N-12022 Load Forecast Report - Redacted
6 passages
1 TABLE OF CONTENTS 2 3 1.0 Executive Summary ............................................................................................................. 7 4 2.0 Introduction .................................................................
AI summary The text is a table of contents from a regulatory proceeding document, outlining sections such as forecasting approach, historical energy data, weather, economic information, price data, and sector-specific analyses (residential, commercial). It structures the report's content without discussing specific claims or arguments.
e Assumptions and Load/Peak Modeling Results ................................ 43 30 Figure 28: EV Impact to Energy and Peak Forecasts (cumulative) .............................................. 45 DATE: April 29, 2022 Page 3 of 98 REDACTED...
AI summary The 2022 Load Forecast Report discusses assumptions and load/peak modeling results, including redacted sections and a figure analyzing EV impact on energy and peak forecasts. The document is dated April 29, 2022, and is part of a regulatory proceeding.
od 19 January 2012 to December 2021. The average temperature continues to show a warming 20 trend: the 30-year average annual HDD is 3,924 while the 10-year average is 3,786. 21 NSUARB that if no electricity is sold to a customer under the...
AI summary The document discusses climate trends affecting heating degree days (HDD) and cooling degree days (CDD) from 2012–2021, noting a warming trend with declining HDD and increasing CDD. It also references a regulatory requirement for Licensed Retail Suppliers to apply for licence continuation if no electricity is sold by December 31, 2024 (M10293).
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.
9 -12 evening - December 16 2016 98 2,013 2,111 4.8 -14 weekday evening - December 28 2017 67 1,951 2,018 -4.4 -13 weekday evening (between holidays) - January 7 weekend 2018 80 1,993 2,073 2.7 -12 evening - February 27 2019 111 1,949 2,06...
AI summary The text presents a series of data points over several years, including dates, temperatures, and numerical values that may relate to energy usage or demand patterns, with notes indicating specific conditions such as holidays or lighting loads.
Figure C4: Energy Forecast Accuracy NSR less mills Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast Forecast for: for: for: for: for: for: for: for: for: for: Issued 2012 2013 2014 2015 2016 2017 20...
AI summary Figure C4 presents energy forecast accuracy data over multiple years, showing the difference between forecasts issued in various years and actual values for each subsequent year, measured in NSR less mills.
N-2NSPI (CA) RIR-1 to RIR-17 - Redacted
23 passages
6 Response IR-1: 27 28 (a) Confirmed. Weather (normal) and economics are the only uncertainties considered in 29 Appendix D scenario analysis using Monte Carlo simulations. 30 Date Filed: July 8, 2022 NSPI (CA) IR-1 Page 1 of 2 REDACTED (C...
AI summary NSPI confirms that weather and economic factors are the primary uncertainties in its 10-year energy forecast, using Monte Carlo simulations. Historical data variability is deemed insufficient for scenario analysis, and warming trends are integrated into the 'Model' variable rather than applied post-hoc.
29 coincident peak time of a weekday evening in January at hour ending 1800, so the 30 difference between the E3 models would be 0.6 kW/vehicle. Not all of the charging will Date Filed: July 8, 2022 NSPI (CA) IR-4 Page 1 of 2 REDACTED (CON...
AI summary NSPI acknowledges challenges in managing EV charging demand during peak hours, noting a 0.6 kW/vehicle difference in peak load scenarios. Temperature impacts EV efficiency and heating/cooling demands, though traffic data analysis for system peaks remains unreviewed. Only 70% of EVs are managed off-peak, with 30% remaining unmanaged.
nd Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL
AI summary The document references a 2022 load forecast report (NSUARB M10569) and NSPI's responses to information requests from the Consumer Advocate. It highlights regulatory proceedings involving demand forecasting and stakeholder engagement in utility rate matters.
mVarsNew.Cool_Var 0.830 0.399 2.078 4.02% mVarsNew.Heat_Var 1.375 0.104 13.276 0.00% Date Filed: July 8, 2022 NSPI (CA) IR-7 Page 1 of 3 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast R...
AI summary The document references a 10-Year Energy and Demand Forecast from NSPI's 2022 Load Forecast Report (NSUARB M10569), alongside NSPI's responses to Consumer Advocate information requests. It includes technical variables and a NON-CONFIDENTIAL designation.
and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL
AI summary The document references the 2022 Load Forecast Report (NSUARB M10569) and NSPI's responses to Consumer Advocate information requests. It highlights demand forecasting and stakeholder engagement processes related to energy planning and regulatory transparency.
