N-7NSPI (Synapse) RIR-1 to RIR-46 - Redacted
26 passages
2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests CONFIDENTIAL (Attachment Only) 1 Request IR-9: 2 3 Residential Electric Vehicles (EV) (Section 4.4, pp 38-43) 4 5 (a) Please provide...
AI summary The document outlines information requests from the NSUARB to NSPI regarding the 2023 Load Forecast Report, focusing on residential electric vehicle (EV) sales forecasts, load shaping tools, time of use tariffs, and EV load management assumptions. The requests aim to clarify data sources, methodologies, and assumptions used in the forecasting process.
ario. In a managed charging scenario, drivers can shift the 22 timing of their charging at a given location to minimize costs of charging based on time- 23 varying electric rates. Date Filed: June 20, 2023 NSPI (Synapse) IR-9 Page 4 of 5 R...
AI summary The text discusses a managed charging scenario where drivers can adjust their charging timing to minimize costs based on time-varying electric rates. It is part of a 2023 Load Forecast Report and NSPI's responses to Synapse Energy Economics Information Requests.
2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests CONFIDENTIAL (Attachment Only) 1 A third charge management type, charge management with Vehicle-Grid Integration 2 (VGI), still featu...
AI summary The document discusses charge management strategies for EV owners, including Vehicle-Grid Integration (VGI) and the use of aggregators to reduce peak demand. It outlines assumptions about EV customer responsiveness to time-of-use (TOU) rates and the expected impact on load forecasting.
trics, details regarding business case development, general updates on broader data and learnings, EfficiencyOne’s role and corresponding outcomes regarding demand response programs. The Board acknowledges that information such as that not...
AI summary The Board requires detailed project reports, including financial breakdowns and program implementation status, for the Smart Grid Nova Scotia Project. Reports must include expenditures categorized as presented in the application and allocations against funding partner contributions.
two semi-annual reports, with the 23:00 peak occurring during the weekdays and not during the weekends. Figure 8 – Average Baseline EV Consumption for Each Hour of the Day on Each Day of the Week The 23:00 charging trend does not appear on...
AI summary The document discusses patterns in EV charging behavior, noting a 23:00 peak on weekdays but not on weekends, possibly due to differences in rate arbitrage and charging behavior influenced by time-of-use rates and app defaults.
patch through pool dispatch or manual events, based on day ahead generation planning, marginal cost-based forecast. ESP constraints maintain one charge/discharge cycle per day. No results to report. Page 40 of 48 . . REDACTED (CONFIDENTIAL...
AI summary The document discusses battery dispatch through pool dispatch or manual events based on intra-day generation planning and system loading. It also outlines modified time-varying curtailment during specific hours, initially executed manually and later aligned with NS Power's time-of-day rate for automatic execution.
availability. This will be followed by alignment to NS Power’s time-of-day rate (i.e. rate 06B) for automatic execution of curtailment events during on-peak hours through ESP. No results to report. S V / P W4 – INTERMITTENT RENEWAB LE GENE...
AI summary The text discusses use cases for managing renewable energy and grid stability, including aligning with time-of-day rates, following intermittent renewable generation, and providing generation contingency support through residential battery dispatch. These initiatives aim to optimize energy consumption and support grid reliability.
Project Scenarios for Comparison Measuring Outcomes ESP Processes Applicable to Value Reduced Upward Pressure on Revenue Baseline Scenario Baseline Scenario 2 Test Scenario Customer Benefit DER Class DER Group Value Streams DER Control Var...
AI summary The text outlines project scenarios for comparing outcomes related to DER (Distributed Energy Resources) control variables, value streams, and their impact on system reliability, grid stability, and customer benefits. It mentions different control strategies such as no utility influence, device-level control, and direct utility control.
Avoided Generation & Demand Reduction) • Intra-day generation planning • Net customer load (kW) • Day-ahead generation planning actions (e.g. decreased • BMS monitoring signal latency (seconds) • Value of load curtailed ($/kW, compared wit...
