N-52024-2025 Bates White FAM Audit Report - Redacted
19 passages
arried out by the Fuels Finance team,68 serves as an additional control through maintenance of the balance sheet, (e.g., accounts receivable, accounts payable), settlements, and financial reporting.69 Another key player in NSPI's risk mana...
AI summary This section describes NSPI's risk management structure, focusing on the Fuels Finance team and the Fuels Strategy Table (FST). The FST oversees fuel procurement and hedging activities, with voting members including the President and CEO, COO, and other senior executives. The FST is chaired by the Director of ERM.
II.B.3.b.iii. Risk Management Systems NSPI continues to use Allegro's Energy Trading and Risk Management ("ETRM") software as its energy trading and risk management system. ETRM is used for deal capture, credit and market risk monitoring,...
AI summary NSPI uses Allegro and Aligne Fuels as its energy trading and risk management systems. Allegro is used for deal capture, credit and market risk monitoring, and settlement, while Aligne Fuels is used to manage fuel information from procurement through to consumption. These systems interact with other NSPI systems like Oracle billing. The impact of a cyber event on these systems is discussed further in the report.
II.C. Conclusions Conclusion II-1: NSPI's organizational structure remains reasonable and well defined, with the roles across the organization adequately specified, including responsibilities, which can help create an environment of accoun...
AI summary The conclusions highlight that NSPI's organizational structure, staffing, performance management, and training programs are well-managed and meet industry standards, with experienced personnel across various departments and reasonable attrition forecasting.
III.B.1.e. Short-Term Load Forecast The system operator relies on short-term load forecasts in its day-ahead unit commitment and scheduling processes. NSPI's operations rely on day-ahead, 2-day-ahead, 3-day-ahead, 4-day-ahead, and 5-day-ah...
AI summary The system operator uses short-term load forecasts provided by a third-party vendor for day-ahead scheduling. The vendor's model, based on historical load data and weather forecasts, is monitored for accuracy. After a cyber event in April 2025, forecast accuracy, measured by MAPE, significantly worsened, averaging 10.22% compared to 2.41% before the event.
NSPI explained that in the aftermath of the cyber event, the loss of the Process Information ("PI") system impacted its short-term load forecasting process. Specifically, the short-term load forecasting model lost its automation (from PI)...
AI summary NSPI's short-term load forecasting was significantly impacted by a cyber event, leading to manual updates instead of automated ones. Although NSPI denies biasing the model, the higher MAPE and upward bias suggest an attempt to ensure adequate online resources during the event. This approach, while understandable, may lead to overcommitment of resources, with significant start-up costs for thermal units.
III.B.2. Fuel and Purchased Power Forecasting Fuel and Purchased Power ("F&PP") forecasts are prepared annually and updated quarterly, or more frequently if there are significant changes that suggest the forecast is no longer reliable (suc...
AI summary Fuel and Purchased Power (F&PP) forecasts are prepared annually and updated quarterly using PLEXOS. The process involves dispatch simulation modelling and financial model production. NSPI continued using PLEXOS during a cyber event by accessing local data. The forecasts are reviewed by relevant management teams as per the Fuel Manual.
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.
III.B.2.f. Input Parameter Validation Some PLEXOS input parameters are subject to regular review within NSPI or are provided by the Nova Scotia System Operator, including System Reserve Requirements and Minimum Unit Commitment Constraints....
AI summary The document discusses the validation of input parameters in PLEXOS, noting that some are reviewed internally by NSPI or provided by the Nova Scotia System Operator, while others are maintained by EAM or ERM and updated to align with PortOps. Model calibration values are also adjusted to reflect changes in operating behaviors.
Figure III-6: PLEXOS Assumptions - Q4 2025 Fuel and Purchased Power Forecast Group PLEXOS Assumptions Update Required Notes Update Received Date Lood Base Load forecast - Monthly demand and energy Yes Load unchanged from previous in 2026 a...