0.973 AIC 7.870301 BIC 8.241966 F-Statistic #NA Prob (F-Statistic) #NA Log-Likelihood -626.49066 Model Sum of Squares 9,931,770.617 Sum of Squared Errors 240,656.468 Mean Squared Error 2,314.00450 Std. Error of Regression 48.10410 Mean Abs...
AI summary The document includes statistical data from a model analysis and references NSPI's responses to consumer advocate information requests, specifically the 10-Year Energy and Demand Forecast (2022 Load Forecast Report) under NSUARB matter M10569. The content pertains to forecasting methodologies and energy usage patterns.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-8: 2 3 Reference Report p. 59: “The non-weather variance in 2021 is mainly related to an inc...
AI summary NSPI responds to a consumer advocate's query about factors influencing new customers in Nova Scotia's 2022 Load Forecast Report. NSPI states there is no analysis linking new customers to pandemic-driven migration, notes population growth since 2016, and acknowledges no concrete policies for affordable housing. The response also addresses residential model accuracy and commercial model considerations.
(b) No. Both provincial and municipal governments have discussed targets related to 29 affordable housing and population growth, but no concrete policies or programs have been Date Filed: July 8, 2022 NSPI (CA) IR-8 Page 1 of 2 REDACTED (C...
AI summary The response addresses housing policy gaps, noting no concrete programs exist for affordable housing despite discussions. Energy load forecasting uses billing data for new homes, assuming higher efficiency. Population trends are modeled indirectly through economic variables like GDP and employment.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-9: 2 3 Reference Report p. 59: “The COVID-19 impact to the Residential forecast is approxima...
AI summary NSPI clarifies that the 'impact' of COVID-19 on the 2022 residential demand forecast refers to the load variable in the model, not an analysis. No additional analysis was conducted, and none is planned. The response relates to the 2022 Load Forecast Report (NSUARB M10569).
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-10: 2 3 Reference Report p. 71: “Sales in this class have been flat for the last 10 years an...
AI summary NSPI responds to a consumer advocate request regarding the 2022 Load Forecast Report, citing the Conference Board of Canada's economic forecasts for small industrial class sales growth. The response outlines reliance on manufacturing GDP data and references Figure 19 of the report for updated forecasts.
the data series. The series is based on the 29 Conference Board of Canada’s February 5-year forecast plus their 20-year forecast produced 30 in January for the years beyond 2026. Date Filed: July 8, 2022 NSPI (CA) IR-10 Page 1 of 2 REDACTE...
AI summary NSPI provides a 10-year energy and demand forecast based on Conference Board of Canada economic projections, noting historical alignment between manufacturing GDP and sales trends. NSPI asserts no material changes are anticipated in the forecast period.
nd Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests REDACTED 1 Request IR-11: 2 3 With reference to the Report pp. 73-74: “One customer makes up over [redacted] of sales 4...
AI summary NSPI responds to Consumer Advocate information requests regarding the 2022 Load Forecast Report, explaining that mid-year data is not included in annual reports but provides requested sales and demand data in attachments. The responses address specific queries about customer sales trends and peak demand metrics.
NSPI (CA) IR-12 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 LFR CA IR-12 Attachment 1 Page 1 of 1 Jan Feb Mar Apr May Net System Requirement (GWh) 1,242 1,096 1,091 913 836 System Peak (MW) 2,216 2,112 2,024 1,720 1,422 RE...
AI summary The document presents a 10-year energy and demand forecast from NSPI's 2022 Load Forecast Report (NSUARB M10569), including monthly net system requirements and system peak data. It references NSPI's responses to Consumer Advocate information requests, highlighting energy usage patterns and forecasting methodologies.
1 Request IR-13: 2 3 Reference NS Power’s 2021 Rebuttal Evidence (M10109), p. 10, where NS Power 4 acknowledges the CA’s comment that “Data on weather circumstances other than 5 temperature is also available,” but does not appear to respon...
AI summary The request challenges NS Power’s reliance on temperature as the sole weather factor in load forecasting, seeking evidence for this claim and data on other variables like wind speed, precipitation, and cloud cover. It also asks whether these variables are subjective or objective and their impact on forecasts.
temperature (and 4 likely lagged temperature) is the predominant driver, so the impact of other factors may 5 not be statistically significant when combined with temperature. Date Filed: July 8, 2022 NSPI (CA) IR-13 Page 3 of 3 REDACTED (C...