AI summary The text outlines metrics and considerations related to generation planning, including intra-day and day-ahead planning, net customer load, system load, and the value of curtailed load. It also references BMS (Building Management System) monitoring and control signal latency, as well as capacity and pilot programs.
2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 Request IR-19: 2 3 End-Use Intensity Trends (Section 4.4) 4 5 (a) The report references critical peak pricing (CPP...
AI summary NSPI responds to Synapse Energy Economics' request regarding the impact of critical peak pricing (CPP) and time-of-use (TOU) rates on EV charging behavior and load forecasts. NSPI assumes 70% of EV charging will be managed through TOU rates and direct control. NSPI plans to file a recommendation on CPP and TOU deployment as part of matter M09777 by June 30, 2023. The load forecast assumes TVP rates will help meet peak savings goals.
rn to 100 percent third party supply. Date Filed: June 20, 2023 NSPI (Synapse) IR-27 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information R...
AI summary NSPI provides responses to Synapse Energy Economics' information requests regarding system losses and unbilled sales, including historical data, seasonal variations, and assumptions about unmetered sales in the 2023 Load Forecast Report.
end-use to use as inputs into the model. Navigant based the segmentation on the examination of NS Power’s rate schedules and the customer segments established in the energy efficiency potential study. Figure 10-2 presents the different lev...
AI summary The text discusses the segmentation of customer data for demand response (DR) potential assessment, based on NS Power’s rate schedules and customer segments from an energy efficiency study. Dun & Bradstreet data is also used to break down BNI customers by business type.
Services » Market Rate • Electric Vehicles Source: Navigant Level 1: Sector Navigant segmented customers into residential and BNI sectors. Additionally, Electric vehicles (EVs) are considered in aggregate across all customer classes since...
AI summary Navigant segmented customers into residential and BNI sectors for the load forecast, considering electric vehicles across all classes. BNI customers were further divided into five categories based on demand values, with DR program offers varying by size. Residential customers and EV owners were not segmented further due to low demand variation.
nd values across residential customers is low. Electric vehicle owners also were not segmented further. Mapping between NS Power rate classes to those used in the DR study are provided in Figure 10-3. Figure 10-3. Mapping Between Nova Scot...
AI summary The document discusses the segmentation of residential and commercial customers for a demand response (DR) study, mapping Nova Scotia Power rate classes to DR customer classes and building types. This mapping helps in analyzing customer segments and their impact on demand response potential.
building type • Winter peak demand projections o By customer class, building type and end use 10.2.1 Customer Count Projections The steps to generate customer count projections include: • Separate out Interruptible Rider customers using BN...
AI summary The text outlines the process for generating customer count projections by separating interruptible rider customers, excluding certain account types, and disaggregating residential and municipal customers based on NS Power and NSP data. It also mentions peak period definitions and peak demand projections by customer class and building type.
ponse Potential Study for 2021-2045 Figure 10-6. Customer Count Forecast by Building Type Source: Navigant 10.2.2 Peak Period Definition and Peak Demand Projections A key element of market characterization for the DR potential study is to...
AI summary The document outlines the methodology for developing peak demand projections for the DR potential study, including defining the peak period, calculating coincident peak demand factors, obtaining end use shares, and calibrating results to align with demand distribution. It also includes steps for forecasting energy sales after DSM and developing separate peak demand projections for EVs.
s dispatching to the grid. Charging modulation to reduce EV EV Charging Control EV EV demand during peak periods A rate schedule with significantly higher Critical Peak Pricing peak prices to discourage consumption All classes Total Facili...
AI summary The text outlines methods to manage electric vehicle (EV) demand during peak periods, including EV charging control and critical peak pricing (CPP), as well as behavioral demand response (BDR) strategies to encourage peak shaving. It also references a study on energy efficiency and demand response potential in Nova Scotia from 2021 to 2045.
considered for all customer classes to shift facility load during peak demand periods. EV control includes reduction in EV load through charging interruptions during the peak demand period. CPP applies to all customer classes and impact ra...
