N-52024-2025 Bates White FAM Audit Report - Redacted
18 passages
, which is filed with the NSEB each year. There were no significant changes to the forecasting methodology and no organizational changes impacting the load forecasting process during the Audit Period. The quantities of the various fuels re...
AI summary The document discusses the forecasting methodology used by NSPI, which involves using the PLEXOS model to estimate fuel requirements based on generating unit characteristics, fuel prices, GHG limitations, and transmission system capacity.
101 NSPI, "Preliminary Outage Report for February 3-5, 2023 Cold Weather Event," M10987, February 21, 2023. 102 NSPI, "Preliminary Outage Report for February 3-5, 2023 Cold Weather Event," M10987, February 21, 2023, page 4. 103 2022-2023 B...
AI summary The document discusses NSPI's Smart Grid Nova Scotia Project, its testing of distributed energy resource management systems, and the impact of various programs on load management and peak demand reduction. It also highlights the cost challenges of residential batteries and the results of the Time Variable Pricing pilot, including load reduction percentages and factors influencing them.
III.B.2.e. PLEXOS Input Information Origination and Maintenance Appendix B of the FAM Plan of Administration documents the FAM Fuel Forecasting Methodology governing the process and assumptions used by NSPI to produce the fuel forecast req...
AI summary This section discusses the origination and maintenance of input information for PLEXOS, including data sources, update procedures, and modeling assumptions used by NSPI. It highlights the roles of EAM and ERM, the exclusion of major unplanned outages, and the modeling of operating reserves in accordance with reliability requirements.
Figure III-6: PLEXOS Assumptions - Q4 2025 Fuel and Purchased Power Forecast Group PLEXOS Assumptions Update Required Notes Update Received Date Generating unit start-up costs / shut down penalties No Updated from the unit performance mode...
AI summary Figure III-6 outlines PLEXOS assumptions for Q4 2025 fuel and purchased power forecasts, including updates to generating unit parameters, wind and tidal energy profiles, fuel prices, and market constraints. Some assumptions require quarterly updates, while others are permanent or unchanged.
IV.C. Conclusions Conclusion IV-1: Consumption of solid fuel was 26.9% higher than the base cost of fuel forecast, due largely to lower than forecasted Surplus Energy, changes in fuel blends, and the sulfur emissions CoV. NSPI's Audit Peri...
AI summary NSPI's solid fuel consumption was 26.9% higher than forecast, driven by lower surplus energy and changes in fuel blends. NSPI relies heavily on imported coal, with South American coal increasing to 52% of total consumption. NSPI has no domestic coal sources and adjusted fuel blends at its plants to meet SO2 emissions constraints. Coal prices moderated during the 2024-2025 audit period.
rm its obligations in accordance with "reasonable Industry Standards," which NSPI stated are generally understood to reflect the practices and performance expected under ordinary operating conditions. The contract language does not explici...
AI summary The text discusses NSPI's obligations under biomass fuel contracts, emphasizing that NSPI is not responsible for incremental costs from fuel management but must cooperate in consuming or removing fuel. NSPI has implemented inventory management improvements to prevent future incidents.
VI.B.10. NSPI's Process for Biomass Fuel Receipt Information NSPI uses the Aligne database in tracking biomass deliveries. NSPI receives all biomass deliveries by truck. Upon arrival, deliveries are weighed using WeighWiz, which is a comme...
AI summary NSPI uses the Aligne database and WeighWiz system to track biomass deliveries, which are then entered into the LIMS system for inventory management. A Senior Contract Administrator for Biomass oversees contract management and invoice verification. A cyber event caused Aligne to be unavailable from April 2025 to October 2025, with limited access for testing and data backfilling continuing through the end of the audit period.
2/15/2024 11/19/2025 11/20/2025 12/20/2025 12/23/2025 1/29/2024 3/14/2024 3/21/2024 3/25/2024 5/19/2024 5/24/2024 5/26/2024 6/30/2024 7/19/2024 7/24/2024 7/25/2024 8/15/2024 8/27/2024 9/11/2024 9/14/2024 12/9/2024 1/17/2025 1/30/2025 2/19/...
AI summary The text presents a table listing dates and associated financial data related to late day trades delivered to Baileyville, including a daily maximum value of $2.15 and a difference of $0.05. The data appears to be related to energy trading activities.
Figure X-8: NSPI's Average Operating Reserve Surpluses Reserve Type Requirement (MW) 2024 Average (MW) 2025 Average (MW) Average Excess (MW) Average Excess (%) 30-Minute Reserve 50 Data unrecoverable 387 337 674% 10-Minute Reserve 168 (cyb...
AI summary Figure X-8 presents NSPI's average operating reserve surpluses for 2024 and 2025, showing significant excess in both 30-minute and 10-minute reserve categories. The data for 2024's 30-minute reserve is unrecoverable, and the 10-minute reserve data for 2024 is impacted by a cyber event.
