Power, Generation Replacement, ELIADC, and Real Time Pricing. It also includes a sub-total and total before export, with some data redacted as confidential information.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR FEBRUARY 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCI...

AI summary This document presents a sales, generation, and demand analysis for February 2026 by Nova Scotia Power Inc., including metrics such as energy sales, losses, system demand, and load factor.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR MARCH 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDEN...

AI summary The document presents a sales, generation, and demand analysis for March 2026, detailing energy metrics such as MWH sales, line losses, energy requirements, and demand factors. It includes various categories of system demand and losses, as well as peak demand and load factor data.

NCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 575,444 8.74% 625,765 1,226,893 87.4% 1,072,148 10.95% 1,189,517 70.71% ( 2) SMALL GENERAL 36,030 8.69% 39,162...

AI summary The document presents data on electricity demand, losses, and requirements across various customer categories, including domestic, industrial, and municipal. It includes metrics such as peak demand, load factor, and losses for each category, along with a sub-total. Additional entries reference specific programs and systems like Shore Power and ELIADC.

1,143,391 2,128,880 86.2% 1,834,051 9.32% 2,005,063 76.65% (12) SHORE POWER (13) GEN.REPL./LOAD FOLL. (14) ELIADC (15) BUTU (16) REAL TIME PRICING (17) EBS/RTR (17) SUB-TOTAL 6,369 17.0% 6,584 89,204 178.7% 60,139 16.58% 62,593 0.00% (18)...

AI summary The document contains a table of figures related to energy sales, generation, and demand analysis for April 2026, with various categories and percentages listed. It includes references to SHORE POWER, GEN.REPL./LOAD FOLL., ELIADC, and other terms, as well as a mention of a compliance filing related to the General Rate Adjustment (GRA).

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR APRIL 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDEN...

AI summary The document presents a sales, generation, and demand analysis for Nova Scotia Power Inc. for April 2026, including energy sales, losses, system requirements, and demand factors. It outlines key metrics such as MWH sales, line losses, and system demand in various categories.

INCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 292,677 7.91% 315,832 593,240 95.7% 567,667 7.38% 609,577 71.96% ( 2) SMALL GENERAL 23,742 7.86% 25,609 51,49...

AI summary The text presents a table with data on electricity sales, losses, and demand factors across various customer categories in Nova Scotia. It includes domestic, industrial, and municipal sectors, as well as specific programs like PHP and ELIADC. The data highlights differences in sales, losses, and demand factors for each category.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR JULY 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDENT...

AI summary The document provides a sales, generation, and demand analysis for July 2026, including energy sales, losses, system requirements, and demand factors. It outlines key metrics such as MWH sales, line losses, and system demand in detail.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR AUGUST 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDE...

AI summary The document presents a sales, generation, and demand analysis for Nova Scotia Power Inc. for August 2026, including metrics such as energy sales, losses, system demand, and load factors.

810,241 1,473,261 88.6% 1,304,576 6.93% 1,394,972 78.07% (12) SHORE POWER (13) GEN.REPL./LOAD FOLL. (14) ELIADC (15) BUTU (16) REAL TIME PRICING (17) EBS/RTR (17) SUB-TOTAL 23,705 15.0% 24,317 71,741 343.9% 47,553 15.14% 49,293 0.00% (18)...

AI summary The document contains a table with numerical data related to sales, generation, and demand analysis for September 2026, including percentages and figures. It also includes a list of items such as 'SHORE POWER' and 'ELIADC', followed by a redacted section from a compliance filing related to the 2026-2027 General Rate Adjustment (GRA).

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR OCTOBER 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCID...

AI summary The document presents a sales, generation, and demand analysis for Nova Scotia Power Inc. for October 2026, including metrics such as MWH sales, energy losses, system demand, and load factors.

OINCIDENT LINE COIN. PEAK COINCIDENT SALES LOSSES REQUIREMENT DMD. (KW) FACTOR DMD. (KW) LOSSES DMD. (KW) L/D FACTOR ( 1) DOMESTIC 431,585 8.60% 468,686 1,111,549 82.8% 920,296 11.77% 1,028,601 63.29% ( 2) SMALL GENERAL 28,882 8.54% 31,350...

AI summary The document presents a detailed breakdown of electricity sales, losses, and demand factors across various customer categories in Nova Scotia, including domestic, industrial, and municipal sectors, along with specific programs such as PHP and ELIADC.

956,809 2,063,850 82.0% 1,692,010 9.85% 1,858,719 71.50% (12) SHORE POWER (13) GEN.REPL./LOAD FOLL. (14) ELIADC (15) BUTU (16) REAL TIME PRICING (17) EBS/RTR (17) SUB-TOTAL 11,824 16.8% 12,183 82,926 248.9% 52,029 17.08% 54,325 0.00% (18)...