AI summary The text discusses demand response mechanisms, including EV control and Critical Peak Pricing (CPP), which aim to shift load during peak demand periods. It also describes Automated Demand Response (Auto-DR) as a platform for automatic load reduction in response to signals from a Demand Response Automation Server (DRAS).
IR-30 Attachment 1 Page 105 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 small commercial and small industrial customers, and Auto-DR for the remaining customer classes). Industry experience sugges...
AI summary The document discusses demand response (DR) programs, including Critical Peak Pricing (CPP) and Behavioural Demand Response (BDR), and their assumptions for potential and cost-effectiveness. It highlights the need for smart meters and opt-in participation, with the start of CPP in 2022 following smart meter deployment.
-50% No change -15% Industrial, and Interruptible Source: Navigant analysis For CPP specifically, Navigant assumed that the CPP rate is offered as “default with opt-out” under the high scenario, while both base case and low scenario assume...
AI summary The analysis discusses the assumptions made regarding the Critical Peak Pricing (CPP) rate under different scenarios. Under the high scenario, CPP is offered as a default with opt-out, placing it at the top of the participation hierarchy, while lower scenarios assume an opt-in model. The high scenario also assumes lower unit impacts for CPP due to the default offer structure, supported by research from the Brattle Group. Low-income residential customers are excluded from CPP in all scenarios due to concerns about affordability.
gy Efficiency and Demand Response Potential Study for 2021-2045 Figure 11-5. DR Base Achievable Scenario Levelized Costs vs. 2045 Potential (MW at generator) Cumulative Achievable Cost-Effective Levelized Costs Cost-Effective DR Option Pot...
AI summary This section discusses the achievable potential results for cost-effective demand response (DR) options, including various DR strategies such as Critical Peak Pricing (CPP), Demand Load Control (DLC), and Behavioural DR, along with their corresponding levelized costs and potential contributions by 2045.
and cost- effectiveness results for each of the scenarios. 28 . Date Filed: August 14, 2019 Page 30 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 158 of 355 Nova Scotia Energy E...
AI summary The document outlines the steps in a demand response (DR) potential assessment, beginning with market characterization. The segmentation approach is based on Nova Scotia Power’s rate schedules and was agreed upon through discussions between E1 and Navigant, differing from the energy efficiency assessment method.
149 89 17 43 96 48 42 45 35 36 54 33 54 94 41 44 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 44 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 339 of 355 No...
AI summary The text includes a redacted section from a 2023 Load Forecast Report and an appendix from a Nova Scotia Energy Efficiency and Demand Response Potential Study. It references a 2019 Electricity Usage Survey for businesses and mentions rate codes from Nova Scotia Power bills.
135 82 15 38 86 44 36 42 32 30 49 31 50 83 36 45 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 45 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 340 of 355 No...
AI summary The text includes a redacted section from a 2023 Load Forecast Report and a 2019 Electricity Usage Survey for businesses in Nova Scotia. It references a rate code selection process, which is typically found on electricity bills.
2023 38.3% 15.5% 24.2% 4.9% 8.4% 5.8% 1.1% 1.7% 0.0 2032 52.2% 11.7% 13.8% 3.0% 6.1% 4.8% 0.8% 1.3% 0.1 Please note that all values are in MW. REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report (NSUARB M11108) NSPI Respo...
AI summary This document outlines a series of information requests related to the 2023 Load Forecast Report, focusing on peak demand, AMI coverage, data collection timelines, and the impact of DSM on residential load. The requests include details on interval data, loss levels, and the use of smart meter data in future forecasts.
REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-44 Attachment 1 Page 7 of 8 LDV Charging Profiles Charging profiles represent population-level charging scaled down to one vehicle In unmanaged charging,...
AI summary The document discusses LDV charging profiles, explaining the difference between unmanaged and managed charging. Unmanaged charging occurs immediately upon arrival, while managed charging shifts timing to reduce costs and flatten peak loads. E3's input assumes 70% of managed charging is coordinated by an aggregator. The second section introduces heating equipment stock rollover, though details are redacted.
