Topic:"Energy Efficiency" in M10569

Page 13 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 • A discussion of the economic inputs to the residential model is provided in Section 2 4.3. 3 4 Summary of Stakeholder Consultations 5 6 On Apr...

AI summary NS Power conducted a stakeholder session on April 13, 2022, discussing updates to the 2022 Load Forecast, including impacts of COVID-19, EV forecasts, space heating, peak savings assumptions, and methodology from Energy and Environmental Economics, Inc. Stakeholders included NSUARB, Synapse, EfficiencyOne, and others.

1 4.4 End-Use Intensity Trends 2 3 In addition to economic data, the SAE model also uses end-use data, in the form of 4 saturations and efficiencies, from NRCan and the US Energy Information Agency (EIA). 5 NRCan data for the residential s...

AI summary The SAE model uses end-use data from NRCan and the EIA to develop end-use intensity trends, adjusting for consistency with actual billing data. Heat pump usage is growing due to its efficiency and environmental benefits.

27 Heat pump usage continues to grow in the province as more customers find heat pumps an 28 efficient way to heat and cool buildings as well as providing environmental and financial 29 benefits. According to the 2019 end use survey, 33 pe...

AI summary Heat pump usage is increasing in Nova Scotia, with 33% of customers using them for heating and 36% for cooling. The 2022 Load Forecast Report indicates that heat pump saturation is expected to reach 66% of homes by 2032 to meet carbon reduction targets. Commercial adoption follows a similar trajectory but will not reach 100% by 2050.

ions and changes to saturation and 17 intensity over the forecast period. Work is underway to collect more detailed data on the 18 contribution of heat pumps to load and peak.11 19 11 NS Power Annual and Regulated Financial Statements – On...

AI summary The document discusses ongoing work to collect more detailed data on the contribution of heat pumps to load and peak demand, with a reference to a study update submitted by NS Power to the UARB in January 2022.

2,204 81 324 3 4 DATE: April 29, 2022 Page 40 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 Water Heaters 2 3 NS Power anticipates that some customers who convert their oil heating systems to heat 4...

AI summary NS Power expects increased adoption of electric water heaters due to conversions from oil heating systems to heat pumps. The 2019 survey indicates 63% of respondents use electricity for water heating, with saturation expected to rise to 82% by 2032. A pilot project with E1 is exploring benefits of direct control of water heaters.

benefits to the system (see Section 10). Figure 25 shows the expected changes in 11 saturation and overall intensity over the forecast period. 12 13 Figure 25: Water Heater Forecast 14 Overall % Overall Intensity Year Saturation (kWh/house...

AI summary The text discusses the forecasted changes in water heater saturation and intensity over the forecast period, as well as the existing federal and provincial incentives for electric vehicles (EVs) in 2022. It provides data on saturation percentages and overall intensity in kWh per household from 2022 to 2032.

Peak @ Peak @ Load Year EVs 0.9kW/vehicle 1.3kW/vehicle (GWh) (MW) (MW) 2022 2,864 12 2 4 2023 5,978 26 5 8 2024 10,258 48 9 14 2025 15,680 76 14 21 2026 22,232 110 20 30 2027 29,908 153 27 40 2028 38,671 204 35 52 2029 48,465 259 45 66 20...

AI summary The text provides a forecast of peak load and electric vehicle (EV) growth from 2022 to 2032, along with information on solar generation in Nova Scotia. It highlights the discrepancy between forecasted and actual solar installations and their impact on residential load reduction.

oject. 19 These are illustrative estimates based on limited data sets and will be refined as the project 20 continues. 21 22 Figure 30: Potential Peak Impacts from Batteries 23 Residential Share (%) Technology 50% 25% 10% 5% Battery Peak I...

AI summary The document provides illustrative estimates of potential peak impacts from battery technologies under different control scenarios, including no control and optimal demand response control, as part of the 2022 Load Forecast Report.

ell as smaller appliances such as computers, dehumidifiers, 28 microwaves, etc. This category also includes solar generation (photovoltaic or PV) 29 and EV forecasts. 30 DATE: April 29, 2022 Page 49 of 98 REDACTED (CONFIDENTIAL INFORMATION...

AI summary The document discusses residential and commercial end-use intensities, including trends in heating, cooling, and appliance usage. It highlights the increasing use of heat pumps and the impact on energy demand, as well as the slow decline in lighting and refrigeration due to improved efficiency. Supporting data is referenced in an attachment.

2022 Load Forecast Report REDACTED 1 Figure 33: Historical and Projected General Commercial End-Use Intensity 2 (kWh/m2) 3 4 5 Supporting data for General commercial end-use intensities is included in Attachment 3. 6 7 For the 2022 Load Fo...

AI summary The 2022 Load Forecast Report discusses historical and projected general commercial end-use intensity, noting increased heat pump penetration. It highlights growth in the commercial and industrial sectors due to electrification programs aimed at reducing emissions and energy usage.

Page 56 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED

AI summary The 2022 Load Forecast Report provides an analysis of projected electricity demand, including factors such as heating and cooling degree days, and includes redacted confidential information.

Page 59 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 forecast is that there will be a certain amount of continued work-from-home load, likely 2 through hybrid work models. 3 4 Apart from the shift...

AI summary The 2022 Load Forecast Report discusses the impact of increased work-from-home trends, higher EV penetration, and electric space heating on long-term load forecasts. These factors are expected to influence load patterns starting around 2025, with new customer growth offsetting some efficiency gains and solar generation.

RMATION REMOVED) 2022 Load Forecast Report REDACTED 1 Figure 41: Illustrative Contribution of Specific End Uses 2 Year HP Heat HP Cool Baseboard Heat Water Heat (GWh) (GWh) (GWh) (GWh) 2022 607 74 1096 710 2023 656 81 1059 725 2024 705 87...

AI summary The 2022 Load Forecast Report provides an illustrative breakdown of energy consumption by specific end uses, including heat pump heating and cooling, baseboard heating, and water heating, across the years 2022 to 2032. The data shows projected trends in energy usage for these categories over time.

ith energy exports are not included. Figure 51 provides a breakdown of the 7 significant variances between forecast and actuals for 2021. 8 9 Figure 51: 2021 Variance to Actual 10 Res Comm Ind Other Losses NSR 2021 Forecast 4,718 3,070 2,4...

AI summary The document discusses the 2021 variance between forecast and actual energy usage, noting significant differences driven by weather impacts and unexplained variances, particularly in residential and commercial classes due to ongoing effects of COVID-19. It also forecasts an annual increase in NSR from 2022 to 2032, driven by new customers, space heating, and EV adoption, with solar and DSM offsetting some sales.

Year Direct Critical Business, Total Total Load Peak Non-Profit (MW) with Control Pricing & Industrial ELCC (MW) (MW) Curtailment (MW) (MW) 2022 0 1 0 1 0 2023 4 4 1 9 4 2024 12 12 2 26 12 2025 24 22 4 50 24 2026 36 32 6 74 36 2027 39 36 7...

AI summary The text presents a table showing the implementation of Direct Load Control (DLC) and Critical Peak Pricing (DR) programs across various years, highlighting the growth in capacity and participation. A pilot project with E1 is underway to test water heater controls, with early results indicating potential peak savings.

