Topic:"Load Management" in M12665

REDACTED 2022-2023 FAM Audit Action Plan Update Attachment 1 Page 18 of 18 The next step was to implement a representation of CBL as a basis of comparison to what was actually achieved through load shifting, including seasonal and hourly l...

AI summary The document discusses the implementation of a Cost-Based Load (CBL) scenario as a comparison to load shifting strategies, including seasonal and hourly shifts using forward replacement pricing. The scenario simulates PHP behavior on an embedded LIIR rate and was discussed with Bates White and the FAM Small Working Group during a Q2 meeting. NS Power seeks stakeholder feedback on the recommendation and potential additional analysis.

III.B. Findings NSPI's overall approach to FAM cost forecasting during the Audit Period was similar to the forecasting processes in place in recent years. The long-term load forecast remained the basis for fuel supply planning, investment...

AI summary NSPI's fuel adjustment mechanism (FAM) forecasting approach during the Audit Period remained consistent with recent years, using long-term load forecasts based on customer class models, including SAE models for residential and commercial classes and econometric models for industrial classes. These forecasts inform fuel supply planning and are aggregated into a Net System Requirement (NSR) and annual Load Forecast Report filed with the NSEB.

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.C. Conclusions Conclusion III-1: NSPI's load forecasting approach remains largely unchanged from the prior audit period. NSPI continues to file an annual 10-year load forecast with the Board and allows for stakeholder involvement in th...

AI summary NSPI's load forecasting approach has remained largely unchanged, with annual 10-year forecasts filed with the Board. The 2025 Load Forecast Report predicts a slight decrease in net system requirement due to factors like RTR load migration and increased energy efficiency. NSPI's actual peak loads have been lower than forecasted in recent years, suggesting a trend of over-forecasting.

XIII.B.1.c.iii. 2024 (Third Quarter) Entering the Audit Period, NSPI was in the midst of a two-year sulfur emissions compliance period, which limited NSPI's total SO2 emissions to 31.6 kt in 2024. In November 2023, NSPI implemented a compl...

AI summary NSPI faced challenges in complying with sulfur emissions limits in 2024 and implemented a compliance buffer. It also adjusted its load and surplus energy forecasts, leading to a portfolio rebalancing. NSPI increased its compliance buffer to 6 kt in 2025 and 2026 due to forecast changes and uncertainty around LIL maintenance.

XV.B.5.a. Comparison of FAM and PHP Load Co-optimization of PHP load and NSPI generation should allow for PHP load to be reduced when FAM load is high and system conditions are relatively tight, and to increase PHP load when FAM load is lo...

AI summary The analysis compares the Fuel Adjustment Mechanism (FAM) load and Peak Hour Load (PHP) load, showing a modest inverse relationship (-0.28 correlation) over the audit period. In winter months, the correlation strengthens to -0.74, suggesting benefits from co-optimization. On-peak PHP load is smaller relative to FAM load compared to off-peak periods, consistent with daily co-optimization under the ELIADC.