N-8Evidence - Synapse
7 passages
ducing energy use, and to a lesser degree peak loads. Specific effects appear in Figures 38 and 55 of the Report. Overall, NSPI projects DSM will reduce the 2033 load by 586 GWh, or about 4.8 percent. Note however that the DSM Program savi...
AI summary NSPI projects DSM will reduce 2033 load by 586 GWh (4.8%) through energy use reduction and peak load management. Statistical adjustments (41% net savings) account for historical DSM program impacts to avoid double-counting. The analysis recommends increasing DSM levels to enhance energy growth mitigation.
, Figure 30, Figure 30. 30 2022 Load Forecast Report, Figure 28. 31 Load Forecast Report, Figure 30, Figure 3, Figure 65. 32 Load Forecast Report, Figure 42. 33 Load Forecast Report, Figure 68. Synapse Energy Economics, Inc. Evidence Regar...
AI summary The document highlights concerns about Nova Scotia Power’s (NSPI) 2023 load forecast, emphasizing the need to monitor EV adoption rates and adjust forecasts due to ambitious public goals and supply chain challenges. It stresses the importance of managing EV charging times to mitigate peak load impacts and suggests implementing rate designs and programmatic interventions, with NSPI’s SGNS project testing direct utility control for off-peak charging.
with a total load increase of 40 GWh by 2033. 55 This is a very small fraction of the total industrial load but the potential could be greater as some industries shift further away from fossil fuels. This forecast assumes the continuation...
AI summary The industrial load forecast projects a 2.7% increase by 2033, with DSM savings of 57 GWh and RTR resources at 38 GWh. Uncertainties include industrial electrification trends and operational changes. Recommendations urge NSPI to explore impacts of electrification, savings potential, real-time rates, and RTR growth.
Evidence Regarding Nova Scotia Power’s 2023 Load Forecast 27 7. QUESTIONS AND RECOMMENDATIONS In this Evidence we ask for further clarifications and make several recommendations: 1. We ask that NSPI explore the benefits of increasing DSM l...
AI summary The document requests clarifications and recommendations for Nova Scotia Power regarding its 2023 load forecast, including exploring increased DSM levels, analyzing heat pump impacts, leveraging water heater demand response data, and addressing EV adoption and load management strategies.
These load management strategies should be reflected in the next load forecast with greater detail, with all assumptions supported empirically to the maximum extent possible (page 14). 5. NSPI should include in its next load forecast more...
AI summary The document outlines several recommendations and questions regarding NSPI's load forecasting, including the need for more detailed and empirically supported assumptions, validation of proxy variables, and exploration of the impacts of EV load shifts, DSM programs, solar generation, RTR programs, and industrial electrification.
ctrification levels (page 21). 13. We ask NSPI to explore the potential for greater industrial savings (page 22). 14. We ask NSPI to explore the impacts of real time rates (page 23). 15. We ask NSPI to explore the impacts of increases in i...
AI summary The text outlines various requests for NSPI to explore and evaluate the impacts of industrial electrification, real-time rates, and technologies like heat pumps and thermal storage. It also recommends sensitivity analyses to mitigate peak load increases. The summary supports NSPI’s efforts to improve load forecast transparency and accuracy.
ch of the commercial and industrial demand savings presented in Figure 36 are contained in the industrial forecast. We ask NSPI to clarify the DSM effects for each sector (p.15). • We’d like further explanation from NSPI about why the comm...
AI summary The text requests NSPI to clarify and improve its load forecasting, particularly regarding demand-side management effects, peak load growth from electric vehicles, time-of-use rates, and the impact of technologies like electric thermal storage, water heating, and induction cooking on energy and peak loads.
N-9Direct Evidence of J. Wilson - CA
10 passages
Matter No. M11108 In the Matter of Nova Scotia Power’s 2023 Load Forecast Report EVIDENCE OF JOHN D. WILSON ON BEHALF OF THE CONSUMER ADVOCATE Grid Strategies, LLC JULY 18, 2023 TABLE OF CONTENTS I. Identification & Qualifications ...........