2022 Load Forecast Report REDACTED 1 Figure 65: Monthly historical Residential LRS load at peak and forecasts 2 3 4 5 Both the current residential peak demand forecast (green line) and the LRS peak 6 experimental model (black line) are des...

AI summary The 2022 Load Forecast Report discusses residential peak demand forecasts and experimental models, noting improvements in summer cooling load resolution due to factors like heat pump proliferation and remote work. It highlights differences between top-down and bottom-up forecasting approaches, with discrepancies ranging up to 200 MW.

Residential Commercial Industrial Total Year Sector Growth Sector Growth Sector Growth Municipal Growth Losses Energy Growth GWh % GWh % GWh % GWh % GWh GWh % 2012 4,160 -2.7 3,196 -0.6 2,164 -38.4 191 0.0 763 10,475 -12.0 2013 4,362 4.8 3...

AI summary The text presents energy usage data across residential, commercial, industrial, and municipal sectors from 2012 to 2023, showing varying growth rates and energy consumption trends over time. The data includes total energy growth and losses for each year, highlighting fluctuations in energy demand and efficiency.

t Appendix B Page 5 of 32 Appendix B – Forecast Model Details Residential SAE Model Fit Residential Model 2022-2032 Reconciliation The following tables provide details reflecting the changes between 2022 and 2032 forecast years. Some of th...

AI summary The document provides a reconciliation of residential load forecasts between 2022 and 2032, showing changes in customer load, EV load, solar load, and DSM captured. It includes a table with data on existing and new customer usage, energy efficiency savings, and load adjustments.

es trends over time. Binary variables were added similar to those used in the underlying commercial and industrial models. Variable Coefficient StdErr T-Stat P-Value MSales.EESavingsProfiled -0.380 0.121 -3.153 0.21% MStructGen.WtXCool 0.5...

AI summary The text presents statistical results from a load forecasting model, including coefficients and significance levels for various variables related to energy efficiency savings, structural generation weights, and seasonal binaries. The EESavings variable is highlighted as representing the amount of demand-side management needed to explain historical sales trends.

Appendix D – Forecast Sensitivity Analysis Figure D4: Peak Forecast (Residential, Commercial and Small and Medium Industrial) The asymmetry in this figure, seen as the off-centre median, is explained by the bias introduced by plotting the...

AI summary The document discusses the asymmetry in peak forecast data, attributing it to the use of the MAX function in selecting the highest monthly Peak HDD. It notes that the Monthly HDD has become more influential than Peak HDD in 2022 due to year-round residential heating impacts, leading to a steeper peak demand curve influenced by E3 electrification scenarios.

022 Load Forecast Report Appendix D Page 7 of 9 Appendix D – Forecast Sensitivity Analysis Figure D5: Relative Sensitivity of Peak In terms of the sensitivity of the energy sales forecast to the various input variables, Figures D6 and D7 s...

AI summary The document discusses the sensitivity of energy sales forecasts to various input variables, noting that weather has the strongest impact in the near term while economics becomes dominant in the long term. Demand-side management (DSM) and other factors significantly outweigh the impact of economic, weather, or end-use changes.

REMOVED) REDACTED 2022 Load Forecast Report Appendix D Page 9 of 9 Appendix D – Forecast Sensitivity Analysis Figure D8: Relative Impact of Inputs 2023 Energy 2023 Peak 2032 Energy 2032 Peak Item (GWh (MW) (GWh) (MW) Included in Forecast D...

AI summary The document presents a sensitivity analysis from the 2022 Load Forecast Report, highlighting the impact of various factors such as demand-side management (DSM), solar PV, electric vehicles (EV), and battery storage on energy and peak load forecasts for 2023 and 2032. It includes different scenarios for EV adoption and the effects of weather and economic factors.

2022 Load Forecast Report Appendix E Page 1 of 8 Nova Scotia Power Electrification Support Load Forecast Inputs – Overview April 2022 Liz Mettetal, PhD Sierra Spencer Michaela Levine Arne Olson Dan Aas REDACTED (CONFIDENTIAL INFORMATION RE...

AI summary This document is part of the 2022 Load Forecast Report Appendix E, prepared by Nova Scotia Power with contributions from E3, a consulting firm specializing in engineering, economics, and public policy. The report provides input for load forecasting related to electrification support.

matics, Public Policy… San Francisco New York Boston Calgary E3 Clients Recent Related Projects • Nova Scotia Power Integrated Resource Planning Support & 300+ ongoing Electrification Strategy Report projects • Transportation Electrificati...

AI summary Electrification is identified as a key strategy for achieving Net-Zero in Nova Scotia, with near-complete electrification of transportation and most buildings being a 'safe bet' due to lower costs and commercial availability of supporting measures.

r-complete electrification of transportation and most buildings is a “safe bet” • Measures are lower cost and commercially available to support economy-wide decarbonization  Electrification must be pursued in parallel to aggressive power...

AI summary The document discusses the electrification of transportation and buildings as a cost-effective strategy for decarbonization, supported by the PATHWAYS model. It also outlines the forecast for electric vehicle (EV) adoption, assuming 100% electric LDV sales by 2035 and a slow ramp-up to 30% by 2030.

2022 Load Forecast Report Appendix E Page 8 of 8 Heating Equipment Stock Rollover  E3’s electrification study scenarios ultimately yield near-complete electrification of residential and commercial buildings by 2050; to achieve policy targ...

AI summary The 2022 Load Forecast Report Appendix E discusses E3’s electrification study scenarios, which predict near-complete electrification of residential and commercial buildings by 2050, driven largely by heat pump adoption in the 2030s. The analysis assumes rapid growth in heat pump usage, tempered by stock rollover, and notes alignment with NSP forecasts despite data limitations.

d Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-1: 2 3 Reference Report p. 7: “As with any forecast, there is a degree of uncertainty arou...

AI summary The Consumer Advocate has requested clarification on the demand forecast report, specifically regarding uncertainty analysis and the inclusion of a general warming trend. NS Power confirms that only weather and economic uncertainties were considered in their scenario analysis and explains that the warming trend was not included in the analysis or figure provided.

232.686 -97.305 177.016 43.995 Summary Feb 2021 heating load 344558 MWh Normal heating load 367348 MWh 2021 Varinace to Normal -22790 MWh

AI summary In February 2021, the heating load was 344,558 MWh, which is 22,790 MWh less than the normal heating load of 367,348 MWh, indicating a significant deviation from typical usage patterns.

1 Request IR-2: 2 3 (a) Please describe all electrification research/pilots/programs NS Power is currently 4 planning and/or carrying out. 5 6 (b) Please provide all applicable project schedules, studies and/or reports that have been 7 dev...

AI summary NS Power outlines electrification initiatives, including residential heating solutions with heat pumps and commercial HVAC electrification programs. The response highlights contractor networks, on-bill financing, and a four-year Smart Grid Nova Scotia pilot (M10176) focused on advanced metering infrastructure and building decarbonization studies.

NSPI (E1) IR-4 Page 2 of 2 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to EfficiencyOne Information Requests NON-CONFIDENTIAL 1 Request IR-5: 2 3 Reference: NS Power 2022 Load Forecast, p...

AI summary NSPI responds to IR-5 by asserting heat pumps are the primary electrification technology due to efficiency, with the model focused on emission reduction targets rather than economic factors. Other heating technologies are excluded due to lower efficiency.

Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to EfficiencyOne Information Requests NON-CONFIDENTIAL 1 Request IR-9: 2 3 Reference: NS Power 2022 Load Forecast, page 39, lines 4-14. 4 5 “The capacity of heat pu...

AI summary NSPI responds to EfficiencyOne's queries about heat pump performance modeling in the 2022 Load Forecast, including low-temperature COP behavior, backup heating assumptions, and RESHAPE analysis coincidence factors. The discussion focuses on technical modeling assumptions for heat pump efficiency and backup systems.

15 16 (e) Yes, NS Power views Electric Thermal Storage (ETS) as an effective backup for Air-Source 17 Heat Pump systems when ETS is sized appropriately to carry the heating load. 18 Date Filed: July 8, 2022 NSPI (E1) IR-9 Page 3 of 4 10 -...

AI summary NSPI confirms Electric Thermal Storage (ETS) can effectively back up air-source heat pumps when appropriately sized. However, it expresses uncertainty about hybrid systems combining heat pumps with fossil fuels in meeting 2050 Net Zero targets. The forecast assumes consistent weather and does not model unaccounted factors, deeming their 10-year impact unlikely.

Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to EfficiencyOne Information Requests NON-CONFIDENTIAL 1 Request IR-10: 2 3 Reference: NS Power 2022 Load Forecast, page 43, lines 12-13 4 5 “The peak impact assume...

AI summary NSPI responds to EfficiencyOne's questions about EV charging management, acknowledging demand response programs and CPP rate structures as potential tools. NSPI emphasizes the need for detailed program specifics and studies on rate impacts, while addressing concerns about double-counting capacity savings from overlapping initiatives.

and Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to EfficiencyOne Information Requests NON-CONFIDENTIAL 1 Request IR-12: 2 3 Reference: NS Power 2022 Load Forecast, Appendix E, page 3 of 8. 4 5 “Measures are lower co...

AI summary NSPI references the Canadian Climate Institute's 2021 report in response to EfficiencyOne's request about electrification and decarbonization measures. The report highlights technologies like building and transportation electrification as common to all net-zero pathways, emphasizing their role alongside energy efficiency.

vel 2 chargers 90% efficient, and DC Fast Chargers 29 are 85% efficient consistent with CEC Plug-In Electric Vehicle Infrastructure 30 Projections: 2017-2025. Date Filed: July 8, 2022 NSPI (NSUARB) IR-2 Page 4 of 6 10 - Year Energy and Dem...

AI summary The document references electric vehicle charger efficiency rates (90% for Level 2, 85% for DC Fast Chargers) aligned with CEC projections, and includes a 10-year energy demand forecast from NSPI's 2022 Load Forecast Report (NSUARB M10569).

1 11. Tariffs: 2 a. E3 assumes a mix of flat rate (residential and small commercial) and Time-of- 3 Day Rate Pilot Program pricing (TOU residential and small commercial TOU 4 pricing) 5 b. E3 assumes 100% access to public chargers, 77% acc...

AI summary The text outlines E3's assumptions about tariff structures, EV charging access rates, and Dunsky's modeling approach for forecasting EV adoption in Nova Scotia. Key elements include flat and time-of-day rate structures, EV charging cost assumptions, and a three-step modeling approach involving market segmentation, calibration, and input assumptions.

1 Request IR-10: 2 3 With reference to Section 4.4 End-Use Intensity Trends, page 38 of 98, the application states 4 “the peak impact predicted by E3 using building stock modelling produces a higher peak 5 impact than the existing SAE peak...

AI summary The response explains that NS Power adjusted its SAE model to incorporate E3's more detailed building-level heat pump modeling, which accounts for reduced efficiency at peak temperatures and backup heat contributions. While energy differences were minimal, peak differences were larger, but NS Power did not adjust the forecast for heat pump sales.

1 Request IR-12: 2 3 With reference to Figure 24: Heat Pump Forecast, page 40 of 98, the Overall Heating 4 Intensity (kWh/house) and Overall Cooling Intensity (kWh/house) are forecast to increase 5 over time. Please explain why NS Power ex...

AI summary The request asks NS Power to explain why the Overall Heating and Cooling Intensities are forecast to increase over time and to provide actual data from 2016 to 2021. NS Power responds that the increase is due to higher saturation levels and provides an expanded table with the data.

Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-18: 2 3 With reference to Section 4.4 End-Use Intensity Trends, page 47 of 98, Figure 29: PV...

AI summary NSPI provided an expanded table showing photovoltaic (PV) impact on energy and peak load from 2019 to 2032, including actual new installs and load reductions. The data indicates increasing PV installations and corresponding load reductions over time.

ergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-31: 2 3 With reference to Section 6.3 Large General Service, page 70 of 98, the application in...

AI summary NSPI responded to an NSUARB information request regarding the 2022 Load Forecast Report, explaining that solar adoption is considered in the commercial class but not in the large general service class due to a lack of specific information on self-production.

y and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-32: 2 3 With reference to Section 7.1 Small Industrial, page 71 of 98, the application indicates...

AI summary NSPI responds to NSUARB's request regarding the small industrial class sales forecast, explaining that economic growth, as measured by manufacturing GDP from the Conference Board of Canada, is expected to increase from 0.3% annually to 2% annually, leading to a 0.7% annual sales growth forecast. This is partly offset by demand-side management (DSM) impacts.

ar in the 2021 forecast, with 23 average annual growth of 0.4 percent over the forecast period. Partly offsetting growth 24 will be the impact of DSM over the forecast period. Date Filed: July 8, 2022 NSPI (NSUARB) IR-33 Page 1 of 1 10 - Y...

AI summary The document discusses NSPI's responses to NSUARB information requests regarding energy and demand forecasts. NSPI explains that actual data for peak demand components is not available, and clarifies that increases in load intensities are due to higher adoption rates of appliances and increased use of electronic devices.

ble, and the creation of a strategic 28 plan to achieve these emissions targets by accelerating the integration of sustainable and 29 innovative technologies and approaches. 30 Date Filed: July 8, 2022 NSPI (SBA) IR-2 Page 1 of 3 10 - Year...

AI summary The document discusses the development of a strategic plan to achieve emissions targets through the integration of sustainable and innovative technologies. It references the 10-Year Energy and Demand Forecast from the Load Forecast Report and NSPI's responses to information requests from the Small Business Advocate.

drive growth 23 and remain competitive. This emphasis on clean growth, coupled with emerging 24 opportunities in areas such as critical minerals, electrification, low-carbon 25 construction materials and an array of clean technologies, wil...

AI summary The text discusses opportunities for clean growth in Canada, emphasizing areas such as critical minerals, electrification, and low-carbon construction materials. It highlights the importance of reducing industrial emissions and meeting demand for clean products. A 10-Year Energy and Demand Forecast from the Load Forecast Report is referenced, along with NSPI's responses to information requests.

to assist customers in minimizing upfront capital costs related to decarbonization & 20 electrification. 5 En4-460-2022-eng.pdf (publications.gc.ca) page 52 of 240 Date Filed: July 8, 2022 NSPI (SBA) IR-2 Page 3 of 3 10 - Year Energy and D...

