N-12024 Load Forecast Report + Appendices - Redacted
8 passages
..................................................... 14 6 4.0 Discussion of Major Inputs ................................................................................................ 16 7 4.1 Historical Class Sales and Energy Data .......
AI summary The document outlines a regulatory proceeding's structure, detailing sections on historical energy data, weather patterns, economic factors, end-use intensity trends, price data, demand-side management, renewable energy integration, and sector-specific analyses for residential and commercial sectors.
EMOVED) 2024 Load Forecast Report REDACTED 1 Figure 3: Historic and Forecast Net System Requirement and System Peak 2 Year NSR (GWh) Growth (%) System Peak (MW) Growth (%) 2014 11,037 -1.4 2,118 4.2 2015 11,099 0.6 2,015 -4.9 2016 10,809 -...
AI summary The 2024 Load Forecast Report presents historical and projected data on Nova Scotia's Net System Requirement (NSR) and System Peak from 2014 to 2034, showing fluctuating growth trends with a general upward trajectory in energy demand and peak load requirements.
ent licensed retailers to sell renewable energy generated within the 25 province directly to NS Power’s retail customers. The impact of this input is discussed in 26 Section 4.7. 27 DATE: April 30, 2024 Page 16 of 100 REDACTED (CONFIDENTIA...
AI summary The text outlines the impact of renewable energy sales by licensed retailers to NS Power's customers, referencing Section 4.7. It discusses weather data's influence on electric sales, using Heating Degree Days (HDD) and Cooling Degree Days (CDD) calculated from 10 years of temperature data (2014–2023), noting a warming trend with a 10-year HDD average of 3,743 versus a 30-year average of 3,864.
INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 5: 10 Year Normal Monthly HDDs and CDDs 2 3 4 5 The annual number of HDD has been declining as a result of climate trends, as shown in 6 Figure 6. 7 8 Figure 6: Historic Annu...
AI summary The 2024 Load Forecast Report analyzes climate trends impacting Heating Degree Days (HDD) and Cooling Degree Days (CDD). HDD has declined by ~17/year due to warming, while CDD increased by ~1.4/year. Trends are derived from regression analysis of 30-year data with 10-year moving averages, illustrated in figures 5-8.
REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 8: CDD Trend 2 3 4 5 These trends are reduced over time (approximately 40 years) such that the average annual 6 HDD is not forced to 0 and the average...
AI summary The 2024 Load Forecast Report analyzes HDD and CDD trends over a 10-year period, showing a projected reduction in annual HDD to 3,600 by 2034 and an increase in CDD to 129. This indicates declining winter heating demand and rising summer cooling demand for residential and commercial sectors, with leap years causing temporary spikes in 2024, 2028, and 2032.
IAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 9: Annual HDD and CDD Over Time 2 3 4 5 Like the 2023 model, for the 2024 peak model the temperature input uses a 12-hour lagged 6 temperature in combination with an aver...
AI summary The 2024 Load Forecast Report discusses methodology using 12-hour lagged temperature and wind speed data, noting a decreased average temperature compared to 2023 and a rising minimum temperature trend of 0.13°C/year. These factors contribute to an increased peak demand forecast and are supported by climate data from the Climate Atlas of Canada.
Res Comm Ind Other Losses NSR 2023 Forecast 4,830 3,142 2,436 138 742 11,288 Est. Weather Impact -126 -25 -3 -11 -164 Large Customer New Projects -3 -3 Large Customer Actuals -260 -260 Unexplained Variance 230 -8 -12 19 40 270 2023 Actual...
AI summary The text presents a forecast and actual data for 2023, highlighting variances due to weather, unexplained residential class variance, and large customer actuals. It notes that 2023 was warmer than average, impacting heating and cooling loads. NSR is projected to increase by 0.2% annually from 2024 to 2034, driven by new customers, space heating, and EV adoption.
Residential Commercial Industrial Municipal Total Year Sector Growth Sector Growth Sector Growth and Other Growth Losses Energy Growth GWh % GWh % GWh % GWh % GWh GWh % 2014 4,404 1.0 3,222 -0.7 2,522 -3.1 198 -1.4 691 11,037 -1.4 2015 4,5...
AI summary The document presents energy consumption data across residential, commercial, industrial, municipal, and other sectors from 2014 to 2027, showing varying growth rates and energy usage trends over time.