AI summary The document outlines the 2023 Load Forecast Report by Nova Scotia Power, critiqued by John D. Wilson on behalf of the Consumer Advocate. Key issues include forecasted peak demand for EV charging, time-varying pricing impacts, and documentation quality. Implications for distribution planning are highlighted.
fication & Qualifications 2 Q: Mr. Wilson, please state your name, occupation, and business address. 3 A: I am John D. Wilson. I am the Vice President of Grid Strategies, LLC, Bethesda, MD. 4 Q: Summarize your professional education and ex...
AI summary John D. Wilson, Vice President of Grid Strategies, LLC, discusses his background in energy policy, including regulatory research, utility rate design, cost-effectiveness analysis of energy projects, and experience with conservation programs and cost recovery mechanisms in utility efficiency initiatives.
ich load forecast 8 methods and documentation could be improved. Finally, I will discuss general implications 9 of the electrification load forecast for distribution system planning. 10 Q: Please summarize your recommendations. 11 A: I rec...
AI summary The witness recommends NS Power adopt a 0.6 kW/vehicle EV charging rate, remove time-varying pricing peak reduction benefits, update load forecast documentation, verify transformer sizing with updated EV data, and improve distribution planning for solar systems <100kW and heating electrification, particularly in small general sector areas.
fully relying on heat pumps to customers using some non-electric backup 9 system during peak periods would have a “large impact on the peak impact of heating 10 electrification.”7 11 Q: What are the implications of this finding for NS Powe...
AI summary NS Power faces challenges in meeting peak winter heating demand as part of its decarbonization strategy. Strategies include time-varying rates, battery storage, gas-fueled peaking units, and transmission interconnections. Customer-sited resources like natural gas and battery storage could reduce system peak demand by 257 MW, but pipeline capacity limits may hinder expansion.
st has been shifted one year later.12 NS Power expects time-varying 13 pricing tariffs to reduce demand by 4 MW in 2023, 12 MW in 2024, and by 32-36 MW in 14 2026 and thereafter.13 15 Q: Is this forecast reasonable? 16 A: No, not given the...
AI summary The respondent challenges NS Power's forecast of demand reductions from time-varying pricing, arguing the 2023 target of 4 MW is unreasonable given the pilot's low participation (795 watts reduction in 2021-2022). Scaling up to 12 MW in 2024 is deemed unlikely due to the pilot's October 2023 end date and delayed final report. Meaningful reductions are expected only from 2025.
tter No. M10109 (April 30, 2021), p. 74. 13 Exhibit N-1, 2023 Load Forecast Report, p. 78. 14 Exhibit N-1, Time Varying Pricing Interim Report, Matter No. M10703 (July 29, 2022), p. 10. Evidence of John D. Wilson Matter No. M11108 July...
AI summary The current time-varying pricing program is criticized for lacking design to achieve demand reduction, requiring further testing and delaying potential benefits until 2026 or later. This argument is presented in evidence related to regulatory proceedings.
5 Q: Why do you believe that the current time-varying pricing program will not 6 achieve any demand reduction? 7 A: The time-varying pricing program includes two pilot tariffs, a time-of-use tariff (TOU) and 8 a critical peak pricing tarif...
AI summary The current time-varying pricing program (TOU and CPP tariffs) fails to achieve demand reduction because peak hours are not fully covered by the tariffs, particularly on weekends and holidays. The interim evaluation shows that 90% of peak events occur outside the defined TOU periods, and CPP tariffs are also ineffective due to similar exclusions.
a critical peak event is in effect, due to this 26 fundamental flaw the CPP tariff cannot be relied upon to reduce the system peak. 27 Furthermore, the interim report showed disappointing results in terms of demand 28 reduction during morn...
AI summary The CPP tariff fails to reduce system peak during critical events, with disappointing demand reduction results, including higher peaks for electric-heat homes. Program changes like the CPP Advanced Tariff Pilot, including weekend/holiday flexibility, are proposed to address these issues.
10 In addition to the foregoing, NS Power commits to work with the parties to 11 develop and implement a pilot version of the CPP Advanced tariff offerings 12 proposed by Resource Insight, Inc. in Section VII of its February 24, 2021 13 ev...