AI summary The document discusses a request related to the 10-Year Energy and Demand Forecast, specifically regarding technologies assumed for space heating electrification and the separation of load data into electrification categories. NSPI provides a list of technologies considered, including various heat pump systems and electric heating solutions.

emand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Small Business Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-4: 2 3 Please refer to page 10 of the Filing: What are the underlying assumptions for t...

AI summary NSPI's response to an information request about the 10% increase in system peak demand from 2021 attributes the growth to the electrification of space heating and increased EV sales, driven by government emission reduction targets. Supporting documentation is referenced in Figure 58 and Synapse IR-42.

d Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Small Business Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-9: 2 3 Please refer to Page 43, Lines 12-22. This section states that it is assumed 70% of...

AI summary The NSPI response to IR-9 discusses the management of EV charging, combining time-based rates and aggregator-based charge management. It clarifies that total kWh load remains unchanged between managed and unmanaged scenarios, but peak demand varies. The forecast assumes no impact on overall consumption, with annual load being the same across all cases.

d Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Small Business Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-10: 2 3 Please refer to the Filing, page 8 of Appendix E. It states that "to achieve policy...

AI summary The NSPI response to the Small Business Advocate's request discusses the assumptions behind heat pump adoption rates in the 2022 Load Forecast Report. The response indicates that these assumptions are based on carbon emission reduction targets rather than incentives or economic analysis, and that current incentives align with historical adoption rates.

nd Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Small Business Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-14: 2 3 Please refer to Figure 32 on Page 51. 4 5 (a) Please confirm that commercial heat...

AI summary NSPI confirms that commercial heat pump adoption is included in the 'Heat' and 'Cool' categories in Figure 32 but commercial electric vehicle adoption is not included in the commercial model. EV load is included in the residential model and will be reallocated to the commercial class in the 2023 forecast, with increasing impacts from 2025 to 2032.

Year Res.Indices Heating Res.Indices Cooling Res.Indices Others XHeat XCool XOther AvgEESavings 15-Apr 15-Apr Aug Jan Sep Oct AContrib2Sales.Feb18 AContrib2Sales.Dec17 ARMA Covid XHeatNew XCoolNew XOtherNew AvgEESavingsNew 15 May New 15 Ap...

AI summary The chunk presents a table with data on residential energy indices, savings, and regression coefficients, likely related to energy efficiency and demand-side management programs under regulatory review in Nova Scotia.

Date Daily Avg Temp Daily Load 10/11/2021 14.02083 25914.76 10/12/2021 15.75417 26505.84 10/13/2021 14.37917 26463.92 10/14/2021 15.03333 26970.68 10/15/2021 12.23333 26588.97 10/16/2021 12.8625 26187.48 10/17/2021 16.49167 26604.07 10/18/...

AI summary The document presents a table showing daily average temperatures and corresponding daily load values from October 11 to December 11, 2021. The data reflects the relationship between temperature and electricity demand over this period.

d Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-14: 2 3 Reference Report p. 86 Figure 60 “Weather-Normalized Firm Peak.” For items a-d bel...

AI summary The document outlines a request (IR-14) made to NSPI regarding the weather-normalized sales, requirements, and peak load data from the 2022 Load Forecast Report. The request includes detailed inquiries about methodology, calculations, and supporting workpapers for the weather normalization process.

of 15 Variable Coefficients Month HDD13 HDD 13 HDD0 lag1 lag2 0 232.686 -97.305 177.016 43.995 Summary May 2021 heating load 50551 MWh Normal heating load 54000 MWh 2021 Varinace to Normal -3449 MWh

AI summary The document presents heating load data for May 2021, showing a total of 50,551 MWh, which is 3,449 MWh less than the normal heating load of 54,000 MWh. This indicates a significant deviation from the expected usage.

August-21 August Normal Total Load from Load Load Load Load Heating Actual Actual Month Load From Load From Load From Load from Load from Total Heating Actual from Feb From From Load Load from Load Day Actual HDD 0 HDD 13 CDD18 HDD13 HDD 1...

AI summary The text provides a table with load data, including HDD (Heating Degree Days) and CDD (Cooling Degree Days) values, along with load measurements in MWh. The data appears to track energy consumption patterns over a specific period, likely for regulatory or planning purposes.

and Demand Forecast (2020 Load Forecast Report) (NSUARB M09707) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-13: 2 3 On page 9 of 137, NS Power reports the 2020 growth in system peak at 8.9% and the prior 4 y...

AI summary This text discusses a request for clarification regarding discrepancies in load forecasts and actual demand in Nova Scotia, specifically focusing on the 2019 and 2020 system peak growth rates. The request seeks explanations for the difference between forecast and actual values, including the impact of lighting load and daylight hours.

ecast Report, pp. 19-24. 7 Exhibit N-7, NS Power response to CA IR-1(c-d). 8 Each of the major components is multiplied by a regression factor, which is close to 1.0 for heating and other, but only 0.6 for cooling. 9 Exhibit N-7, NS Power...

AI summary The analysis examines cooling and heating model outputs, showing increasing CDD-driven cooling demand but stable heating demand despite decreasing HDD. Heat pumps and electrification are suggested to offset reduced heating needs, though NS Power requires further validation of electrification load forecasts.

Evidence of John D. Wilson • Matter No. M10569 • July 29, 2022 Page 9 1 example, NS Power currently includes all EV load in the residential model but will be 2 shifting commercial EV load to the commercial model for the 2023 forecast. 22 3...

AI summary John D. Wilson identifies three issues with NS Power's electrification forecast: modeling errors in residential/commercial heating load assumptions, flawed heat pump adoption trajectory assumptions, and Itron findings showing increased loads due to customer behavior (e.g., warmer homes, expanded floor space). These challenge NS Power's alignment with carbon reduction targets.

SUMMARY OF PROFESSIONAL EXPERIENCE 2019– Research Director, Resource Insight, Inc. Provides research, technical assist- Present ance, and expert testimony on electric- and gas-utility planning, economics, and regulation. Reviews electric-u...

AI summary Summary of professional experience in energy regulation, including roles in utility planning, rate design, conservation programs, renewable energy evaluation, and regulatory policy. Highlights work with organizations focused on energy efficiency, market data, and air pollution reduction.

cs (with honors) and history, Rice University, 1990. MPP, John F. Kennedy School of Government, Harvard University, 1992. Concentration areas: Environment, negotiation, economic and analytic methods. PUBLICATIONS “Urban Areas,” with Judith...

AI summary The text outlines an individual's academic background in environmental policy and their publications on energy efficiency, climate change, and power markets. Key works include studies on urban ecosystems, utility performance incentives, and monopsony behavior in power generation.

John D. Wilson • Resource Insight, Incorporated Page 3 “Increased Levels of Renewable Energy Will Be Compatible with Reliable Electric Service in the Southeast,” Southern Alliance for Clean Energy, November 2014. “Cleaner Energy for Southe...

AI summary The document lists multiple reports by the Southern Alliance for Clean Energy on renewable energy, solar capacity, energy efficiency, and decarbonization in the Southeastern US, highlighting their analysis of seasonal demand, solar equivalent values, and low-cost clean energy pathways.