N-4NSPI (NSUARB) RIR-1 to RIR-26
7 passages
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-2: 2 3 Figure 5: 10 Year Normal Monthly HDD and CDDs on page 19 of the Report, please explain 4 why there are HDD in July...
AI summary NSPI explains that Heating Degree Days (HDD) in July and August of the 2024 Load Forecast Report occur because average temperatures occasionally fall below 18°C during those months, even though they are typically summer months.
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 2 3 (i) The increasing number of cooling degree days (CDD) will drive additional cooling 4 load, but they are increasing at a very s...
AI summary NSPI highlights that while cooling degree days (CDD) increase slowly, heat-pump adoption drives larger load impacts. Regression equations in the 2024 Load Forecast Report (NSUARB M11689) changed due to updated data (1994-2023 vs. 1993-2022), with R² values for HDD slightly decreasing and CDD improving, though both remain strong fits.
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-5: 2 3 Page 23 of the Report indicates that NS Power expects Nova Scotia’s annual population 4 growth peaked in 2023. 5 6...
AI summary NSPI attributes population growth projections to the Conference Board of Canada, noting slowing growth rates but no policies altering trends. The 2 million population target by 2060 is deemed aspirational and not factored into forecasts. The 2024 Load Forecast Report shows reduced population growth after 2024 compared to prior projections.
ge the rate 27 of population growth beyond demographics and current trends; the Provincial population 28 target of 2 million by 2060 is aspirational and not taken into account. 29 Date Filed: June 19, 2024 NSPI (NSUARB) IR-5 Page 1 of 2 20...
AI summary NSPI explains that population growth projections beyond current trends are not factored into forecasts, as the 2060 target of 2 million is aspirational. The 2024 Load Forecast Report uses updated data from the Conference Board of Canada, with source details in Synapse IR-05. NSPI did not adjust housing forecasts for the Housing Accelerator Fund, as it was ongoing during forecast development.
NSPI (NSUARB) IR-7 Page 1 of 2 2024 Load Forecast Report (NSUARB M11689) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 (b) NS Power is not aware of why the historic series changes, but Statistics Canada lists a 2 change...
AI summary NSPI responds to NSUARB's information requests regarding the 2024 Load Forecast Report, noting revisions to historic employment data due to Statistics Canada's NAICS 2022 update and lack of details from the Conference Board of Canada on forecast changes.
of 2 2024 Load Forecast Report (NSUARB M11689) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 (c) Cooling intensity has also increased but is of a smaller magnitude compared to heating. 2 No specific adjustments have been...
AI summary NSPI's response to NSUARB's information requests notes that while cooling intensity has increased, no specific model adjustments were made for cooling due to the model's good fit with actual summer load data. The report is part of the 2024 Load Forecast proceeding (NSUARB M11689).
8 for example, changes to the fuel sources for heating or purchasing more efficient appliances 29 as they reach end of life. These longer-term changes are driven by the end use components 30 of the SAE model and therefore a separate elasti...
AI summary NSPI responds to NSUARB's IR-18 request regarding population projections in the 2024 Load Forecast Report. It clarifies that 2034 population growth projections (1.140 million) remain consistent between 2023 and 2024 forecasts, with differences attributed to updated 2022/2023 population counts. NSPI states it does not separately evaluate population growth against deaths/emigrations.
N-6NSPI (Synapse) RIR-1 to RIR-54 - Redacted
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Synapse IR-09 Attachment 2 Figure 27, 64 Synapse IR-10 Attachment 1 Figure 28 Synapse IR-11 Attachment 1 Figure 30 2024 LFR Attachment 2, tab Intensity Figure 32 2024 LFR Attachment 4, tab CommGrowth Figure 33 Synapse IR-17 Attachment 1, t...
AI summary The document lists figures and attachments from the 2024 Load Forecast Report (NSUARB M11689) and Synapse IR submissions, including responses by NSPI to information requests. It references multiple tabs and appendices containing load forecast data, regression analyses, and model details.
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-2: 2 3 Historical Sales and Energy Data (Figures 1, 3, 37-39, 43, 45-46, 48-50, 52). For all of the 4 following, to the...
AI summary NSPI responds to Synapse's IR-2 requests by directing to spreadsheet attachments containing historical sales data, electric space-heat usage, system load data, and unmetered sales. Notably, 2023 electric heat data is unavailable, and unmetered sales comprised ~0.7% of total sales in 2023.
stical relevance as shown 24 by high P-values (Small Industrial), or the model loses statistical relevance as shown by a 25 reduced adjusted R squared value (Medium Industrial). Date Filed: June 19, 2024 NSPI (Synapse) IR-3 Page 1 of 1 RED...