AI summary The analysis highlights temperature (and likely lagged temperature) as the primary driver of energy demand, suggesting other factors may not be statistically significant when combined with temperature. The text references NSPI's 10-Year Energy and Demand Forecast (2022 Load Forecast Report) and responses to consumer advocate information requests.
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 NSPI's responses to the Consumer Advocate's information requests regarding the 2022 Load Forecast Report, focusing on weather-normalized sales, peak load calculations, methodology documentation, and data for Figure 60. The request includes detailed workpapers and explanations for adjustments in load forecasting.
used to construct Figure 60. 27 Date Filed: July 8, 2022 NSPI (CA) IR-14 Page 1 of 4 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Ad...
AI summary NSPI is responding to the Consumer Advocate's information requests regarding its 10-year energy and demand forecast, part of the NSUARB M10569 proceeding. The forecast is based on the 2022 Load Forecast Report.
1 Response IR-14: 2 3 (a) Weather normalized (WN) sales and net system requirement are provided in the figure 4 below: 2012 2013 2014 2015 2016 2017 2018 2019 2020 2021 WN Sales 9,635 10,362 10,352 10,318 10,023 10,136 10,419 10,262 10,146...
AI summary The response details weather-normalized sales and net system requirements from 2012 to 2021, explaining that weather-adjusted actuals are not used in forecasts but for variance analysis. Forecast models assume normal weather, using regression with HDD/CDD values and day-of-week binaries to estimate baseload and temperature-dependent load.
values by month. Binaries are added for day of week. The baseload is estimated by a 14 constant, with the other variables accounting for the temperature dependent load. 15 Date Filed: July 8, 2022 NSPI (CA) IR-14 Page 2 of 4 REDACTED (CONF...
AI summary NSPI submitted a 10-Year Energy and Demand Forecast (2022 Load Forecast Report) as part of NSUARB M10569, responding to Consumer Advocate information requests. The forecast models load using a constant baseload and temperature-dependent variables, with data analyzed by month and day-of-week binaries.
degree since 2016. The adjustment for the morning 20 peak in 2019 in Figure 60 was inadvertently omitted from the Report and a copy of the 21 revised figure is provided below. 22 Date Filed: July 8, 2022 NSPI (CA) IR-14 Page 3 of 4 REDACTE...
AI summary The document discusses adjustments to energy demand forecasts, including a 2019 morning peak correction and 2021 weather-adjusted sales data. NSPI explains the 2019 adjustment as reflecting differences between morning and evening peak loads, not solely lighting. 2021 data shows actual and weather-adjusted sales across residential, commercial, industrial, and other sectors.
February-21 February Normal Total Load Load Load Heating Actual Load from Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 Feb HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day...
AI summary The document presents a table with load data for February, including actual load, load from HDD0, HDD13, and comparisons from previous days and months. The data includes total heating load, load from specific days, and load from lag periods, indicating an analysis of energy consumption patterns.
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 presents 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 be related to energy usage patterns over a specific time period, possibly for regulatory analysis or planning purposes.
Avg Avg Avg Date Month Day Prior Year Month Day HDD0 HDD13 CDD18 Variable Coefficient StdErr T-Stat P-Value Avg HDD18 Actuals HDD0 HDD13 CDD18 CONST 19044.519 56.624 336.331 0.00% Constant term 1-Jan-00 1 1 3 14.8 0 19.8 30-Dec 12 30 2.29...
AI summary The text presents statistical data with coefficients, standard errors, t-statistics, and p-values related to heating and cooling degree days (HDD0, HDD13, CDD18) over various dates, indicating analysis of energy usage patterns and their correlation with temperature metrics.
N-3NSPI (E1) RIR-1 to RIR-12
5 passages
fication rebates and 27 funding programs to offset capital investment. 28 29 (iii) Smart Grid Nova Scotia (M10176): A four-year pilot program focused on studying 30 the effects posed by distributed energy resource (DER) penetration on the...
AI summary The text references the Smart Grid Nova Scotia pilot program (M10176), which studies the impact of distributed energy resources (DER) on the electrical grid, and NSPI's 10-Year Energy and Demand Forecast (NSUARB M10569). These initiatives address grid modernization and energy forecasting, supporting DER integration and long-term planning.
mand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to EfficiencyOne Information Requests NON-CONFIDENTIAL
AI summary The document references the 2022 Load Forecast Report (NSUARB M10569) and NSPI's responses to EfficiencyOne's information requests. It highlights regulatory proceedings involving load forecasting methodologies and data disclosure processes.
l General Intensities and 2022 LFR 28 Attachment 03 General Intensities, Shares tab. 29 (c) The trajectories have been calibrated to show similar increases over the forecast period. Date Filed: July 8, 2022 NSPI (E1) IR-8 Page 1 of 1 10 -...
