Topic:"Grid Modernization" in M11689

f 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 but research in these areas is ongoing and timelines for significant shifts in this technology 2 are unknown. 3 4 The use of home battery storage was ex...

AI summary The 2024 Load Forecast Report discusses ongoing research into technological shifts and the exploration of home battery storage through the SGNS Project. The project used a utility DERMS as a virtual power plant for grid-aware applications, with performance data presented in the Appendix.

Page 44 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 The technology required for V2G is still in development and is not widely available, but a 2 few manufacturers have included the capability in...

AI summary The text discusses the current state of vehicle-to-grid (V2G) technology, noting that it is still in development and not widely available. It highlights the potential of coordinated distributed energy resources, such as batteries and EVs, to smooth energy demand and mitigate peak loads when managed through a utility DERMS.

Page 91 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 66: Commercial End-Use Peak Shares 2 3 4 5 The trend in the Commercial classes shows that the heating component of the peak is 6 expecte...

AI summary The 2024 Load Forecast Report discusses the increasing impact of heating and commercial EVs on commercial peak demand. It highlights NS Power's shift from using Load Research Samples (LRS) to Advanced Metering Infrastructure (AMI) data for more accurate forecasting.

res, the sum of all the available AMI DATE: April 30, 2024 Page 92 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 meters, per hour, per class, is later adjusted so the monthly totals correspond to r...

AI summary The text discusses the 2024 Load Forecast Report, highlighting how the use of Advanced Metering Infrastructure (AMI) improves the accuracy and smoothness of load shape data compared to previous years, which relied on statistical estimates from Licensed Retail Suppliers (LRS).

2024 Load Forecast Report REDACTED 1 Figure 68: 2023 Monthly Load Research Data vs System Generation 2 3 4 5 Class coincident peak demand forecast using LRS and the AMI future 6 7 The 2024 class contribution to peak analysis is still focus...

AI summary The 2024 Load Forecast Report discusses the use of Advanced Metering Infrastructure (AMI) in forecasting residential peak demand. The report highlights the shift to using AMI data for more accurate load forecasting, focusing on residential class demand due to its weather dependency and reduced noise compared to other classes.

Page 95 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 system peak (the sum of all customer classes) and then AMI informed load factors are used 2 to disaggregate it into all the classes. In the fut...

AI summary The 2024 Load Forecast Report discusses the use of AMI for more accurate load forecasting, including disaggregation of system peak into customer classes, regional forecasting, and testing end-use sensitivities. It also highlights the potential for electrification to impact different regions differently and the importance of updating end-use assumptions.

w of price elasticity estimate 17 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix E Page 18 of 18 Ongoing work for future reports • Integrating AMI data into the sales and peak forecast • Impact of electrific...

AI summary The document outlines ongoing work for future load forecast reports, including integrating AMI data, evaluating the impact of electrification and emissions targets, and assessing new technologies like time variable pricing and direct load control.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to CA Information Requests NON-CONFIDENTIAL 1 Request IR-4: 2 3 Reference: Exhibit N-1, p. 39, lines 21-22. 4 5 (a) Please confirm that the 1.6 kW/vehicle “sensitivity” was used as t...

AI summary NSPI clarifies in its response to IR-4 that the 2024 load forecast uses a managed peak impact of 0.9 kW/vehicle, not the 1.6 kW sensitivity cited. It references counterfactual calculations from the SGNS Project (M11621) and provides a table of 2023 unmanaged peak impact data. The response emphasizes managed charging impacts and methodology details.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to CA Information Requests NON-CONFIDENTIAL 1 Request IR-7: 2 3 Reference: Exhibit N-5, CA RIR-2(b), M11458; Exhibit N-9, NSUARB RIR-72(g), M11458. 4 Exhibit N-2, CA RIR-4, M11108; a...