AI summary The text presents statistical analysis of load forecasting models for different industrial sectors, noting that model relevance is affected by P-values and adjusted R-squared values. Tables show accrued and billed sales data from 2014–2023 across residential, industrial, and general demand categories, as part of the 2024 Load Forecast Report.
253 257 247 245 254 261 253 257 264 257 Medium Industrial 471 476 463 463 472 461 468 476 483 473 Residential variance 0.8% 0.4% -1.3% -0.2% -0.8% 0.5% 0.5% -0.9% 0.6% -1.0% Small General variance 0.7% 0.1% -1.1% -1.0% -0.2% 0.0% -0.4% -0....
AI summary The text presents load forecast variance data for different customer classes, including residential, small general, general demand, small industrial, and medium industrial sectors. It references the 2024 Load Forecast Report (NSUARB M11689) and NSPI's responses to Synapse Information Requests, indicating regulatory analysis of energy usage patterns and forecasting methodologies.
nd. Please identify 25 the years represented on the x-axis for Figure 8. 26 27 (f) Please provide the data and calculations behind the HDD and CDD forecast in Figure 28 9. 29 Date Filed: June 19, 2024 NSPI (Synapse) IR-4 Page 1 of 3 REDACT...
AI summary The document contains requests for clarification on figures 8 and 9 from a 2024 Load Forecast Report submitted by NSPI to NSUARB (M11689). It seeks data on x-axis years for Figure 8 and HDD/CDD forecast calculations for Figure 9, reflecting regulatory scrutiny of load forecasting methodologies and energy usage patterns.
f Canada’s view of the most likely future. 17 18 (k) Bank forecasts are checked for discrepancies in the near-term GDP and employment 19 forecasts, which are provided in Attachment 1. Date Filed: June 19, 2024 NSPI (Synapse) IR-5 Page 4 of...
AI summary The document references Canada's economic outlook, emphasizing checks on bank forecasts for GDP and employment discrepancies. It includes a 20-year CBoC forecast and is part of NSPI's 2024 Load Forecast Report, filed on June 19, 2024.
3178.2 521.0 36.7 1.8 5716 41220 484 21522 2029 1.7 3.8 39326.3 45120.1 3284.7 526.0 36.9 1.8 5485 41835 489 21771 2030 1.5 3.5 40574.4 45708.6 3394.4 530.6 37.2 1.8 5042 42314 493 22018 2031 1.4 3.1 41859.0 46353.3 3502.6 535.1 37.4 1.9 4...
AI summary The text presents a redacted 2024 Load Forecast Report (Synapse IR-5 Attachment 1) containing numerical data spanning 2029–2034, likely related to energy load projections. The document is part of a regulatory proceeding, with confidential information removed.
23124 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-5 Attachment 1 Page 2 of 4 Bank Source GDP Emp Housing 2024 2025 2024 2025 2024 2025 BMO Provincial Economic Outloo 0.9% 1.6% 0.8% 1.0% 10000 8000 RBC P...
AI summary The document presents economic and demographic data from 2013–2016, including GDP growth, employment trends, and housing completions, sourced from BMO, RBC, TD, and National Bank. This data is part of Synapse's 2024 Load Forecast Report, used for energy demand projections.
2034 2024 502021 7021 1083.24 29,718 6,826 0.040017 -5000 2025 508635 6614 1101.81 18,571 6,614 0.040426 Change in Res Customers Change in Population Housing Completions 2026 514805 6169 1113.59 11,784 6,169 0.040693 2027 520500 5695 1120....
AI summary The text presents numerical data tables covering projected customer changes, population shifts, housing completions, and household size trends from 2024 to 2034. It references a confidential '2024 Load Forecast Report' by Synapse, indicating analysis of energy demand forecasting and demographic factors influencing residential energy usage.
2.524167 2002 2.480833 2.60 2003 2.463333 2004 2.443333 2.50 2005 2.408333 2.40 2006 2.373333 Household Size 2007 2.344167 2.30 2008 2.324167 2009 2.3075 2.20 2010 2.296667 2011 2.279167 2.10 2012 2.259167 2.00 2013 2.234167 2014 2.215 1.9...