AI summary The document references a 10-Year Energy and Demand Forecast from NSPI's 2022 Load Forecast Report (NSUARB M10569), including responses to EfficiencyOne's information requests. It discusses general intensities and load forecast trajectories calibrated for similar increases over the forecast period.
is less than 100%, what other types of back-up heating are 27 expected to be in place for heat pumps in 2050, and what percent of the market are 28 they expected to serve? 29 Date Filed: July 8, 2022 NSPI (E1) IR-9 Page 1 of 4 10 - Year En...
AI summary NSPI responds to EfficiencyOne's questions about heat pump backup systems, modeling efficiency tiers (Base, Mid, Best in Class) with corresponding COPs. The analysis includes climate change impacts on heating/cooling degree days and low-GWP refrigerant transitions, though specific technologies are not detailed.
of the forecast it was assumed that E1’s proposed demand response measures 16 are incorporated into the larger demand response program that is being developed as part of the 17 IRP Action Plan. Date Filed: July 8, 2022 NSPI (E1) IR-11 Page...
AI summary NSPI incorporates E1's proposed demand response measures into the larger demand response program under the IRP Action Plan, as part of the 10-Year Energy and Demand Forecast (NSUARB M10569). This relates to NSPI's responses to EfficiencyOne's information requests.
N-4NSPI (NSUARB) RIR-1 to RIR-36
12 passages
10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-1: 2 3 With reference to the 2020 Load Forecast Decision Letter (M09707), dated Oc...
AI summary NS Power's 2022 Load Forecast Report addresses the ongoing impact of the COVID-19 pandemic on electricity demand, adjusting the COVID-19 variable to reflect reduced work-from-home effects. The Board directed consideration of near-term and long-term pandemic impacts on electricity sales, with NS Power assuming continued hybrid work models will influence load patterns.
nergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL
AI summary NSPI provided responses to NSUARB information requests regarding the 2022 Load Forecast Report, focusing on energy and demand forecasting. The document is marked non-confidential and relates to regulatory proceedings involving NSPI and NSUARB.
nergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL
AI summary NSPI provided responses to NSUARB information requests regarding the 2022 Load Forecast Report, focusing on energy and demand forecasting. The document is marked non-confidential and relates to regulatory proceedings involving NSPI and NSUARB.
ment, assumptions 26 on average vehicle characteristics (fuel consumption, powertrain size, 27 battery size, etc.) are used to develop a representative model of vehicles 28 within the segment. Additional assumptions on utilization (e.g. di...
AI summary The analysis uses average vehicle characteristics and utilization assumptions to model vehicle costs and total cost of ownership (TCO) across powertrain segments. Nova Scotia-specific inputs were sourced from the 2021 and 2022 Load Forecast Reports, including Synapse IR-9 Attachment 1 and NSUARB M10569.
ergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL
AI summary NSPI provided responses to NSUARB information requests regarding the 2022 Load Forecast Report, focusing on energy demand projections and regulatory compliance under the Nova Scotia Utility and Review Board proceeding (M10569).
88 2029 0.8 1.2 34460.2 42648.5 3332.1 483.3 32.2 1.7 0.8 1.2 34093.9 42881.5 3241.4 483.8 33.7 1.7 1960 39640 450 19678 2030 0.7 1.1 35325.6 43094.8 3365.3 484.2 32.3 1.7 0.7 1.1 34950.1 43330.2 3273.7 484.7 33.8 1.8 1824 40057 451 19775...
AI summary The text presents a 10-year energy and demand forecast (2022 Load Forecast Report, NSUARB M10569) and references NSPI's responses to NSUARB information requests. The table includes numerical data spanning 2029–2032, likely related to energy metrics and financial figures.
rgy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Date Filed: July 8, 2022 NSPI (NSUARB) IR-4 Page 2 of 2 10 - Year Energy and Demand Forecast (2022 Load Fo...
AI summary NSPI submitted a 10-year energy and demand forecast (2022 Load Forecast Report) in response to NSUARB information requests, marked as non-confidential. The document outlines NSPI's approach to energy and demand planning for regulatory review.
referenced 27 above, while 2021 differs. Stats Can does make periodic adjustments to historic data, but 28 the forecast inputs for economics were frozen as of February 2022. 29 Date Filed: July 8, 2022 NSPI (NSUARB) IR-5 Page 1 of 2 10 - Y...