AI summary NSPI confirms it does not track housing unit data by type or service level, outlines plans to use advanced metering infrastructure (AMI) for modeling, and explains considerations for EV charging and solar generation in distribution planning. Additional data is required before extrapolating SGNS project impacts.

requiring 23 transformers with long-lead times, such as padmount transformers, large commercial 24 customers are asked to provide notice of intent to connect one year in advance. Date Filed: June 19, 2024 NSPI (CA) IR-8 Page 3 of 3 2024 Lo...

AI summary NSPI is required to provide data on the impact of time-varying pricing (TVP) rates, AMI technology's role in reducing peak demand, and additional data needed for extrapolating pilot results in the 2024 Load Forecast Report.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to CA Information Requests NON-CONFIDENTIAL 1 Response IR-9: 2 3 (a) The peak reduction associated with TVP rates is provided in Figure 56 of the 2024 Load 4 Forecast report. 5 6 (b)...

AI summary NSPI responds to NSUARB's information requests regarding the 2024 Load Forecast Report, referencing peak reduction from TVP rates, AMI-related savings by 2028/2029, and a table analyzing TOU and CPP event occurrences. The response highlights forecasted peak savings and event data.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to SBA Information Requests NON-CONFIDENTIAL 1 Request IR-1: 2 3 Please provide workpapers, with formula intact, in Excel format, for all Figures/Charts 4 presented in the load forec...

AI summary NSPI responds to SBA's information requests regarding the 2024 Load Forecast Report, clarifying that SGNS project assets (other than EV charging and batteries) are not direct inputs to the forecast. Workpapers are referred to Synapse IR-01, and SGNS is described as a pilot project for grid control evaluation.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-14: 2 3 Introduction (Section 2.0, citing to Board Decision concerning 2023 Load Forecast). Please 4 explain in detail h...

AI summary NSPI responds to Synapse Information Requests regarding the 2024 Load Forecast Report, addressing the Board's direction to include the IRP, SGNS, AMI, and TVP outcomes; reviewing carbon emission reduction assumptions; and assessing historical load data compared to survey results. Citations are provided for each section in the report.

2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-33: 2 3 Peak Demand (Section 10 Coincident Peak Demand Research, pp 92-96) 4 5 (a) Please provide more details about the...

AI summary NSPI responded to Synapse's information requests regarding the 2024 Load Forecast Report, addressing topics such as the use of interval data, AMI coverage, loss levels on peak days, and the robustness of the load forecasting model. The response highlights differences in peak load modeling approaches and the impact of demand-side management.

1 interval data is gathered this class-level view will allow for analysis of the impact from 2 specific inputs (e.g. end uses, rates, other specific trends) to peak. 3 4 (b) The available AMI data by class as of June 7th , 2024, is set out...

AI summary The text discusses the analysis of AMI data by customer class as of June 7th, 2024, highlighting the percentage of customers with AMI and the uncertainties associated with AMI data, including coverage and outages. It also provides detailed data on total losses and loss percentages over a specific time period.

Date-time Total losses (MW) Loss percentage 2023-02-04 17:00 380.22 16.02 2023-02-04 18:00 376.64 15.53 2023-02-04 19:00 384.26 15.81 2023-02-04 20:00 372.60 15.64 2023-02-04 21:00 365.86 15.67 2023-02-04 22:00 358.41 15.85 2023-02-04 23:0...

AI summary The text provides data on total losses (in MW and GWh) and loss percentages across different times and months, highlighting uncertainties related to AMI and adjustments to hourly AMI loads. It also discusses peak residential forecasts with and without DSM, emphasizing the importance of comparing forecast methods.

r GenIndices Heating GenIndices Cooling GenIndices Others XHeat XCool XOther Feb 18 May 20 Jun 20 22-Oct 22-Sep Covid 23-May ARMA

AI summary The text presents a table with various indices related to heating, cooling, and other factors, along with dates and an ARMA model. The content appears to be technical data used for analysis, possibly related to energy generation or demand forecasting.

temperature setpoints, more heating load served by the heat 20 pumps).2 1 Exhibit N-1, 2024 Load Forecast Report, p. 34. 2 Exhibit N-1, 2024 Load Forecast Report, p. 34. Evidence of John D. Wilson  Matter No. M11689  July 11, 2024 Page 4...