AI summary The document outlines assumptions and updates for the PLEXOS model related to load forecasting, hydro generation, tidal storage, and unit performance parameters for Q4 2025. Some updates are required, particularly for load forecasts and maintenance schedules, while others are based on historical data or unchanged from previous models.
annual peak load exceeded actual peak load. These data should not necessarily be a cause for alarm but suggest caution in making long-term decisions based on a single year peak demand forecast values. Conclusion III-5: NSPI completed and r...
AI summary The text summarizes conclusions regarding NSPI's load management and forecasting performance. It highlights successful pilot programs like DERMS, TVP, and CPP in reducing peak demand, while noting a significant decline in forecasting accuracy after a cyber event, with forecasts overestimating actual load in most cases.
VI.D. Recommendations Recommendation VI-1: NSPI should consider revising future biomass supply RFPs to reduce or remove preference for supply contracts of 2-years or greater, given the inability or unwillingness of suppliers to offer such...
AI summary The recommendations focus on revising biomass supply RFPs, clarifying contract terms, and improving the energy balance process to better reflect supply realities and economic dynamics, aiming to enhance participation and fairness in biomass procurement and energy management.
hat may evolve. Bates White offers its perspective on this position noting that the uncertain role of the new NS IESO in procuring gas for any new, gas-fired generation makes NSPI's role less certain. Bates White does not agree with ERM's...
AI summary Bates White disagrees with ERM's position on NSPI's management of natural gas procurement, emphasizing that natural gas is procured dynamically and requires continuous adjustments. Selling unneeded gas or releasing FT capacity is a standard practice, not speculative, and asset managers can manage FT contracts effectively.
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 values for 'Late Day Trades delivered to Baileyville,' including a daily maximum value of $1.90 and a difference of $0.05 on 11/20/2025. The data appears to be related to energy trading activities involving Emera Energy L.P.
3, the bearing was again inspected and the bearing remained in good condition. The bearing was again inspected during the unit's March-April 2024 maintenance outage, and it remained in good condition. The investigation determined that the...
AI summary The root cause analysis found that inaccurate temperature readings from a faulty sensor triggered high temperature alarms at Tufts Cove 3. NSPI replaced the sensor with a more accurate one, resolving the issue. The cause of the faulty readings remains under investigation, with recommendations expected by December 2026. The issue is not expected to recur elsewhere in the fleet.
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.c. Summary We find, like we have found in prior audits, that numerous commitment and dispatch decisions are made outside of PortOps. Many of those decisions are based on experience and knowledge of the marketing desks and NSPSO. For...
AI summary The summary highlights that many commitment and dispatch decisions are made outside of PortOps, often by NSPSO in real time without sufficient cost information. These decisions are influenced by factors like fuel supply and unit restartability. NSPI committed to addressing these issues through the Economic Dispatch Optimization Solution.
XI.B.4. Port Hawkesbury Paper Port Hawkesbury Paper ("PHP") takes service from NSPI under the Extra Large Industrial Active Demand Control ("ELIADC") tariff. The tariff allows NSPI to manage PHP load to reduce system costs to the benefit o...
AI summary Port Hawkesbury Paper operates under the ELIADC tariff, allowing NSPI to manage its load for system cost reduction. However, the methodology for measuring ADC benefits is inadequate, and real-time dispatch deviations impact FAM customers. PHP's load is not consistently used for reserve requirements due to operational interruptions.
Measurement - (a) PHP's final intra-day schedule is indicative of the OM level, but does not necessarily represent the actual load level at which PHP is operating. For example, the final intra-day schedule may be MW placing PHP in OM-8, bu...
AI summary The text discusses discrepancies in measuring PHP's real-time deviations from its intra-day schedule, noting that NSPI's method may not align with actual load levels due to variability in operating points and SCADA metering tolerances. It recommends measuring deviations on an hourly basis for consistency with independent system operators' methods.
transactions do not have costs or benefits in this context. For example, it would not be correct to conclude that there is a dis-benefit in an hour where actual costs are greater than the fixed rate. A potential secondary benefit of active...
AI summary The document discusses the challenges in measuring the costs and benefits of real-time load shifting and deviations in demand control. It highlights that NSPI lacks the tools, such as PortOps software, to quantify these impacts due to low load levels, model convergence issues, and reliance on assumptions.