Practices for All-Source Electric Generation Procurement,” with Mike O’Boyle, Ron Lehr, and Mark Detsky, Energy Innovation Policy & Technology LLC and Southern Alliance for Clean Energy, April 2020. PRESENTATIONS “Clean Energy Solutions fo...

AI summary The text lists presentations on energy topics by Mike O’Boyle, Ron Lehr, Mark Detsky, and affiliated organizations, including discussions on clean energy solutions, utility-scale renewables, and energy efficiency regulation. Presentations date back to 2008 and involve entities like Southern Alliance for Clean Energy and Energy Innovation Policy & Technology LLC.

John D. Wilson • Resource Insight, Incorporated Page 4 “Building the Energy Efficiency Resource for the TVA Region,” presentation on behalf of Southern Alliance for Clean Energy to the Tennessee Valley Authority Integrated Resource Plannin...

AI summary John D. Wilson from Resource Insight, Incorporated has participated in numerous energy efficiency and policy discussions, focusing on integrated resource planning, renewable energy, and regulatory challenges in the Southeast U.S., including presentations on energy efficiency modeling, carbon markets, and the Clean Power Plan.

John D. Wilson • Resource Insight, Incorporated Page 6 2011 South Carolina PSC Docket No. 2011-09-E, allowable ex parte briefing on behalf of Southern Alliance for Clean Energy, South Carolina Coastal Conservation League, and Upstate Forev...

AI summary The text outlines various regulatory proceedings involving energy efficiency and integrated resource plans in South Carolina and Georgia, with John D. Wilson representing environmental and consumer advocacy groups. The proceedings focus on the adequacy of energy efficiency considerations, resource mix, and the use of renewable energy alternatives.

re more fully technologies to control peak space heating and water heating loads. • Explore whether battery storage and solar/battery storage combinations could modify the peak loads. • Provide updates on the water heating load control pro...

AI summary The text outlines initiatives to manage peak loads through battery storage, solar/battery combinations, and DSM program updates. It emphasizes revising pandemic impacts on commercial sales, monitoring DSM savings, and addressing design day temperature changes due to global warming. Heat pumps and water heaters are highlighted as critical for residential energy efficiency.

he peak is first modeled statistically using historical data and economic and demographic projections to produce a Modeled Peak, and then NSPI applies various adjustments to arrive at the System Peak. Table 5. Peak contribution components...

AI summary NSPI models peak demand using historical data and adjustments, with commercial/industrial electrification as the largest growth driver. The 2032 System Peak increases by 350 MW, driven by electrification, residential heating, and EV adoption, though demand response could mitigate some impacts.

peak shares are shown in Figure 61 for the residential sector and in Figure 62 for the commercial sector. Our understanding is that these contributions are in the Modeled Peak values shown previously. In the NSPI response to E1 IR-9, it wa...

AI summary The text requests NSPI to clarify heat pump performance during peak loads, quantify ETS's role in reducing peak demand, and investigate water heating load control. It notes a shift from resistance heating to heat pumps in residential heating but highlights increased water heating contributions. Induction cooking's potential impact on energy use is also mentioned.

• We also raise a point about the appropriateness of the commercial electrification programs. We ask NSPI to provide further information about their relative benefits and costs (p.14). • It is not clear in the report how much of the commer...

AI summary The text outlines requests for clarification and further analysis from Synapse Energy Economics, Inc. regarding NSPI's 2022 load forecast, focusing on commercial electrification programs, demand savings, EV impacts, time-of-use rates, DR measures, thermal storage, and emerging technologies like induction cooking. Questions emphasize cost-benefit evaluation, sector-specific DSM effects, and load management strategies.

Nova Scotia Utility and Review Board IN THE MATTER OF The Public Utilities Act - -and- IN THE MATTER OF NOVA SCOTIA POWER’S 2022 LOAD FORECAST REPORT (M10569) EFFICIENCYONE EVIDENCE FILED July 29, 2022 NOVA SCOTIA POWER 2022 LOAD FORECAST...

AI summary EfficiencyOne submits evidence in the Nova Scotia Utility and Review Board proceeding regarding Nova Scotia Power’s 2022 Load Forecast Report (M10569), covering electrification modeling, demand response plans, and forecasting methodologies. The document outlines sections on heat pump modeling, alternative heating systems, and demand response treatment in the forecast.

Average annual energy net system requirement change -0.1% +0.3% Average annual system peak demand change +0.2% +1.6% 3 4 In response to NSUARB IR-36, NS Power attributed increases forecasted in energy requirement, 5 system peak demand, and...

AI summary NS Power attributes projected energy demand increases to carbon reduction targets and EV adoption. They state models align with net-zero goals but note a lack of market analysis to assess customer responses, emphasizing the need for a comprehensive study to inform policy objectives.

ccelerate low-carbon heating in the UK. Under the 13 RHI, households that have installed a heat pump could claim these tariffs quarterly for seven 14 years based off the dwelling’s heat demand. 15 16 The UK Climate Change Committee’s targe...

AI summary The UK's Renewable Heat Incentive (RHI) program aimed to accelerate heat pump adoption but has significantly underperformed, with only 62,492 accredited installations by 2020 versus a target of 491,000 by 2021. The Regulatory Assistance Project (RAP) highlights this gap, noting that even with incentives, deployment remains far below expectations, undermining climate goals.

EfficiencyOne Evidence 1 climate, including but not limited to, Efficiency Vermont, Massachusetts Clean Energy Center, 2 National Grid, Efficiency PEI, and Energy Star. 3 4 The NS Power On-Bill Financing Study Update (M09321) dated Decembe...

AI summary EfficiencyOne (E1) argues that NS Power's 2022 Load Forecast overestimates peak demand by relying on electric resistance heating below -7°C, potentially misrepresenting cold climate heat pump adoption. E1 recommends updating the model to reflect higher COP standards (1.75 at -15°C) and removing lock-out temperatures. NS Power's assumptions about heat pump adoption rates may not align with market-driven trends.

systems. 16 In its response to E1 IR-05 (b), when asked to confirm if these changes are expected 26 to be market-driven, NS Power stated, “[t]he model is not based on economic uptake. It is based 15 M09321, P701, On-Bill Financing Study Up...

AI summary NS Power's load forecast model prioritizes 100% heat pump saturation to meet emission targets, but lacks evidence for this approach. Alternative heating systems (e.g., ETS, wood stoves) could achieve similar policy goals with different load impacts and market uptake potential, challenging NS Power's assumptions.

as supplemental heat, and gas heating 11 systems as supplemental heat, would have a different impact on load and would likely have a 12 different combination of system investment requirements. 13 14 Given that the 2022 Load Forecast indica...

AI summary The text discusses the impact of heating technologies on load forecasting and grid flexibility, emphasizing the need for peak load management in a net-zero grid. It references the 2022 Load Forecast and the RAP paper 'Heating Without the Hot Air,' which highlights principles for efficient and flexible heat decarbonization.

20 on one particular technology. 21 22 E1 currently offers rebates on wood/pellet stoves and ETS units. These measures have the 23 following evaluated unitary savings as outlined in Table 2: 20 Ibid., page 13. 21 Nova Scotia Power 2020 IRP...

AI summary EfficiencyOne (E1) outlines rebate programs for wood/pellet stoves and electric thermal storage units, citing unitary peak demand savings in Table 2. E1 emphasizes the need for consistent treatment of demand response programs in load forecasts, as part of its 2023-2025 DSM Plan.