AI summary NSPI uses 2013 as the base year for calibrating US EIA intensities to Nova Scotia due to limited provincial commercial energy data, relying instead on employment data from NRCan. Forecast inputs were frozen as of February 2022.
ergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-6: 2 3 With reference to Section 4.4 End-Use Intensity Trends, page 35 of 98, the application...
AI summary NSUARB requested details on how EIA data was calibrated for the SAE model in the 2022 Load Forecast Report. NSPI responded by directing to specific attachments containing EIA data, calculations, and formulas used in the forecast, emphasizing year-over-year changes for efficiency and share estimates.
ergy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL 1 Request IR-9: 2 3 With reference to Section 4.4 End-Use Intensity Trends, page 37 of 98, the application...
AI summary NSPI explains discrepancies between E3 and NS Power models in load forecasts, attributing differences to data approaches: E3 uses building-level heating demand data, while NS Power aligns with NRCan's Atlantic province-wide data. Near-term intensity trends are similar, but long-term impacts of switching to electric heating diverge.
y and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL
AI summary This document outlines NSPI's responses to information requests from the NSUARB regarding the 2022 Load Forecast Report. It is part of a regulatory proceeding and includes non-confidential information.
rgy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to NSUARB Information Requests NON-CONFIDENTIAL Overall % Overall Intensity Year Saturation (kWh/household) 2016 59 1,358 2017 60 1,379 2018 62 1,411 2019 6...
AI summary The document provides an energy and demand forecast from 2016 to 2032, highlighting increasing electricity saturation and intensity. A change in data series from Natural Resources Canada (NRCAN) affected the hot water heater consumption values, with a notable drop in the calibration value from 2.32 PJ in 2021 to 2.16 PJ in 2022, though overall growth trends remained similar.
N-7Refiled NSPI (CA) RIR 1 to RIR-17 - Redacted
15 passages
6 Response IR-1: 27 28 (a) Confirmed. Weather (normal) and economics are the only uncertainties considered in 29 Appendix D scenario analysis using Monte Carlo simulations. 30 Date Refiled: July 22, 2022 NSPI (CA) IR-1 Page 1 of 2 REDACTED...
AI summary The response confirms that weather and economic factors are the sole uncertainties considered in Appendix D's Monte Carlo simulations for the 10-Year Energy and Demand Forecast (NSUARB M10569). It references NSPI's responses to consumer advocate information requests.
the impact of the trend variable is a reduction of 59 GWh in the Residential class (around 20 1 percent by 2032) and 16 GWh in the Commercial class (around 0.5 percent by 2032). Date Refiled: July 22, 2022 NSPI (CA) IR-1 Page 2 of 2 REDACT...
AI summary The text outlines projected energy use reductions: 59 GWh (1%) in residential and 16 GWh (0.5%) in commercial sectors by 2032. It references NSPI's 10-Year Energy and Demand Forecast (NSUARB M10569) and redacted consumer advocate responses.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL
AI summary The document references NSPI's responses to Consumer Advocate information requests related to the 2022 Load Forecast Report, with the matter labeled as NSUARB M10569. The content is marked as non-confidential and pertains to demand forecasting analysis.
nd Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL
AI summary The document references the 2022 Load Forecast Report (NSUARB M10569) and NSPI's responses to information requests from the Consumer Advocate. It pertains to demand forecasting and regulatory proceedings involving NSPI and the NSUARB.
mVarsNew.Cool_Var 0.830 0.399 2.078 4.02% mVarsNew.Heat_Var 1.375 0.104 13.276 0.00% Date Filed: July 8, 2022 NSPI (CA) IR-7 Page 1 of 3 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast R...
AI summary The document includes a 10-year energy and demand forecast from NSPI's 2022 Load Forecast Report (NSUARB M10569) and NSPI's responses to consumer advocate information requests. Filed on July 8, 2022, it contains non-confidential data related to energy usage projections and stakeholder engagement.
0.973 AIC 7.870301 BIC 8.241966 F-Statistic #NA Prob (F-Statistic) #NA Log-Likelihood -626.49066 Model Sum of Squares 9,931,770.617 Sum of Squared Errors 240,656.468 Mean Squared Error 2,314.00450 Std. Error of Regression 48.10410 Mean Abs...