AI summary The 2024 Load Forecast Report (NSUARB M11689) includes NSPI's responses to Synapse Information Requests, presenting historical and projected electricity consumption data by household size from 2002 to 2034. The data highlights trends in energy usage patterns and load forecasting methodologies.
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 Request IR-6: 2 3 Residential End-Use Intensity Trends (Section 4.4, pp 30-50) 4 5 (a) Please provide in electronic spreadsheet for...
AI summary NSPI provided data from NRCan and U.S. EIA for residential and commercial models, detailing adjustments to align end-use intensities with NRCan reports and NS Power billing data. Attachments include raw data and modeling specifics.
End Use Consumption Data End-Use Stock Data Room and central air- Table 4 Table 27 conditioning Electric furnace and heat Table 9 Table 21 pumps Electric hot water Table 10 Table 28 Refrigerator, freezer, Table 13 Table 31 dishwasher, clot...
AI summary The document outlines data sources for end-use consumption, referencing NRCan and EIA data, with specific tables in Attachment 2 and references to '2024 LFR Attachment 01' and a 'Calibration' tab for aggregating household consumption data.
8 9 (c) Please refer to 2024 LFR Attachment 01. On the tab labeled “Calibration,” individual end- 10 use consumption based on NRCan data is added together to give a household view of Date Filed: June 19, 2024 NSPI (Synapse) IR-6 Page 2 of...
AI summary NSPI's 2024 Load Forecast Report uses NRCan data for individual end-use consumption, aligns it with NS Power's billing records via a scaling factor, and applies this factor to annual end-use intensity values for calibration.
7 1402 28 28 2 17 26 6 60% 60% 20% 57% 39% 30% 44% 35% 35% 8 1433 16 18 1 21 36 9 34% 38% 10% 70% 54% 45% 42% 33% 33% 9 1336 43 43 2 14 11 5 91% 91% 20% 47% 16% 25% 49% 39% 39% 10 1356 3 3 1 1 4 1 6% 6% 10% 3% 6% 5% 6% 5% 5% 11 1776 0 7 4...
AI summary The document includes data from the 2024 Load Forecast Report (NSUARB M11689) and NSPI's responses to Synapse Information Requests. The data appears to be related to load forecasts and energy usage patterns, though much of the content is redacted due to confidentiality.
Year Month ResEndUse.ResCool NResEndUse.SmlGenCool NResEndUse.GenCool mVars.CoolLoad mVars.Days mVars.Cool_AvgMW mPkDayWthr.PkCDDIdx mVars.Cool_Var 2020 8 58,848.7 5,353.0 42,085.2 106,286.9 31.0 142.9 1.0 148.6 2020 9 27,124.0 2,479.2 19,...
AI summary The data presents monthly cooling load and related metrics for residential and non-residential end-use in Nova Scotia from 2020 to 2021. The table includes cooling load, number of days, average cooling demand, and peak cooling degree day index, providing insights into energy usage patterns during cooling seasons.
Year Month ResEndUse.ResCool NResEndUse.SmlGenCool NResEndUse.GenCool mVars.CoolLoad mVars.Days mVars.Cool_AvgMW mPkDayWthr.PkCDDIdx mVars.Cool_Var 2027 3 - - - - 31.0 - - - 2027 4 6.2 0.5 3.5 10.2 30.0 0.0 - - 2027 5 2,263.5 171.8 1,268.3...
AI summary The text presents a table of cooling load data across multiple months and years, including metrics such as cooling load, average megawatts, peak cooling degree days, and other related variables. The data appears to be technical and related to energy usage patterns.
N-8Evidence of Synapse (BCC)
9 passages
ding Nova Scotia Power’s 2024 Load Forecast 1 Figure 1. Net system requirements 12,500 12,000 Net System Requirements 11,500 2020 (GWh) 2021 2022 11,000 2023 2024 Actual 10,500
AI summary The document presents Nova Scotia Power’s 2024 load forecast, illustrating net system requirements from 2020 to 2024. Figure 1 shows projected demand trends, with actual data labeled for comparison. The analysis focuses on energy usage patterns and system capacity planning over time.