EfficiencyOne (E1) – In the Matter of Nova Scotia Power Incorporated’s (NS Power) 10-Year Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL 1 Request IR-01: 2 3 R...

AI summary EfficiencyOne (E1) responds to Nova Scotia Power's (NS Power) request for data on heat pump installations in Nova Scotia, including forecast vs. actual installations, energy consumption, and savings from 2022 to 2025. E1 references UK and RAP reports highlighting gaps between heat pump deployment targets and actual outcomes.

s by year (kWh and kW demand associated with each heat pump installation 23 or overall). 24 25 (c) The forecast and actual energy and demand savings for heat pump installations by year. Date Filed: 12 September 2022 E1 (NS Power) IR-01 Pag...

AI summary The document outlines NS Power's 10-year energy and demand forecast, focusing on heat pump installations' energy savings by year. EfficiencyOne (E1) provided responses to NS Power's information requests as part of the regulatory proceeding M10569, which includes forecasts and actual energy/demand savings data.

1 (d) The forecast and actual incentive ($) totals associated with heat pump installations by 2 year. 3 4 (e) The average coefficient of performance (COP) of heat pumps installed by year. 5 6 Response IR-01: 7 EfficiencyOne has historicall...

AI summary EfficiencyOne (E1) provides data on heat pump installations under the Green Heat program, including forecast vs. actual installations and COP metrics. Data sources include DSM Evaluation Reports and specific matter numbers (e.g., M03669, M04819). The 2015 DSM Plan was not modeled.

2024 M10473 E-1(i) Appendix A Attachment 4 2023- n/a 2025 Settlement Plan Measure Level Energy Efficiency Technical Tables • Rows 254, 255, 256, 257 • Column Z 2025 M10473 E-1(i) Appendix A Attachment 4 2023- n/a 2025 Settlement Plan Measu...

AI summary EfficiencyOne (E1) provides data on heat pump energy savings from DSM Plans and technical tables for NS Power’s 2025 Settlement Plan. The document references measure-level energy efficiency data and a 10-year forecast proceeding (M10569).

1 evaluation reports respectively. E1 does not track the forecast or actual energy 2 consumption or demand associated with heat pump installations in the Green Heat 3 program component. 4 5 (c) Please refer to the table below for the forec...

AI summary E1 does not track forecast or actual energy consumption data for heat pump installations in the Green Heat program. A table provides references to evaluation reports and matter numbers (e.g., M03669, M04819) for annual energy and demand savings from 2012 to 2016, with specific document tabs, rows, and columns cited.

Year Forecast Energy Savings Forecast Demand Actual Energy Actual Demand Savings Savings Savings 2019 n/a (2019 DSM Plan was not modelled) M09651, E-1, 2019 DSM Evaluation Reports, Existing Residential Program, Table 36, page 65. 2020 M090...

AI summary The document outlines forecasted and actual energy savings from 2019 to 2024, referencing DSM evaluation reports and technical tables. It links forecast data to specific matters (e.g., M09651, M10473) and EfficiencyOne (E-1) appendices, highlighting discrepancies between planned and realized energy efficiency outcomes.

025 Settlement Plan Measure Level Energy Efficiency n/a Technical Tables • Rows 254, 255, 256, 257 • Column AB • Column AA 2025 M10473 E-1(i) Appendix A Attachment 4 2023-2025 n/a Settlement Plan Measure Level Energy Efficiency Technical T...

AI summary The document outlines EfficiencyOne's (E1) responses to Nova Scotia Power's (NS Power) information requests regarding energy efficiency measures, including technical tables and incentive levels for heat pumps under the Green Heat program. It references forecast and actual incentive data from 2012 and mentions the 2022 Load Forecast Report proceeding (M10569).

2022 M09096 E-1(i) Appendix A Attachment 1 n/a Technical Tables • Rows 248, 255, 256, 257; Column J Column K 2023 M10473 E-1(i) Appendix A Attachment 4 2023- n/a 2025 Settlement Plan Measure Level Energy Efficiency Technical Tables • Rows...

AI summary The document references technical tables from multiple regulatory matters (M09096, M10473, M10569) related to energy efficiency metrics, including average coefficient of performance (COP) data for mini-split heat pumps in Nova Scotia's Green Heat program from 2015-2021. EfficiencyOne (E1) and Nova Scotia Power Incorporated (NS Power) are central to the proceeding.

E1 (NS Power) IR-01 Page 7 of 7 EfficiencyOne (E1) – In the Matter of Nova Scotia Power Incorporated’s (NS Power) 10-Year Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CON...

AI summary EfficiencyOne (E1) recommends NS Power explore electrification scenarios using electric thermal storage (ETS), wood/pellet stoves, and gas heating systems. E1 requests data on installations, energy consumption, demand savings, and rebate totals for these technologies from rebate inception through the 2025 DSM plan, emphasizing grid flexibility and peak load management.

• Rows 260, 261, 269, 270 • Column Z 2024 M10473 E-1(i) Appendix A Attachment 4 2023- n/a 2025 Settlement Plan Measure Level Energy Efficiency Technical Tables • Rows 260, 261, 269, 270 • Column Z 2025 M10473 E-1(i) Appendix A Attachment 4...

AI summary EfficiencyOne (E1) responds to Nova Scotia Power Incorporated (NS Power) information requests regarding the 10-Year Energy and Demand Forecast (2022 Load Forecast Report) in regulatory proceeding M10569. The document includes references to Energy Efficiency Technical Tables and forecast data from 2012–2017.

Year Forecast Number of ETS Actual Number of ETS 2018 n/a n/a 2019 n/a n/a 2020 M09096 E-1(i) Appendix A Attachment 1 M10056, E-1, 2020 DSM Evaluation Reports, Technical Tables Existing Residential Program, Table 30, pages • Rows 157, 158...

AI summary The document presents a table comparing forecasted and actual Energy Efficiency Savings (ETS) across years 2018-2025, referencing specific regulatory matters (e.g., M09096, M10473) and technical tables from DSM evaluation reports. It highlights discrepancies between projected and actual savings for energy and demand reductions, with citations to evaluation reports and technical data.

• Rows 263, 264 • Column Z 1 2 (b) E1 has projected and actual total energy and demand savings for both ETS and wood/pellet 3 stove installations by year as provided in measure level technical tables associated with 4 DSM Plans and annual...

AI summary E1 (EfficiencyOne) provides projected and actual energy savings data for ETS and wood/pellet stove installations but does not track energy consumption in the Green Heat program. Tables in DSM Plans and annual evaluations are referenced for detailed savings data.

1 Table 1 Year Forecast Energy Forecast Demand Actual Energy Actual Demand Savings Wood/Pellet Savings Wood/Pellet Savings Savings Stove Stove Wood/Pellet Wood/Pellet Stove Stove 2012 M03669, E-9 (C ), ENSC (Synapse) RIR-01 M04819, Other D...

AI summary The text references tables comparing forecasted and actual energy/demand savings from 2012-2016, citing specific documents like DSM Evaluation Reports and matter numbers (e.g., M03669, M04819). It links data to entities like ENSC (Synapse), E1 (EfficiencyOne), and NSPI (Nova Scotia Power Incorporated).