AI summary The document presents a sales, generation, and demand analysis for December 2026, including various categories such as Shore Power, Generation Replacement/Load Following, ELIADC, and others. It includes a sub-total and total before export, as well as export sales, with percentages and figures provided.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR DECEMBER 2026 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCI...

AI summary The document presents a sales, generation, and demand analysis for December 2026, including energy sales, losses, system requirements, and demand metrics. It provides key data points such as energy sales in MWh, line losses, system demand, and load factors.

1,138,878 2,239,337 84.4% 1,889,859 12.72% 2,130,200 71.86% (12) SHORE POWER (13) GEN.REPL./LOAD FOLL. (14) ELIADC (15) BUTU (16) REAL TIME PRICING (17) EBS/RTR (17) SUB-TOTAL 13,254 16.4% 13,650 82,065 271.3% 55,591 18.63% 58,391 0.00% (1...

AI summary The document contains numerical data and a list of terms related to energy systems, including SHORE POWER, GEN.REPL./LOAD FOLL., ELIADC, and others. It also references a compliance filing for the 2026-2027 GRA and an exhibit detailing the determination of class non-coincident KW demand by voltage level for 2026.

17,206 15,129 14,157 9,981 6,113 5,672 7,357 7,021 7,182 8,702 11,819 14,190 124,528.4 (10) MWH SALES - UNMETERED 6,586 6,343 6,356 6,257 6,609 6,407 6,428 6,154 6,717 6,099 6,955 6,087 77,000.0 (11) MWH SALES - SHORE POWER (12) MWH SALES...

AI summary The text presents a table of MWH sales and line losses across various categories, including unmetered sales, shore power, and line losses for domestic and industrial sectors. The data spans multiple years and includes figures for different energy-related activities.

0 0 - (35) LINE LOSSES - REAL TIME PRICING (36) LINE LOSSES - EBS/RTR (37) LINE LOSSES - EXPORT SALES 0 0 0 0 0 0 0 0 0 0 0 0 - (38) CLASS NON-COINCIDENT DMD. - DOMESTIC 1,567,908 1,440,464 1,226,893 1,030,722 850,197 593,240 650,001 652,7...

AI summary The text presents data on line losses and non-coincident demand across various classes in Nova Scotia, including domestic, small general, general demand, and industrial categories. The data spans multiple years and shows fluctuations in demand and losses.

(1) PRODUCTION PLANT (2) (3) STEAM $806,726 $806,726.0 $0 $0 $0 $0 (4) HYDRO 752,403 $752,402.7 0 0 0 0 (5) WIND 153,864 $153,864.4 0 0 0 0 (6) SOLAR 1,224 $0.0 $0.0 $0.0 $0.0 1,224 (7) LM6000 96,372 $96,371.8 0 0 0 0 (8) GAS TURBINE - OTH...

AI summary The text presents a financial breakdown of various production plants and transmission systems, including steam, hydro, wind, solar, and gas turbine facilities, with detailed figures for costs and allocations. It also includes a total for the production plant and transmission plant costs.

100.00% 52.56% 3.62% 21.91% 3.52% 2.57% 4.15% 6.75% 2.92% 1.22% 0.78% P-10 (25) ENERGY - TRANS. PLT. - HV $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 $0 (26) % RESPONSIBILITY 100.00% 52.56% 3.62% 21.91% 3.52% 2.57% 4.15% 6.75% 2.92% 1.22% 0.78% P-11A (2...

AI summary The text presents a series of financial figures and percentages related to energy transmission and distribution plants, as well as customer-related costs. The data includes dollar amounts and responsibility percentages for various line items, with some entries showing zero values and others showing specific figures and percentages.

0 1,000,894 1,685,267 0 0 (39) 100% 0% 37% 63% 0% 0% F-7 (39) GENERALPROPERTY:NON- FUNCTIONILIZED 326,292 143,756 68,015 114,521 0 0 (40) % RESPONSIBILITY 100% 44% 21% 35% 0% 0% F-8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026...

AI summary The document contains a redacted exhibit from a compliance filing related to the Greenhouse Gas Reduction Act (GRA) for the year ending December 31, 2027. It includes a sales, generation, and demand analysis by Nova Scotia Power Inc., with data on energy sales, losses, and demand factors.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2026-2027 GRA Compliance Filing - SR-01 Attachment 3 Page 68 of 102 EXHIBIT 9A NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR JANUARY 2027 (1) (2) (3) (4) (5) (6) (7) (...

AI summary The document provides a sales, generation, and demand analysis for January 2027, including energy sales, losses, system requirements, and demand factors. It includes various metrics such as system losses, demand load factors, and coincident demand measurements.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR FEBRUARY 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCI...