2027 2028 2029 2030 2031 2032 2033 2034 Source: Synapse from Figure 1 in NSPI’s 2024 Load Forecast Report (2024 Load Forecast) and responses to Synapse IR-1
AI summary The text presents a series of years (2027–2034) alongside a source citation referencing Synapse’s work in NSPI’s 2024 Load Forecast Report and responses to Synapse IR-1, indicating data related to long-term energy demand projections.
r’s 2024 Load Forecast 3 Figure 2. Firm peak demand 2,700 2,500 Firm Peak Demand (MW) 2,300 2020 2021 2,100 2022 2023 2024 1,900 Actual 1,700
AI summary The document presents a 2024 load forecast with firm peak demand data from 2020 to 2024, showing a decline from 2,700 MW in 2020 to 1,900 MW in 2024, with actual demand values plotted for each year.
281 -37 -68 4 115 -145 2,670 147 2,851 mitigation) Source: Figure 61 from 2024 Load Forecast NSPI provides the percent error and mean absolute percent error for the firm peak forecast in Figure C5 of Appendix C. In aggregate, the average p...
AI summary NSPI's 2024 load forecast shows under-forecasting trends, with residential load growth driven by EVs and electrification. The forecast's accuracy is questioned due to consistent under-forecasting, while sectoral energy use trends highlight residential dominance. Synapse Energy Economics provides analysis on these issues.
in terms of energy, driven by electric vehicles, new customers, and building electrification. The commercial forecast increases at a more modest level, and the industrial load shows a small decrease. Table 3. Sector energy requirements (GW...
AI summary The text outlines energy forecasts for residential, commercial, industrial, and municipal sectors, noting slight increases and decreases. It highlights DSM's projected role in reducing 2034 energy use by 699 GWh (5.6%) through demand-side management initiatives.
24.7 51% 2033 71.3 43.4 7.7 31.7 28.2 39.6 22.9 51% 2034 69.1 44.0 7.8 30.7 28.6 38.4 23.2 51% Source: Synapse from Figure 35 from 2024 Load Forecast Recommendations and Considerations We ask that NSPI explore the benefits of increasing DS...
AI summary The document references a 2024 load forecast and recommends NSPI increase DSM levels. It also outlines Board directives from Matter 11108, including implementing IRP, AMI, and reviewing carbon emission assumptions.
tial sales estimate. Both these values are presented in the same row of the “Residential Load – Post Regression” table in NSPI’s Appendix B and should be calculated consistently or labeled clearly. 10 The residential statistical model also...
AI summary The text discusses NSPI's residential load forecasting models, including adjustments for post-pandemic work-from-home trends and regression coefficients for the 2023 and 2024 forecasts. It notes a decline in the pandemic's impact on residential load, with projected effects of 150 GWh (2023) and 100 GWh (2024). Commercial and industrial models use different economic indicators, with industrial models using longer regression timescales for better statistics.
ilding size. The major change drivers for XHeat are electric (resistance) heat, heat pumps, and, to a lesser extent, secondary heat. The net change over the forecast period is a 12.5 percent increase. The XCool variable is the product of t...
AI summary The document details load forecast variables XHeat, XCool, and XOther, driven by factors like heating technologies, cooling saturation, and appliance efficiency. XHeat increases 12.5%, XCool surges 57.8% due to heat pump cooling, while XOther declines 2.1% from reduced lighting and TV use. Residential energy use is 45% heating, 4% cooling, 53% other, with existing customers seeing 5.6% higher heating loads over the forecast period.
rs, average heating load increases by 5.6 percent, average cooling load increases by 2.2 percent, and the average load associated with other end uses increases by 1.1 percent over the forecast period. The output of the SAE model is an aver...
AI summary The text outlines projected load increases for residential heating, cooling, and other end uses, and describes NSPI's method for forecasting residential consumption using the SAE model, including adjustments for new customers, EV load, PV generation, RTR sales, and DSM impacts.
N-9Rebuttal Evidence - NSPI
4 passages
Nova Scotia Utility and Review Board IN THE MATTER OF The Public Utilities Act, R.S.N.S. 1989, c.380, as amended M11689 2024 Load Forecast Report NS Power Rebuttal Evidence September 6, 2024 NON-CONFIDENTIAL 2024 Load Forecast Report Rebut...
AI summary NS Power submitted a rebuttal to the 2024 Load Forecast Report under the Public Utilities Act, R.S.N.S. 1989, c.380, as amended. The document is part of regulatory proceedings (M11689) and addresses energy usage forecasting methodologies.