AI summary NS Power committed to a CPP Advanced Tariff Pilot but unilaterally canceled it in winter 2022/2023 despite customer preference for alternatives, citing unsupported claims about pricing impacts. The text criticizes NS Power for failing to test the pilot and emphasizes the need for time-varying pricing programs with peak demand incentives to meet load reduction standards.
meet the standard for use in the load forecast report. 15 Consensus Agreement (May 12, 2022), Matter No. M09777, Attachment A, p. 3. 16 NS Power, CA RIR-2(c), Matter No. M09777. Evidence of John D. Wilson Matter No. M11108 July 18, 202...
AI summary The expert testifies that NS Power should exclude peak reduction benefits from time-varying pricing programs in its load forecast unless a new forecast is developed for programs effective on all peak days. The load forecast report is criticized for lacking documentation on key formulas and assumptions, with a recommendation to improve transparency in future reports.
N-9-(i)J. Wilson CV
10 passages
SELECTED PRESENTATIONS “Clean Energy Solutions for Western North Carolina,” presentation to Progress Energy Carolinas WNC Community Energy Advisory Council, February 7, 2008. “Energy Efficiency: Regulating Cost-Effectiveness,” Florida Publ...
AI summary The text lists presentations and testimonies on energy efficiency, renewable energy, and regulatory approaches by organizations like the Southern Alliance for Clean Energy (SACE) and individuals, focusing on regions such as Florida, the Tennessee Valley Authority (TVA), and Southeastern U.S. regulatory discussions. Topics include cost-effectiveness, utility-scale renewables, and energy efficiency programs.
ncy in Utility Resource Planning Meeting, February 10, 2015. “The Clean Power Plan Can Be Implemented While Maintaining Reliable Electric Service in the Southeast,” FERC Eastern Region Technical Conference on EPA’s Clean Power Plan Propose...
AI summary John D. Wilson from Grid Strategies, LLC presented on energy planning topics including renewable energy reliability, carbon market challenges, solar capacity value, procurement best practices, and resource adequacy. His work spans regulatory proceedings, market design, and technical analyses related to power generation and grid planning.
John D. Wilson Grid Strategies, LLC Page 8 California PUC Docket A.19-08-013, direct testimony in Southern California Edison’s 2021 general rate case (track 2) on behalf of the Small Business Utility Advocates. Reasonableness of remedial...
AI summary John D. Wilson of Grid Strategies, LLC provided testimony in multiple regulatory proceedings across California, Georgia, and Nova Scotia, focusing on utility rate design, cost recovery, compliance with regulatory orders, and modifications to pricing programs. Key issues included the reasonableness of fuel contract costs, capacity cost calculations, and adjustments to time-of-use pricing.
ervice in the event of an extreme weather event on behalf of the Small Business Utility Advocates. Modifications to Critical Peak Pricing programs and Time of Use periods. Modifications to load management programs. Nova Scotia UARB Matter...
AI summary The Nova Scotia Consumer Advocate provided testimony on modifications to Critical Peak Pricing (CPP) and Time of Use (TOU) programs, Time-Varying Pricing (TVP) tariffs, and capital expenditure plans. Arguments focused on the impact of TVP on load, capacity savings, and energy costs, recommending CPP tariffs instead. Matters included analysis of power contract delays, variable capital costs, and economic models for project evaluation.
avings, and energy costs. Recommended CPP tariffs. Treatment of demand charges in TVP tariffs. Implementation and evaluation of TVP tariffs. Lost revenue adjustment mechanism.
AI summary The text discusses recommended CPP tariffs, treatment of demand charges in TVP tariffs, implementation and evaluation of TVP tariffs, and the lost revenue adjustment mechanism. These topics relate to tariff design and revenue management in energy regulation.
John D. Wilson Grid Strategies, LLC Page 9 South Carolina PSC Docket Nos. 2019-224-E and 2019-225-E, surrebuttal testimony on 2020 Integrated Resource Plans filed by Duke Energy Carolinas and Duke Energy Progress. All-source procurement...