Green Heat, Table 14, page 32. 2016 M06733, E-7 E1 (NSPI) RIR-10 Attachment 1 M07964, E-1, 2016 DSM Evaluation • Rows 238, 240 Reports, Existing Residential Program, Table 28, page 64. • Column AA • Column Z 2017 M06733, E-7 E1 (NSPI) RIR-...

AI summary The text lists references to Green Heat and DSM Evaluation Reports from 2016 to 2021, citing matter numbers (e.g., M06733, M07964) and specific table rows/columns in documents related to Nova Scotia Power Incorporated (NSPI) and EfficiencyOne (E1). It tracks DSM program evaluations across years.

Year Forecast Energy Forecast Demand Actual Energy Actual Demand Savings Wood/Pellet Savings Wood/Pellet Savings Savings Stove Stove Wood/Pellet Wood/Pellet Stove Stove 2022 M09096 E-1(i) Appendix A Attachment 1 Technical n/a Tables • Rows...

AI summary The text presents tables comparing forecast and actual energy/demand savings across years (2022-2025), referencing specific regulatory matters (M09096, M10473) and technical appendices. It includes row/column references from '2023-2025 Settlement Plan Measure Level Energy Efficiency Technical Tables' and mentions 'ETS Unit Installations' in energy savings contexts.

2022 M09096 E-1(i) Appendix A Attachment 1 n/a Technical Tables • Rows 157, 158 • Column BB • Column BA 2023 M10473 E-1(i) Appendix A Attachment 4 2023- n/a 2025 Settlement Plan Measure Level Energy Efficiency Technical Tables • Rows 263,...

AI summary The text references technical tables from multiple years (2022–2025) related to incentive levels for wood/pellet stoves and ETS units in Green Heat. It cites specific regulatory matters (e.g., M09096, M10473) and attaches detailed incentive structures, including forecast vs. actual levels and cost thresholds.

2.5 Recommendation 5: .....................................................................19 33 3.2.6 Recommendation 6: .....................................................................19 DATE FILED: September 26, 2022 Page 2 of 25 20...

AI summary This document is a rebuttal to the 2022 Load Forecast Report, containing sections on recommendations related to load forecasting, small business advocacy, and efficiency programs. It outlines various recommendations and stakeholder positions within a regulatory proceeding context.

D: September 26, 2022 Page 21 of 25 2022 Load Forecast Report Rebuttal NON-CONFIDENTIAL 1 NS Power Response: 2 3 The scenario modeled by E3 assumed a COP of 2.3 at -15 degrees Celsius for 4 new heat pumps installed over the forecast period...

AI summary NS Power responds to recommendations regarding electrification scenarios by agreeing to explore a hybrid approach in the 2022 IRP Evergreen analysis. They note limitations in the adoption of ETS units, wood and pellet stoves, and gas heating systems due to factors like limited uptake, physical effort requirements, and limited natural gas availability.

ear actual 2 Based on Table A2 in 2022 and 2021 Load Forecast reports and in Table A3 in each annual report from 2015 to 2020 Document: 298717 -3- However, the significant increase in Load for 2022 is mainly attributed to the application o...

AI summary NS Power attributes a 2022 load increase to E3's estimated peak model, planning to validate it with AMI data. Intervenors praised forecast improvements but raised concerns about heat pump adoption, EV growth, new demand-reducing technologies, and peak management via Smart Grid Nova Scotia (SGNS) project outcomes.

ing storm closures at peak periods. Lastly, Mr. Wilson requested that NS Power complete the line loss determination model and report on its progress on a quarterly basis until the project is complete. The SBA raised concerns about the accu...

AI summary Mr. Wilson requested NS Power to finalize the line loss model with quarterly updates. The SBA questioned the EV and space heating forecast accuracy, urging data integration and incentive evaluation. EOne recommended updating heat pump models, exploring electric thermal storage, and assessing DR capacity frameworks to address growing peak load.

mpacts on peak. Synapse asked that NS Power review its peak forecasting methodology and provide a peak sensitivity analysis as well as the assumptions and calculations used. NS Power Reply Submission In its Reply, NS Power addressed the co...

AI summary Synapse requested NS Power to review its peak forecasting methodology and provide sensitivity analyses. NS Power agreed to incorporate multi-hour weather data, refine electrification impact assessments, and evaluate hybrid demand response scenarios while integrating findings from recent studies and projects.

n process, as well as a scenario analysis for ETS to moderate peak load. It will monitor growth in heating load for commercial customers and work with EOne on possible firm peak mitigation strategies. NS Power confirmed that the model used...

AI summary NS Power discusses heat pump COP assumptions, DSM allocation between commercial and industrial classes, and rejects intervenor requests on line loss modeling and ELCC factors for LIIR. It also denies a request for commercial electrification analysis and plans to address EV load shapes with ELCC adjustments.

Document: 295519 (P-194) Date Filed: June 9/22 UARB (NSPI) Pg. 5 of 10 1 Request IR-13: 2 With reference to Section 4.4 End-Use Intensity Trends, page 41 of 98, Figure 25: Water Heater 3 Forecast: 4 a) Please provide actuals for the years...

AI summary The UARB requests data on water heater end-use intensity trends (2016-2021 actuals) and explanations for forecast discrepancies. It also seeks sources for EV adoption estimates, stock rollover data, and comparative EV forecast tables between 2021 and 2031 models.

Document: 295519 (P-194) Date Filed: June 9/22 UARB (NSPI) Pg. 8 of 10 1 Request IR-28: 2 With reference to Section 5.0 Residential Sector, page 61 of 98, the application states, “While 3 efficiency is expected to increase, house size is a...

AI summary The UARB requests clarifications on NSP's load and sales forecasts, including assumptions about residential efficiency, commercial sales declines, small industrial growth, and renewable energy integration in hospital expansions. Questions focus on data sources, growth rate changes, and adjustments for renewable energy impacts.

Document: 295519 (P-194) Date Filed: June 9/22 UARB (NSPI) Pg. 9 of 10 1 Request IR-33: 2 With reference to Section 7.2 Medium Industrial, page 72 of 98, the application indicates that the 3 load in this class has been flat since 2014 and...

AI summary The UARB requests detailed explanations from NS Power regarding load growth projections, peak demand data, energy efficiency assumptions, and factors driving post-2022 energy requirement growth. Requests focus on economic activity drivers, load forecast discrepancies, energy efficiency intensity values, and unaccounted growth factors.

Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 4 of 16 1 c. Please provide supporting evidence for the 35 percent saturation of customers providing 2 their heat via heat pumps in 2022 (p.36). 3 d. Please provide the data s...

AI summary The document outlines regulatory requests from the Board to NSPI and E3 regarding heat pump saturation data, residential water heater efficiency standards, and electric vehicle load patterns. Requests focus on evidence, data sources, and impact analyses for heat pumps, water heating technologies, and EV integration into the grid.

Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 5 of 16 1 Request IR-10: 2 Solar Generation (PV) (Section 4.4, pp 45-47) 3 a. Please provide supporting data for the average capacity and capacity factor for the PV 4 installa...

AI summary The document outlines regulatory requests for data on solar PV capacity, home battery costs, end-use intensity calculations, and commercial/industrial growth assumptions. It seeks detailed explanations for figures and projections related to renewable energy, energy storage, and demand-side management.

Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 7 of 16 1 d. Please explain in more detail the reasoning behind the continued work-from-home impacts 2 at 2023 levels. 3 e. The report cites increased electric heating load as...

AI summary The document contains regulatory requests for detailed explanations on work-from-home impacts, electric heating load growth, building efficiency regulations, and commercial sector energy usage forecasts. Questions focus on quantifying load changes, calculation methodologies, and potential regulatory impacts on energy efficiency metrics.

Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 10 of 16 1 h. Please provide the data and calculations behind the peak share values in Figures 61 and 2 62 including the actual load values as well as the percentages. Please...

AI summary The document contains regulatory requests for data and explanations related to peak demand analysis, AMI coverage, DSM impacts, and sensitivity analysis variables. Requests include clarifying peak share calculations, AMI coverage levels, loss levels, DSM differences, and the rationale for selected sensitivity analysis variables.

Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 13 of 16 1 Request IR-38: 2 Appendix B: Combined Model for Commercial and Industrial DSM Coefficient (pp 25-26) 3 a. Please provide in electronic spreadsheet format the data a...

AI summary The document contains regulatory requests (IR-38 to IR-41) directed at Synapse (NSPI), seeking detailed data, methodological explanations, and justifications for models related to demand-side management (DSM) coefficients, peak forecasts, and forecast accuracy. Requests focus on transparency in statistical models, variable selection, and data normalization.

M10569 – SBA IRs – June 16, 2022 Page 3 of 5 1 a) Is it truly accurate to describe this as a forecast, or would it best be termed as an 2 “adoption scenario”? 3 b) Given that this is one scenario, has NSPI or E3 forecasted adoption rates u...

AI summary The document contains 16 requests (IR-1 to IR-16) questioning NSPI and E3's electrification forecasts, including terminology accuracy, adoption scenario discrepancies, categorization of electrification (heating/cooling vs. transportation), and methodology for accounting for electrification in commercial and industrial classes.

Date Filed: June 16, 2022 CA (NSPI) Page 2 of 11 1 b. If NS Power does not have load data by transmission zone, please explain how NS 2 Power determines load flows in transmission planning. 3 4 c. Please discuss NS Power’s plan to develop...

AI summary The document includes regulatory requests to NS Power regarding load data management, transmission planning, EV charging impact assumptions, and DSM adjustments. Questions focus on data collection methods, EV load modeling, and demand-side management efficacy, with specific references to technical reports and forecasting methodologies.

Requests to Nova Scotia Power Inc. (NS Power) In the Matter of Nova Scotia Power Incorporated’s 2022 Load Forecast Report – M10569 NON-CONFIDENTIAL 1 (a) Please describe the specific assumptions and/or modelling approaches that are 2 causi...

AI summary The document requests Nova Scotia Power Inc. (NS Power) to clarify assumptions in its 2022 Load Forecast Report, including heat pump performance modeling, commercial electric heating share estimates, model calibration issues, and low-temperature COP behavior. Specific focus areas include heat pump capacity decline, backup heating reliance, and temperature thresholds for COP performance.

ed to back-up) expected below 23 -15 °C? 24 (iii) At what temperature(s) are heat pump coefficients of performance expected 25 to reach 1.0? Date Filed: June 16, 2022 E1 (NS Power) Page 5 of 8 EfficiencyOne (E1) Information Requests to Nov...

AI summary The text includes questions about heat pump performance at specific temperatures and references a 2022 Load Forecast Report proceeding. EfficiencyOne (E1) has requested information from Nova Scotia Power Inc. (NS Power) regarding these technical parameters.

d incentive structures availabie to Nova Scotians3 • This is very important since we can see that electrification is expected to add at least 605 OWh oflaod and 267 MW of peak in 2030 of the Report4 • As such, while the SBA recognizes this...

AI summary The SBA highlights gaps in Nova Scotia's understanding of consumer interventions needed for electrification, stressing the need for historical data from the SONS Project, real-world adoption rates, and uncertainty evaluations in load forecasts. It acknowledges electrification's impact on system requirements but emphasizes data refinement for accurate planning.

1 Request IR-1: 2 3 Reference: EfficiencyOne evidence, July29, 2022, pages 4-5. 4 The UK Climate Change Committee’s target was, and still is, to reach deployment 5 levels of 600,000 heat pumps per annum in existing homes and 300,000 heat p...

AI summary The text references UK heat pump deployment targets and highlights a significant shortfall in installations despite incentives. EfficiencyOne is requested to provide data on heat pump installations, energy savings, and incentive costs from 2022 to 2025, aligning with Nova Scotia's DSM plan. The Regulatory Assistance Project (RAP) report underscores the gap between forecasted and actual heat pump installations under the RHI scheme.

ficient of performance (COP) of heat pumps installed by year. 25 26 Request IR-2: 27 28 Reference: EfficiencyOne evidence, July 29, 2022, page 9 of 14. 29 30 E1 recommends that NS Power explore electrification scenarios that maintain or 31...

AI summary EfficiencyOne recommends NS Power explore electrification scenarios using electric thermal storage (ETS) units, wood, and pellet stoves for grid flexibility and peak demand management. The text references a 2022 Load Forecast Report (M10569) and cites EfficiencyOne's evidence from July 2022.

0 - Year Energy and Demand Forecast (2022 Load Forecast Report) NSPI Information Requests to EfficiencyOne NON-CONFIDENTIAL 1 • gas heating systems as supplemental heat for peak times. 2 3 E1 states that they provide rebates on wood/pellet...

AI summary NSPI requests data from EfficiencyOne on rebate programs for wood/pellet stoves and ETS units, including installations, energy savings, and incentives, from rebate inception to the end of the 2025 DSM plan.

EV forecast, investigation of new technologies to reduce energy and peak demand, and the management of peak through the Smart Grid Nova Scotia (SGNS) project results and direct control water heaters. The CA filed evidence prepared by John...

AI summary The document discusses John Wilson's recommendations for NS Power to improve climate change scenario analysis, enhance weather station integration, refine peak load forecasting models, and address modeling errors in residential energy models. Wilson also suggests adjustments to heat pump assumptions and EV usage during peak periods, alongside completing the line loss determination model with quarterly reporting.

ing storm closures at peak periods. Lastly, Mr. Wilson requested that NS Power complete the line loss determination model and report on its progress on a quarterly basis until the project is complete. The SBA raised concerns about the accu...

AI summary Concerns were raised about the accuracy of EV and space heating forecasts, the incorporation of SGNS project data, and the adequacy of demand response (DR) capacity. EOne recommended updating heat pump models and exploring electrification scenarios with electric thermal storage (ETS). Mr. Wilson requested NS Power to complete a line loss determination model and report progress quarterly.

n process, as well as a scenario analysis for ETS to moderate peak load. It will monitor growth in heating load for commercial customers and work with EOne on possible firm peak mitigation strategies. NS Power confirmed that the model used...

AI summary NS Power discusses heat pump efficiency (COP 2.3 at -15°C), DSM allocation (15% industrial, 85% commercial), and DR strategies. It rejects intervenors' requests for line loss modeling, ELCC for LIIR, and commercial electrification analysis. The IRP Action Plan includes lock-out temperature analysis removal.