AI summary John D. Wilson testifies that NS Power's adjustment to residential heating intensities is reasonable but recommends further investigation using AMI data to address uncertainties in weather adjustments, heating saturation assumptions, and new customer forecasts, which could impact electrification planning and distribution planning.

electric vehicle owners. Considering the impact of managed charging, which 7 further reduces the contribution to peak, a more reasonable forecast assumption is 0.45 8 kW/vehicle. 9 Q: What would be the impact of adjusting to your proposed...

AI summary NS Power estimates adjusting EV peak demand from 0.9 kW to 0.45 kW/vehicle would reduce 2033 peak demand by 120 MW (from 240 MW to 120 MW). This adjustment could be further reduced through managed charging programs. The correction would significantly impact resource planning, offsetting load forecast increases from removing peak savings attributed to the time-varying pricing pilot.

es. NS Power has also updated its transformer sizing charts 27 to account for increased load from heat pumps and EVs.29 28 Exhibit N-2, CA RIR-4. 29 Exhibit N-2, CA RIR-8(b). Evidence of John D. Wilson  Matter No. M11689  July 11, 2024 P...

AI summary NS Power's transformer sizing methods for EVs and heat pumps are criticized for overestimating demand and using inconsistent load factors compared to other domestic services. The testimony highlights a lack of consideration for solar systems under 100 kW in distribution planning.

Power’s commercial load forecast does not include an estimate of the number of new customers. 34 Exhibit N-6, Synapse RIR-5, Attachment 1. 35 Exhibit N-26, NSUARB Undertaking U-5. Evidence of John D. Wilson  Matter No. M11689  July 11, 2...

AI summary NS Power's load forecast excludes new customer growth and unmetered services, leading to discrepancies with distribution planning forecasts. The testimony highlights the need to align forecasts with electrification strategies and account for housing supply initiatives.

John D. Wilson  Grid Strategies, LLC Page 5 “Views on TVA EE Modeling Approach,” presentation with Natalie Mims to Tennessee Valley Authority’s Evaluating Energy Efficiency in Utility Resource Planning Meeting, February 10, 2015. “The Cle...

AI summary John D. Wilson of Grid Strategies, LLC has presented on energy efficiency modeling, renewable energy reliability, carbon markets, solar capacity value, power plant procurement, resource adequacy, and energy transitions at various conferences and forums between 2015 and 2024.

of renewable energy in Georgia Power’s 2016 integrated resource plan, including portfolio diversity, operational and implementation risk, analysis of project-specific costs and benefits (including location and technology considerations), a...

AI summary The text details testimony in Georgia Power's 2016 and 2019 integrated resource plans (IRP) and demand-side management (DSM) plans, focusing on renewable energy adequacy, plant retirements, and procurement processes. In Nova Scotia, testimony addressed the Smart Grid project's cost classification, decommissioning, and capital expenditure plans, including hydroelectric decommissioning considerations.

John D. Wilson  Grid Strategies, LLC Page 12 of utility replacement portfolio and membership in PJM. Definition of dispatchable electric generating capacity. Use of dispatch practices including full flexibility operating mode for renewabl...

AI summary John D. Wilson of Grid Strategies, LLC provides testimony in Nova Scotia UARB matters and Washington UTC dockets, addressing load forecasting methods, DSM adjustments, capital expenditure plans, and smart grid initiatives. Topics include electrification forecasts, resource adequacy, and reliability investments.

24.7 51% 2033 71.3 43.4 7.7 31.7 28.2 39.6 22.9 51% 2034 69.1 44.0 7.8 30.7 28.6 38.4 23.2 51% Source: Synapse from Figure 35 from 2024 Load Forecast Recommendations and Considerations We ask that NSPI explore the benefits of increasing DS...