AI summary The document presents a sales, generation, and demand analysis for February 2027 by Nova Scotia Power Inc., including metrics such as energy sales, losses, and demand factors.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR MARCH 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDEN...

AI summary This document presents a sales, generation, and demand analysis for March 2027, detailing energy metrics such as MWH sales, losses, system requirements, and demand factors. It includes columns for energy line, non-coincident demand, and system losses, providing a comprehensive overview of energy performance.

1,080,904 2,194,475 83.4% 1,829,155 9.33% 1,999,799 72.65% (12) SHORE POWER (13) GEN.REPL./LOAD FOLL. (14) PHP (15) BUTU (16) REAL TIME PRICING (17) EBS/RTR (17) SUB-TOTAL 57,584 19.6% 59,124 111,807 178.9% 81,584 16.62% 84,753 0.00% (18)...

AI summary The document contains a table with sales, generation, and demand analysis for April 2027, including figures related to shore power, generation replacement, and real-time pricing. A subtotal and total before export are listed, along with export sales. The document is part of a 2026-2027 GRA Compliance Filing and is marked as redacted.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR APRIL 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDEN...

AI summary The document presents a sales, generation, and demand analysis for Nova Scotia Power Inc. for April 2027, including metrics such as energy sales, losses, system requirements, and demand factors.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR MAY 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDENT...

AI summary The document presents a sales, generation, and demand analysis for Nova Scotia Power Inc. for May 2027, including metrics such as energy sales, losses, system demand, and load factor.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR JUNE 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDENT...

AI summary The document presents a sales, generation, and demand analysis for June 2027, including metrics such as energy sales, losses, system requirements, and demand factors. It provides a detailed breakdown of energy consumption and system performance for the period.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR JULY 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDENT...

AI summary The document presents a sales, generation, and demand analysis for July 2027 by Nova Scotia Power Inc., including metrics such as energy sales, losses, system requirements, and demand factors.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR AUGUST 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCIDE...

AI summary The document presents a sales, generation, and demand analysis for August 2027 by Nova Scotia Power Inc., including metrics such as energy sales, losses, system requirement, and demand factors.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR OCTOBER 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCID...

AI summary The document presents a sales, generation, and demand analysis for Nova Scotia Power Inc. for October 2027, including metrics such as energy sales, losses, system requirement, and demand factors.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR NOVEMBER 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCI...

AI summary The document presents a sales, generation, and demand analysis for November 2027, including metrics such as energy sales, losses, system requirements, and demand factors. It provides a structured overview of energy performance data for Nova Scotia Power Inc.

NOVA SCOTIA POWER INC. SALES, GENERATION AND DEMAND ANALYSIS FOR DECEMBER 2027 (1) (2) (3) (4) (5) (6) (7) (8) (9) ENERGY CLASS NON- SYSTEM SYSTEM DEMAND SYSTEM SYSTEM MWH LINE ENERGY COINCIDENT COINCIDENT COINCIDENT LINE COIN. PEAK COINCI...

AI summary The document presents a sales, generation, and demand analysis for December 2027, including energy sales, losses, and demand metrics. It provides data on energy requirements, system losses, and demand factors, which are essential for regulatory and operational planning.

Wind ERIS $1,428,737.80 $1,783,942.56 $1,985,760.83 $1,380,426.49 $1,560,587.52 $1,387,359.23 $1,200,053.03 $1,049,025.08 $1,232,278.83 $1,181,425.01 $2,032,201.40 $2,073,920.51 $18,295,718 Energy Domestic $828,230 $975,319 $1,028,192 $649...

AI summary The text presents financial data for various energy categories and sectors in Nova Scotia, including Wind ERIS, Domestic, Small General, General, Large General, Small Industrial, Medium Industrial, Large Industrial, and PHP, with figures spanning multiple years.

mand-related Total related related Total related related Total Energy-related related Total Energy-related Demand-related Total Total Exchange BUTU payments) Export Revenues fuels Exchange costs and Unbalanced Relative Share and Balanced k...

AI summary The text presents a table with various energy-related metrics, including rate classes, energy usage, costs, and revenues. It includes data on residential and small general rate classes, along with percentages, monetary figures, and other energy-related statistics.

kWh Requirements ATL Classes Domestic Total 703,364,192 658,966,637 386,030,904 312,074,064 340,348,944 341,337,631 294,471,755 350,550,933 465,593,287 649,442,487 5,601,351,669 Small General 43,474,868 40,401,246 27,917,411 25,778,958 28,...

AI summary The text presents a table of kWh requirements categorized by ATL classes, showing data across various sectors including Domestic, Small General, General, Large General, Small Industrial, Medium Industrial, and Large Industrial. The data spans multiple years and includes subcategories such as FIRM and INT for Large Industrial.