1 the 2024 Load Forecast report, this is an input to the forecast. Other than household size, 2 demographics are not taken into account explicitly, but the impact of any other changes in the 3 underlying demographics (average age for insta...
AI summary The Board recommends NSPI reassess its load forecast model's treatment of work-from-home behavior and household demographics, and address sensitivities in EV/solar penetration and hybrid heating impacts. NS Power acknowledges the need to re-evaluate the model's statistical validity but notes current limitations in data variables.
asis for the planning and 4 overall operating activities to serve customer load.” 16 Despite year-over-year variances from load 15F 5 forecast to load actuals, the load forecast continues to provide a reliable basis on which to plan and 6...
AI summary The document discusses the reliability of load forecasts despite variances, emphasizing sensitivity analysis over scenario planning. It requests NSPI to assess solar and DSM impacts on the Large General Service forecast and industrial electrification effects. NS Power notes existing DSM inclusion and solar impact assumptions, with future updates if projects are identified.
ure, seeking testimony from 29 NS Power and Eastward Energy, and invite comments from other key stakeholders, 30 including those involved in the propane and fuel oil markets. 33 31 31 Consumer Advocate Evidence, 2024 Load Forecast Report (...
AI summary The Consumer Advocate submitted evidence related to the 2024 Load Forecast Report (M11689), seeking testimony from NS Power and Eastward Energy while inviting stakeholder input, particularly from propane and fuel oil market participants.
94266NSUARB (NSPI) IR-1 to IR-26
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Document: 313458 Date Filed: 05/28/24 UARB Page 1 1 Request IR-1: 2 Figure 3: Historic and Forecast Net System Requirement and System Peak shows that System 3 Peak growth from 2023 to 2024F is -3.7% and the NSR growth from 2024F to 2025F i...
AI summary The document contains four requests questioning NS Power's load forecasting methodology, including discrepancies in NSR and system peak trends, HDD/CDD anomalies in summer months, and changes in forecasting equations. It challenges NS Power's assumptions about load growth, climate trends, and the impact of cooling technologies on energy demand.
discuss. 26 27 Request IR-4: 28 In Figures 7 and 8, the values applied in the equations and the resulting R2 have changed from 29 the 2023 Load Forecast Report. 30 a) Please explain the changed values in the equation. 31 b) Please briefly...
AI summary Request IR-4 seeks clarification on changes in equations and R2 values from the 2023 Load Forecast Report, specifically in Figures 7 and 8. The request asks for an explanation of altered equation values and a brief discussion on the impact of the changed R2 and model fit.
Document: 313458 Date Filed: 05/28/24 UARB Page 2 1 Request IR-5: 2 Page 23 of the Report indicates that NS Power expects Nova Scotia’s annual population growth 3 peaked in 2023. 4 a) Why does NS Power consider that the trend of population...
AI summary The document contains requests for clarification on NS Power's population growth projections, housing forecast adjustments, and changes in economic driver data. Questions focus on alignment with provincial targets, data sources, and impacts of housing initiatives on energy demand forecasts.
Industrial Electrification Forecasts (cumulative) present values that 31 are different from the 2023 Load Forecast Report. Please explain the factors that have changed 32 from the 2023 report, resulting in lower estimates.
AI summary The text requests an explanation for discrepancies between the 2023 Load Forecast Report and updated Industrial Electrification Forecasts, specifically why the latter presents lower estimates. It seeks clarification on factors contributing to the change in projected values.
recasts (cumulative) present values that 31 are different from the 2023 Load Forecast Report. Please explain the factors that have changed 32 from the 2023 report, resulting in lower estimates.
AI summary The text requests an explanation for discrepancies between cumulative present value estimates and the 2023 Load Forecast Report, specifically asking to identify factors causing lower estimates. The focus is on changes in load forecasting assumptions or data since 2023.
Document: 313458 Date Filed: 05/28/24 UARB Page 5 1 Request IR-17: 2 Page 52 of the Report discusses the price impact to sales through imposed price elasticities and 3 explains that the SAE models use a price elasticity of -0.15. In matter...
AI summary The UARB requests clarification from NS Power on three issues: (1) why different price elasticities were not applied to rate classes despite evidence from Appendix C; (2) discrepancies in population growth forecasts between the 2023 Load Forecast Report and the Conference Board of Canada; and (3) the basis for the structural index in the Report. These questions challenge NS Power's modeling approaches and data reconciliation.