X.B.3.d.ii. Status and Operation of Lingan 2 The Board considered the issue of the retirement of Lingan 2 and its relation to the commencement of the NS Block volumes in a February 8, 2022 Decision.446 The Board noted that in NSPI's integr...
AI summary The Board addressed the retirement of Lingan 2 in a February 2022 decision, noting that NSPI planned to keep the unit operational until one year after the NS Block commenced. The Board disallowed recovery of Lingan 2 operating costs beyond August 15, 2022, without further approval. NSPI phased out economic dispatch after that date but kept the unit in cold reserve. The IESO forecasts Lingan 2's retirement until 2029/2030, requiring NSPI to maintain the unit for 2-3 additional years.
X.B.6. Power Plant Visits The FAM POA requires the fuel auditor to "[c]onduct on-site inspection for fuel handling, quality control, inventory management and performance monitoring." In May 2026, we completed the following in-person site v...
AI summary The FAM POA requires on-site inspections of fuel handling and inventory management. In May 2026, site visits were conducted at several Nova Scotia Power facilities, including biomass and coal plants, as well as inventory locations. These visits included interviews and facility tours.
Figure X-37: PHB Steam Turbine Performance (in MW) Across Different Steam Production, PHP OM Scenarios. 519 PB3 Average Steam Flow (kg/s) PHP OM Mode Range Steam Turbine Output Range (MW Gross) 60 1 - 9 36 - 40 50 1 - 9 28 - 40 40 1 - 9 19...
AI summary The document presents a table showing the performance of PHB steam turbines under different steam flow and PHP OM scenarios. NSPI conducted further testing with 100% biomass fuel between September 2024 and February 2025, examining fuel moisture levels of 50%, 55%, and 60%.
ll and incorporate the information into the day ahead planning and dispatch process. Each Thursday, a small hydro meeting is held. Each day, Monday through Friday, the following process is followed: • At 7:30 AM, a system evaluation is don...
AI summary The document outlines a daily commitment and dispatch process for energy management, including system evaluations, meetings with various stakeholders, and coordination with the Natural Gas desk and NS Power thermal fleet. It describes the use of the Port Ops model for optimized system dispatch and the involvement of multiple departments in reviewing system load, generation status, and maintenance plans.
XI.B.2.b. Dispatch to Manage Natural Gas Pipeline Pressure and Position Due to recurrent low gas pipeline pressure issues on the M&NP Mainline, NSPI faces a constraint on the use of natural gas at Tufts Cove and PHB, which is sometimes bin...
AI summary NSPI faces challenges managing natural gas pipeline pressure and position, leading to reduced generation output at Tufts Cove. Corrective actions include fuel switching and derating production. While modifying generator outputs is not a concern due to market conditions, the lack of documentation raises concerns about the economic management of pipeline positions.
omass was off-line in percent of all hours. Of the remaining hours, output was above 30 MWh in percent of the hours and below 15 MWh in percent of the hours, with an average output of 25 MWh per hour. Various fuels are used for steam produ...
AI summary The Port Hawkesbury Biomass Generator uses bark, wood chips, and natural gas for steam production, with bark being the lowest cost fuel. Natural gas is used for stabilization and during maintenance periods. Fuel prices and heat rate coefficients are modeled and fixed during the audit period, with the fuel price dropping significantly during a cyber event in April 2025.
Figure XI-12: Annual Generation (MWh)573 Units 2022 2023 2024 2025 Unit 1 Unit 2 Lingan Unit 3 2,180,119 1,532,900 1,559,503 2,195,760 Unit 4 Point Aconi Unit 1 908,652 782,620 782,438 670,857 Point Tupper Unit 2 625,187 480,727 563,036 69...
AI summary Annual generation data across various units in Nova Scotia from 2022 to 2025 is presented, with significant fluctuations in output influenced by natural gas prices and OBPS adders. Higher gas prices in 2025 led to reduced dispatch of gas-fired units like TUC-1 and TUC-3, while solid fuel units were favored due to the OBPS adders.
XI.C. Conclusions Conclusion XI-1: NSPI, to its credit, was able to keep its system running reliably through the period following the cyber event. However, the loss of automation and information required for scheduling and dispatch would h...
AI summary The document highlights NSPI's ability to maintain system reliability post-cyber event but notes inefficiencies and increased costs due to lost automation. It identifies issues with scheduling processes, RTED functionality, and dispatch of PH Biomass. There are concerns about understated system marginal costs and increased GHG emissions. A new Economic Dispatch Optimization Solution is expected to address some inefficiencies.
XV.B.5.b. Comparison of Wind Generation and PHP Load Figure XV-18 provides a comparison over the audit period of 14-day average hourly PHP load and system wind generation. Under ELIADC co-optimization, the expected relationship between the...
AI summary The audit period analysis of wind generation and PHP load under ELIADC co-optimization shows no significant correlation between the two, despite expectations of a positive relationship. Only a weak correlation of 0.14 was observed in the limited data available after a cyber event affected data integrity.