Topic:"Tariff Design" in M12349

aily Price Elasticity -1.607 +/- 0.317 -0.017 +/- 0.173 Inter-Period Substitution Price Elasticity -0.105+/- 0.005 -0.029 +/- 0.001 18 19 The elasticity values have changed significantly from the prior report, and although the Daily Price...

AI summary The document discusses changes in price elasticity values from prior reports, noting that the Daily Price Elasticity for the TOU rate is significantly higher than previously used in load forecasts, while Inter-Period Substitution values remain similar. These elasticity values impact sales in the SAE model but are less influential than other factors like DSM and EVs.

amount in the response to part (a). Date Filed: August 19, 2025 NSPI (CA) IR-2 Page 1 of 6 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2025 Load Forecast Report (NSEB M12349) NSPI Responses to CA Information Requests NON-CONFIDENTIAL 1 (c)...

AI summary NSPI responds to information requests regarding AMI technology's impact on peak demand, TVP rate performance, and data requirements for load forecasting. Questions focus on timelines for AMI benefits, peak event analysis, TVP savings projections, and data needed for program evaluation.

2025 Load Forecast Report (NSEB M12349) NSPI Responses to NSEB Information Requests NON-CONFIDENTIAL 1 Request IR-19: 2 3 Page 72 of the application explains that NS Power’s model assumes that the Municipal load 4 will be served by a third...

AI summary NSPI responded to NSEB's IR-19 request regarding municipal load service arrangements post-2025. Initially, MEU applied for Backup/Top-up Tariff service but later confirmed they would continue with bundled service in 2026, adjusting the energy supply under the tariff.

2025 Load Forecast Report (NSEB M12349) NSPI Responses to SBA Information Requests NON-CONFIDENTIAL 1 Request IR-8: 2 3 Refer to Report, Section 4.6, Renewable to Retail, page 56 of 94 and respond to the following: 4 5 (a) Will RTR-supplie...

AI summary NSPI responds to SBA Information Request IR-8 regarding the 2025 Load Forecast Report, stating Renewall sets RTR electricity costs, and NS Power cannot compare total costs. The response references the Energy Balancing Service Tariff and Exhibit R-10(ii) from M10293, noting customer usage impacts average costs and that balancing/backup charges apply via specific tariffs.

harges based on usage. The Energy Balancing Service Tariff 29 and Standby Service Tariff provides the charges and credits applied to the LRS for 30 balancing and backup services. Date Filed: August 19, 2025 NSPI (SBA) IR-8 Page 1 of 2 2025...

AI summary NSPI explains that non-participating customers' rates are based on forecasts from General Rate Applications and FAM AA/BA Riders, with variances affecting financials. Participating customers are addressed separately. The Mersey River Wind project by Renewall is the sole renewable source for RTR licensing, with no other suppliers identified.

Date Filed: 07/28/2025 Synapse (NSPI) Page 5 of 12 1 ii. How did the potential study compare to actual demand side management results 2 for the years 2021-2024? Does NS Power and/or E1 believe that the 2019 3 Potential Study accurately pre...

AI summary The text outlines requests for information regarding the accuracy of the 2019 Potential Study on demand-side management (DSM), solar generation data, and new technologies like home batteries. It questions whether DSM projections were met, seeks updates to the study, and asks about assumptions, solar capacity factors, battery cost declines, and compensation for energy export. Topics include DSM evaluation, solar forecasting, and emerging technologies.

response, please provide support for all data and assumptions. 24 25 (f) Please summarize the plans for the TVP Pilot and the longer-term plan for TVP tariff 26 deployment. 27 Date Filed: July 28, 2025 CA (NSPI) Page 3 of 4 1 (g) Please id...

AI summary The text outlines regulatory requests to NS Power for data and analysis on the TVP Pilot program, long-term TVP tariff deployment, and methodological comparisons between aggregate and class-specific forecasting approaches. It seeks details on performance metrics, data requirements, and implications of shifting forecasting methodologies.