Document: 313458 Date Filed: 05/28/24 UARB Page 6 1 Request IR-21: 2 Section 6.0 examines the Commercial Sector and indicates that a detailed breakdown of the two 3 commercial SAE models are in Attachments 6 and 7. Page 65 explains that th...
AI summary The document contains five requests (IR-21 to IR-25) questioning NS Power's modeling assumptions, including outdated economic data, NSR trends, RTR impact, heating load forecasts, and data discrepancies. Requests focus on model accuracy, forecasting methodology, and alignment with current economic and energy trends.
94285BCC-Synapse (NSPI) IR-1 to IR-54
8 passages
Date Filed: May 29, 2024 Synapse (NSPI) Page 1 of 24 1 Request IR-1: 2 Report Tables 3 a. Please provide in electronic spreadsheet format all tables and graphs with identification of 4 the data source(s) that appear in the load forecast re...
AI summary The document outlines requests for electronic spreadsheet data, including load forecasts, historical sales data, and billed versus accrued sales comparisons. It specifies detailed data requirements for customer sales, system load, and unmetered sales, emphasizing transparency and accuracy in reporting.
ear. 28 b. The report notes that it uses monthly billed sales data from January 2014 to 29 December 2023 for the residential and commercial energy forecasts, and sales data from 30 January 2014 to December 2023 for Small Industrial, and fr...
AI summary The document requests clarification on data periods used for energy forecasts (residential, commercial, and industrial sectors) and details on HDD/CDD calculation methodologies, including temperature data and spreadsheet formats for analysis. It also seeks explanations on how internal and solar heat gains influence these calculations.
r the same period. 14 d. Please provide the calculations used to construct the data values in Figure 7: HDD Trend 15 from the Historic Annual HDD shown in Figure 6. Please identify the years represented 16 on the x-axis for Figure 7. 17 e....
AI summary The text contains a series of data requests related to heating degree days (HDD), cooling degree days (CDD), economic models, and housing completions. It asks for calculations, spreadsheet data sources, and explanations of variables like work-from-home trends, with references to prior regulatory decisions.
Date Filed: May 29, 2024 Synapse (NSPI) Page 3 of 24 1 term,” please discuss in detail any alternatives to housing completions considered and the 2 relative merits of each alternative considered. 3 d. Regarding Figure 16 and the historical...
AI summary The document outlines regulatory requests for clarifications on population projections, economic drivers for industrial/commercial sectors, inflation adjustments, and data sources for residential energy use. Questions focus on forecasting methodologies, economic scenario selection, and data validation.
Date Filed: May 29, 2024 Synapse (NSPI) Page 10 of 24 1 Introduction (Section 2.0, citing to Board Decision concerning 2023 Load Forecast). Please 2 explain in detail how NSPI has addressed the Board’s direction to include/address each of...
AI summary The Board requests NSPI to address specific aspects in its 2024 Load Forecast, including IRP outcomes, carbon emission assumptions, historical load analysis, elasticity evaluation from the TVP Pilot (M11267), and residential model robustness. It also inquires about providing multiple forecasts based on the IRP.
l DSM Savings provide in Figure 35 33 relative to the same forecast provided in the 2023 Load Forecast Report, and please 34 provide a narrative explanation of any such changes. 35
AI summary The text requests a comparison of DSM Savings in Figure 35 to the 2023 Load Forecast Report, seeking a narrative explanation for any discrepancies. This focuses on demand-side management program outcomes relative to energy usage forecasts.
b. Please provide the source data and calculations behind the results in Figure 37. 25 c. The report states concerning the COVID-19 variable that, “The impact of the variable to 26 the Residential forecast is approximately +100 GWh in 2024...
AI summary The text requests clarification on energy forecasting methodologies, specifically the impact of the COVID-19 variable on residential sales, the basis for expecting its decreasing magnitude, and changes in econometric approaches since prior forecasts. It seeks source data, interpretation of modeled effects, and analysis supporting future expectations.
lease explain and quantify the impacts of COVID on the 2022 and 2023 loads. 27 b. Please explain and quantify the ongoing effects of COVID in the commercial forecast. 28 c. Please explain and quantify the specific reasons for the differenc...
AI summary The text requests Nova Scotia Power (NSP) to explain and quantify the impacts of COVID-19 on 2022/2023 load forecasts, ongoing effects in commercial forecasts, and reasons for discrepancies between current and prior forecasts, including reduced sales growth projections.