AI summary John D. Wilson and Paul Chernick provided testimony in multiple regulatory proceedings across South Carolina, California, and Nova Scotia, addressing integrated resource plans, net energy metering, real-time pricing, and hydroelectric project reasonableness. Testimonies focused on rate design, cost-of-service methods, and program evaluations.
ck Cove hydroelectric project on behalf of the Nova Scotia Consumer Advocate. Reasonableness of project and unresolved issues. California PUC Docket A.19-08-013, direct testimony in Southern California Edison’s 2021 general rate case (trac...
AI summary The text outlines legal proceedings involving the Nova Scotia Consumer Advocate in multiple regulatory cases, including assessments of project reasonableness, prudence of costs, and cost recovery. Cases span California PUC, Colorado PUC, and Nova Scotia UARB, with focus on hydroelectric projects, software remediation costs, and rate design.
with Paul Chernick in Liberty Utilities Calpeco 2022 general rate case on behalf of the Small Business Utility Advocates. Marginal cost study, revenue allocation, rate design.
AI summary Paul Chernick worked with Liberty Utilities Calpeco in the 2022 general rate case for Small Business Utility Advocates, focusing on marginal cost studies, revenue allocation, and rate design. The proceeding addresses key regulatory themes in utility pricing and cost distribution.
John D. Wilson Grid Strategies, LLC Page 10 Nova Scotia UARB Matter No. M10366, direct testimony on Nova Scotia Power’s Annual Capital Expenditure Plan for 2022 on behalf of the Nova Scotia Consumer Advocate. Alignment with IRP and new r...
AI summary John D. Wilson of Grid Strategies, LLC provided direct testimony on Nova Scotia Power's capital expenditure plans, rate applications, and programs, emphasizing alignment with the Integrated Resource Plan (IRP), cost minimization, and analysis of deferral accounts. Testimonies covered matters in Nova Scotia and Massachusetts, including seasonal rates, economic models, and distribution revenue allocation.
Nova Scotia Power’s 2023 Application for Annually Adjusted Rates on behalf of the Nova Scotia Consumer Advocate. Seasonal and time-varying rates. Impact of Maritime Link power delivery. Cost of service study updates. California PUC Docket...
AI summary Nova Scotia Power's 2023 rate applications, testimony on fuel adjustment mechanisms, biomass costs, and the Maritime Link project's impacts. Testimony addresses rate design, electrification effects, and regulatory recovery of customer benefits from infrastructure projects.
N-10Rebuttal Evidence - NSPI
10 passages
1 2.0 RESPONSE 2 3 The evidence from Synapse, and the CA, as well as the SBA’s submission are primarily focused 4 on the following issues: 5 6 1. Further details and investigation of the impact to energy and peak from expected 7 electrific...
AI summary The response highlights the need for further analysis of electrification's impact on energy and peak demand, as well as new technologies like smart grids and time-variable rates. NS Power agrees to investigate these issues using data from initiatives like the Integrated Resource Plan (IRP) and Smart Grid Nova Scotia (SGNS), while emphasizing the role of peak mitigation measures.
9 curtailment as outlined in NS Power’s 2020 IRP, and an assumed reduction in peak related to 30 managed EV charging. Several projects are in progress to evaluate the impact of new technologies, DATE FILED: September 14, 2023 Page 7 of 25...
AI summary The 2023 Load Forecast Report discusses ongoing projects like SGNS and water heater control, technologies such as battery storage and heat pumps, and the impact of rate design on energy consumption. Intervenors requested inclusion of project data in forecasts, while heat pump displacement of heating sources and rate design effects are highlighted as key areas for future analysis.
etting peak demand increases in future years. The current TVP pilot will be concluding in 18 2024, and lessons learned from that pilot will be used to forecast future impacts from rate design. 19 DATE FILED: September 14, 2023 Page 8 of 25...
AI summary The 2023 Load Forecast Report discusses the conclusion of the TVP pilot in 2024 and its implications for future rate design. Lessons from the pilot will inform forecasting methods related to rate design impacts.
vice customers? Are they 28 implementing DSM measures to reduce load? Adding solar generation? Entering 29 into RTR contracts? Might all this reduce their loads to some degree? 30 DATE FILED: September 14, 2023 Page 13 of 25 2023 Load Fore...