AI summary The document references a 2024 load forecast and recommends NSPI increase DSM levels. It also outlines Board directives from Matter 11108, including implementing IRP, AMI, and reviewing carbon emission assumptions.

4 Load Forecast, Appendix B, page 8. 26 2024 Load Forecast, Appendix B, page 9. 27 2024 Load Forecast, Figure 41, Figure 41, 42. 28 2024 Load Forecast, page 34. 29 2024 Load Forecast, page 34. Synapse Energy Economics, Inc. Evidence Regard...

AI summary The text highlights discrepancies between NSPI's and E3's 2030 heat pump energy usage estimates (242 GWh vs. 74 GWh) due to differing assumptions about heating scenarios and saturation rates. It recommends validating assumptions about heat pump displacement of fossil-based heating and using AMI data for more accurate modeling.

d-use scenarios, NSPI should also evaluate the possibility of a higher than forecast peak in light of the systematic under-forecasting of peak that is noted above. Recommendations and Considerations For the major resources and end uses tha...

AI summary The document recommends that NSPI evaluate higher-than-forecast peak demand scenarios, develop multiple scenarios for uncertain resources like heat pumps and DSM, and conduct sensitivity analyses using new technologies. It also asks NSPI to explore increasing DSM levels and improve modeling of heat pump impacts on energy and peak load.

the transparency and accuracy of the load forecast. There is still more to do; but overall, NSPI’s Report is very well done and satisfactorily explains the underlying factors driving the forecast. Synapse Energy Economics, Inc. Evidence Re...

AI summary The document provides feedback on NSPI’s 2024 load forecast, highlighting the need for increased DSM levels, further investigation into heat pump impacts on energy and peak load, and the use of data from a water heater demand response pilot in future forecasts.

1 // 2 3 We support NSPI’s ongoing efforts to improve the transparency and accuracy of 4 the load forecast. There is still more to do; but overall, NSPI’s Report is very well 5 done and satisfactorily explains the underlying factors drivin...

AI summary The text supports NSPI's efforts to enhance load forecast transparency and accuracy, acknowledging progress but noting ongoing improvements needed. NS Power has adopted some intervenor recommendations but faces constraints in others. Integration of data from initiatives like Demand Response and Smart Grid Nova Scotia pilots is discussed, with AMI data integration expected to evolve over time as models adapt to granular data.

Page 6 of 25 2024 Load Forecast Report Rebuttal Evidence Non-Confidential 1 Synapse is also an active participant in the DSMAG and may raise the question of optimal DSM 2 investment with E1 as part of that forum. 3 4 2.1.2 Recommendation 2...

AI summary Synapse recommends NSPI investigate heat pump impacts on energy and peak load, validate assumptions about fossil fuel displacement, and model hybrid systems. NS Power agrees to evaluate heating components using AMI data and integrate hybrid scenarios into models. References to prior recommendations are noted.

, page 33. 28 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. 29 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. DATE FILED: September 6, 2024 Page 16 of 25 2024 Load Forecast Rep...

AI summary NS Power responds to Synapse's 2024 Load Forecast Report, acknowledging sensitivity analyses for peak load projections and referencing ongoing initiatives like SGNS, IRP, and TVP. The Consumer Advocate recommends refining residential heating intensity adjustments using AMI data for better accuracy.

al 29 heating intensities, including consideration of AMI data to gain a more granular 30 Synapse Evidence, 2024 Load Forecast Report (M11689), July 11, 2024, page 33. DATE FILED: September 6, 2024 Page 17 of 25 2024 Load Forecast Report R...

AI summary The text references Synapse's 2024 Load Forecast Report (M11689), highlighting the use of AMI data to analyze heating intensities for more granular insights. The report is cited in a rebuttal context related to load forecasting.

on previous occasions. In the Board decision letter in matter M11108, the Board provided NS Power with direction on enhancements for continuous improvement in the development of the load forecast and 1 Based on Table A1 in each annual repo...