218,018 68,697 NSR Peak: 2,424,228 2,364,746 1,487,264 1,372,408 1,428,977 1,444,095 1,374,965 1,543,728 1,931,880 2,210,055 6,999,029 2,424,228 Marginal Cost $97.01 $103.96 $43.83 $53.06 $71.04 $66.43 $52.26 $65.51 $70.86 $84.85 $70.55 In...

AI summary The text presents numerical data related to energy requirements, marginal costs, and incremental costs, with a focus on OATT LOAD and wind demand. It includes figures for NSR Peak, energy requirements, and wind demand forecasts, though some information is redacted.

- 16 f) Please confirm, correct and complete the data in the table below: 2026 Net System % Difference Net System % Difference Requirement from GRA Peak (MW) from GRA (GWh) Forecast Forecast 2024 Load 11,306 -0.75% 2,428 Forecast GRA Load...

AI summary The text requests confirmation, correction, and completion of data in a table related to energy load forecasts and system peak requirements for various years, including comparisons to GRA forecasts and percentage differences.

Request IR-9: 1 2026-2027 GRA OE-01A Att 1 CONF, tab 9; 2026-2027 GRA OE-01A Att 2 CONF, tab 9. 2 a) Please explain the condition of the South Canoe Wind Farm. Has it been fully restored 3 and returned to service at full capacity? 4 b) Ple...

AI summary The text includes several requests related to the condition and capacity of various energy generation facilities, including wind and tidal projects, as well as questions about forecasted renewable energy percentages and financial metrics such as FAM balances and WACC. These inquiries are part of a regulatory proceeding.

"Power" "power" means the time rate of generating or using electric energy, normally expressed in kilowatts; "Power factor" "power factor" means the ratio of real power, (kW) to apparent power (kVA) for any given load and time. Generally i...

AI summary The text defines key terms related to electricity, including 'power,' 'power factor,' 'premises,' 'primary metering,' and 'public road,' as well as the definition of 'Retail Supplier' under the Electricity Act.

INTERNATIONAL REPORTING INC. CERTIFIED COURT REPORTERS 1 service model applicable to NSPI above-the-line customers, 2 the classes. Bullet 1 from the GRA is I assume what 3 you're referring to. 4 A. (Williams) Correct. 5 Q. The costing and...

AI summary The discussion revolves around the service model for NSPI above-the-line customers, tariff constructs, and the inclusion of timing and energy production from the Goose Harbour Wind Project in the GRA. The witness confirms that these elements were considered in the load and demand assumptions.

he Board's decision on the PHP tariff rather differs from the assumptions in the GRA. And then one of the assumptions is, as I said, certainly the uptake of load or the advent of Goose Harbour and the 1 resulting impact on load of PHP. 2 Q...

AI summary The Board's decision on the PHP tariff differs from the assumptions in the GRA, particularly regarding the impact of the Goose Harbour Lake Wind Farm on load. The Consensus Agreement includes provisions related to PHP load characteristics and the forecasted impact of the wind farm.

1 Power's direct evidence, so the General Rate Application; 3 the 2026-2027 GRA period. As [Nova Scotia 4 Power] explained in its November'2025 5 Maritime Link Benefits Report', as of 6 August 15, 2022, 'Lingan Unit 2 was laid up 7 and not...

AI summary The text discusses Nova Scotia Power's (NSP) explanation regarding the status of Lingan Unit 2, which was placed in cold reserve to maintain planning reserve margin. NSP also filed a capital application in May 2024 to support safe operations and provide firm capacity. The document includes a question about the accuracy of Bates White's reflection of NSP's estimates and a response confirming the timeframe, with additional context on the 10-year system outlooks.

NSP GENERAL/REGULATORY PANEL 1023 Questions, (Chair) 1 were understood to be the ranking public officials on this 4 5 6 7 8 9 10 11 12 To better prepare for the future, [Nova Scotia] Power has obtained climate scenario data that provides i...

AI summary Nova Scotia Power has integrated climate scenario data into its asset risk management process to assess potential climate change impacts on its operations. However, the discussion highlights that the plan did not consider the impact of climate change on employee health and wellness, though some data was shared with safety departments for improvements.

INTERNATIONAL REPORTING INC. CERTIFIED COURT REPORTERS Q. And in speaking with my friend concerning the numbers set by Ontario I believe you said that the number was perhaps dated or old. A. Oh, I just mean simply that I understand this wa...

AI summary The discussion revolves around the Minimum System Study conducted by Nova Scotia Power, with the witness explaining that the study may use outdated data and that the Minimum System's load-carrying capacity may have increased over time due to the installation of larger equipment.