AI summary NS Power addresses questions about customer load reduction efforts, including DSM measures, solar adoption, and RTR contracts, stating impacts on large general class customers are minimal. They reference IRP scenarios for electrification and savings impacts in the 2023 Load Forecast Report.
. 23 24 3.1.13 Recommendations 14-15: 25 26 We ask NSPI to explore the impacts of real time rates. 27 28 We ask NSPI to explore the impacts of increases in industrial RTR. 29 30 DATE FILED: September 14, 2023 Page 14 of 25 2023 Load Foreca...
AI summary The document outlines recommendations for NSPI to explore real-time rates, industrial RTR increases, and post-2026 electrification prospects. NS Power responds that real-time pricing is available to industrial customers but limited in use, with potential future expansion. DSM adjustment factors are referenced in Section 4.6, and electrification discussions are deferred to prior responses.
d be adjusted upward to reflect greater levels of incremental 24 savings. 25 26 NS Power Response: 27 28 This recommendation is discussed in Section 4.6 of the Load Forecast Report. 29 DATE FILED: September 14, 2023 Page 15 of 25 2023 Load...
AI summary The NS Power responds to recommendations regarding load forecasting, clarifying that system peak calculations account for interruptible customers and demand response (DR) impacts. It notes that time-varying pricing and AMI-enabled strategies are already factored into peak forecasts, with updates pending Smart Grid and pilot data. Heat pump performance during peak conditions is under investigation.
2 3.1.20 Recommendation 22: 23 24 We ask NSPI to quantify specifically the electrification and EV impacts for the 25 commercial sector and to consider how this can be moderated. 26 27 NS Power Response: 28 29 As outlined in the response to...
AI summary The document outlines regulatory recommendations and NS Power's responses. Recommendation 22 requests quantification of commercial electrification and EV impacts, which NS Power claims is already addressed using E3's work. Recommendation 23 calls for sensitivity analyses on peak mitigation technologies, which NS Power agrees to incorporate alongside existing measures like managed EV charging and time-variable pricing. The Consumer Advocate recommends using a 0.6 kW/vehicle EV charging estimate.
19 The CA’s evidence provides the following recommendations: 10 20 21 3.2.1 Recommendation 1: 22 23 NS Power should use an estimate of 0.6 kW/vehicle for its EV charging forecast. 24 25 NS Power Response: 26 27 NS Power disagrees with this...
AI summary The Consumer Advocate (CA) recommends NS Power use a 0.6 kW/vehicle EV charging estimate, but NS Power disagrees, citing variability in their data. NS Power argues the CA's average understates peak load variability and requires more analysis. The CA also recommends removing time-varying pricing's peak reduction benefits from forecasts, though NS Power has not directly responded to this second recommendation.
EV peak 9 impact. 10 11 3.2.2 Recommendation 2: 12 13 NS Power should remove the peak reduction benefits associated with time-varying 14 pricing from its load forecast. 15 16 NS Power Response: 17 18 NS Power agrees that the forecast TVP p...
AI summary NS Power acknowledges overstated TVP peak savings in 2023-2024 but disputes removing them from load forecasts, citing minimal impact. The CA argues pilot programs lack coverage of all peak periods, while NS Power suggests flexibility in CPP events could improve alignment. NS Power will revise 2024 forecasts based on updated uptake estimates.
rates. 19 20 3.2.3 Recommendation 3: 21 22 NS Power should update its load forecast documentation to include the additional 23 details supplied in response to CA IR-10. 24 25 NS Power Response: 26 27 NS Power agrees with this recommendatio...
AI summary The Board recommends NS Power update its load forecast documentation with details from CA IR-10, specifically HeatUse, CoolUse, and OtherUse variables. NS Power agrees and will include these in the 2024 Load Forecast Report. A cross-reference to M09777, the Time Varying Pricing Pilot Program report, is cited.