AI summary The Board directed NS Power to improve load forecasting and stakeholder engagement, with specific recommendations including incorporating hydrogen production scenarios, IRP data, and evaluating model assumptions. NS Power conducted a virtual consultation with stakeholders and included materials in Appendix E of the Report.

al load with survey results; • Evaluate the elasticity used in the SAE model to the TVP Pilot EM&V elasticity; and, • Evaluate input variables in the residential model and test them over time. The Board stated in its 2023 decision, that NS...

AI summary The Board directed NS Power to continue monitoring commercial hydrogen production and integrate AMI data into load forecasts. NS Power evaluated model elasticity and used AMI data for accuracy, with the Board approving these approaches.

rgely the same but is now enhanced by AMI load factors. The Board considers the addition of AMI as an improvement to the model and directs NS Power to continue to add AMI data into the forecast model. NS Power applied E3’s scenario for hyb...

AI summary NS Power updated load forecasts using AMI data and hybrid electrification scenarios, aligning with its 2023 Electrification Strategy. The Board endorsed incorporating SGNS and TVP Pilot findings to enhance forecast accuracy. EV adoption estimates were revised to reflect Nova Scotia's lagging sales, with a low scenario adjusted for federal 2035 targets.

the demands from its residential customers. The Board directs NS Power to continue to revisit the unexplained variance and report on its findings in the 2025 Load Forecast Report. Intervenor Comments As in previous Load Forecast Reports, i...

AI summary The Board directs NS Power to investigate unexplained variance in residential load forecasts and report findings in the 2025 Load Forecast Report. Intervenors commend NS Power's efforts but urge continued improvement, while the Consumer Advocate recommends using AMI data, adjusting TVP peak reduction assumptions, and revising EV charging forecasts.

-5- load by 943 watts in winter 2022-23; therefore, reaching its target is unlikely. Second, Mr. Willson suggested that the EV charging forecast should use 0.45 kW/vehicle instead of 0.9 kW/vehicle. Mr. Wilson compared the 2024 Load Foreca...

AI summary The document discusses discrepancies in NS Power's load forecasts, including underestimation of EV charging demand and customer growth. Mr. Wilson highlights inconsistencies between load forecasts and distribution planning, urging alignment with electrification strategies. The SBA recommends incorporating smart grid data and electrification impacts, while Synapse notes areas for improving the load forecast model.

Forecast Report. Synapse Synapse noted NS Power’s continued improvement to the Load Forecast Report. However, Synapse also remarked on several aspects, suggesting revisions. These included: • modeling heat-pump-based hot water heating, exa...

AI summary Synapse recommends revisions to NS Power’s Load Forecast Report, emphasizing improved modeling of heat pumps, solar impacts, EV adoption, DSM adjustments, and peak forecasting methodology. Key areas include hybrid heating scenarios, electrification effects, and validating new home construction as a proxy for customer growth.

efault-source/irp/electrification-strategy-report-february-2-2024- engagement-session-material.pdf?sfvrsn=4d233583_1 -6- Rebuttal Evidence - NS Power NS Power addressed the concerns raised by the intervenors in its Rebuttal evidence. As a...

AI summary NS Power rebutted intervenor concerns by refusing to include pilot program data in forecasts until programs are comprehensive, committing to use AMI data for accuracy, and citing Bill 228's removal of EOne's joint DSM filing requirement. NS Power agreed to monitor EV adoption, solar generation, and hybrid heating models while shifting DSM planning responsibility to EOne.

Date Filed: May 29, 2024 Synapse (NSPI) Page 17 of 24 1 j. How did the 2022 Evergreen IRP estimate peak demand reductions. How many 2 customers and which end uses or technologies does the IRP assume for 3 estimating the peak load reduction...

AI summary The text contains a series of requests related to demand-side management (DSM) programs, peak demand research, and data analysis, including requests for reports, evaluations, and detailed explanations of figures and calculations.

Date Filed: May 29, 2024 CA (NS Power) Page 4 of 6 1 Request IR-7: 2 3 Reference: Exhibit N-5, CA RIR-2(b), M11458; Exhibit N-9, NSUARB RIR-72(g), M11458. 4 Exhibit N-2, CA RIR-4, M11108; and Exhibit N-1, 2024 Load Forecast Report, pp. 32-...

AI summary The document contains regulatory requests (IR-7 and IR-8) seeking clarification on NS Power's data gaps regarding housing units, AMI integration for forecasting, distribution planning for EV/solar growth, and data requirements for extrapolating SGNS Project results. References to exhibits, load forecasts, and transformer sizing charts are included.

dentifying the sources of 40 data for the relevant factors, including but not limited to the number of customers 41 connected, panel sizes, and special loads such as EVs. 42 Date Filed: May 29, 2024 CA (NS Power) Page 5 of 6 1 (d) Are tran...

AI summary The text outlines regulatory inquiries into NSP's data practices for transformer sizing, time-varying pricing (TVP) impact assessments, and AMI technology implementation timelines. Requests focus on quantifying TVP's system peak reduction, forecasting AMI benefits, and analyzing peak demand patterns from winter 2023-2024.

on previous occasions. In the Board decision letter in matter M11108, the Board provided NS Power with direction on enhancements for continuous improvement in the development of the load forecast and 1 Based on Table A1 in each annual repo...

AI summary The Board directed NS Power to improve load forecasting and stakeholder engagement, with recommendations including incorporating hydrogen production scenarios, IRP/SGNS/AMI data, and evaluating model assumptions. A stakeholder consultation was held with entities like EOne, SBA, and CA.

al load with survey results; • Evaluate the elasticity used in the SAE model to the TVP Pilot EM&V elasticity; and, • Evaluate input variables in the residential model and test them over time. The Board stated in its 2023 decision, that NS...

AI summary The Board approves NS Power's approach to monitor commercial hydrogen production and continues using AMI data for improved load forecasting accuracy. Evaluations of elasticity and model variables are recommended, with the Board supporting enhanced forecasting methods.

rgely the same but is now enhanced by AMI load factors. The Board considers the addition of AMI as an improvement to the model and directs NS Power to continue to add AMI data into the forecast model. NS Power applied E3’s scenario for hyb...

AI summary The Board approves NS Power's updated load forecasting methods, including AMI data integration, hybrid electrification scenarios, and adjusted EV adoption estimates. These changes align with recent strategies and pilot program outcomes, enhancing forecast accuracy and robustness.

the demands from its residential customers. The Board directs NS Power to continue to revisit the unexplained variance and report on its findings in the 2025 Load Forecast Report. Intervenor Comments As in previous Load Forecast Reports, i...

AI summary The Board directs NS Power to investigate unexplained variance in the 2024 Load Forecast Report and report findings in 2025. The Consumer Advocate (CA) recommends using AMI data and SAE model improvements, adjusting EV charging forecasts, and revising TVP peak reduction benefits based on underperformance.

efault-source/irp/electrification-strategy-report-february-2-2024- engagement-session-material.pdf?sfvrsn=4d233583_1 -6- Rebuttal Evidence - NS Power NS Power addressed the concerns raised by the intervenors in its Rebuttal evidence. As a...

AI summary NS Power rebutted intervenors' concerns by refusing to include pilot program data in forecasts until programs are comprehensive, committing to use AMI data for accuracy, and citing Bill 228's removal of DSM joint-filing requirements. It agreed to monitor factors like temperature trends, heat pump impacts, and EV adoption while shifting DSM responsibility to EOne.

NS Power agreed to monitor several of the model’s inputs, including EV adoption, solar generation, battery storage deployment and bi-directional EV charging, and the associated load impacts for each. NS Power agreed to review pricing innov...

AI summary NS Power agreed to monitor EV adoption, solar generation, and load impacts but disagreed with the CA's recommendation to remove TVP benefits from peak forecasts. It contested EV peak value assumptions and weather factor inclusions, though it agreed to analyze temperature and cloud cover trends.