AI summary The text includes statistical analysis results from a 10-Year Energy and Demand Forecast (2022 Load Forecast Report) and references NSPI's responses to the Consumer Advocate's information requests. It contains model metrics and a matter number (NSUARB M10569) related to regulatory proceedings.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-8: 2 3 Reference Report p. 59: “The non-weather variance in 2021 is mainly related to an inc...
AI summary NSPI responds to a consumer advocate's inquiry about factors influencing demand forecasts, noting population growth since 2016, no pandemic-driven migration analysis, and lack of concrete housing policies. The response addresses residential and commercial model assumptions, efficiency in new construction, and forecasted customer growth.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-9: 2 3 Reference Report p. 59: “The COVID-19 impact to the Residential forecast is approxima...
AI summary NSPI clarifies that the 'impact' of COVID-19 on the 2022 residential demand forecast refers to the load variable in the forecast model. No additional analysis of pandemic-related demand impacts was conducted as part of the 2022 forecast, and no further analyses are planned.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-10: 2 3 Reference Report p. 71: “Sales in this class have been flat for the last 10 years an...
AI summary NSPI responds to a consumer advocate request regarding its 2022 load forecast, citing the Conference Board of Canada's economic forecasts as the basis for predicting 0.7% annual growth in small industrial class sales. The response highlights reliance on manufacturing GDP data and requests for updated forecasts or model re-runs.
nd Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests REDACTED 1 Request IR-11: 2 3 With reference to the Report pp. 73-74: “One customer makes up over [redacted] of sales 4...
AI summary NSPI responds to Consumer Advocate information requests regarding sales data for a major customer and mid-year energy demand data from the 2022 Load Forecast Report (NSUARB M10569). NSPI clarifies that mid-year calculations are not included in annual reports but provides Jan-May 2022 energy and peak demand data in Attachment 1.
NSPI (CA) IR-12 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 LFR CA IR-12 Attachment 1 Page 1 of 1 Jan Feb Mar Apr May Net System Requirement (GWh) 1,242 1,096 1,091 913 836 System Peak (MW) 2,216 2,112 2,024 1,720 1,422 RE...
AI summary The document presents monthly energy data (January-May) including Net System Requirement and System Peak, referencing NSPI's responses to the Consumer Advocate's information requests. It cites the 2022 Load Forecast Report (NSUARB M10569) as part of a 10-year energy and demand forecast.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL
AI summary The document references NSPI's responses to Consumer Advocate information requests related to the 2022 Load Forecast Report, with the matter labeled as NSUARB M10569. The content is marked as non-confidential and pertains to demand forecasting analysis.
cover, precipitation and wind speed. 28 (g) Please provide NS Power’s best estimate (quantitative or qualitative) as to the impact 29 of cloud cover, snow cover, precipitation, and wind speed on loads, including peak 30 loads. Date Filed:...
AI summary NS Power responds to a request about weather variables affecting load, referencing a 10-Year Energy and Demand Forecast. They provide a temperature-load correlation (R²=0.8556) and list objective variables from Environment Canada, with precipitation sometimes populated.
may have an impact on loads, but as described in the report temperature (and 4 likely lagged temperature) is the predominant driver, so the impact of other factors may 5 not be statistically significant when combined with temperature. Date...
AI summary The analysis examines the relationship between temperature and daily load, indicating temperature is the primary driver. A regression model (y = -660.44x + 35375, R² = 0.8556) shows strong correlation, suggesting other factors may not significantly impact load when temperature is accounted for.
Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL
AI summary The document references NSPI's responses to Consumer Advocate information requests related to the 2022 Load Forecast Report, with the matter labeled as NSUARB M10569. The content is marked as non-confidential and pertains to demand forecasting analysis.
N-9Evidence - Synapse
4 passages
oad Forecast 6 Energy Forecast In Table 1, we saw the sectorial components of the Nova Scotia load. Here, we will review each of them in sequence, going in the same order as in the forecast report. Major Inputs and Regression Models In add...
AI summary The document discusses Nova Scotia Power's (NSPI) energy forecast methodology, emphasizing economic drivers like household compensation and new construction. It references the Conference Board of Canada's (CBoC) 20-year forecast and notes a 7.3% real-term increase in household compensation and 6.1% growth in new customers. Regression models are used, with a recommendation to annually review driver selection.
trends. The primary change drivers for XOther are water heat (increased electric heater saturation), reductions in lighting use, and miscellaneous. The net effect is to increase XOther by 1.5 percent. From this one can see that there are m...
AI summary The document analyzes residential energy use factors, noting heating (42%), cooling (2%), and other uses (56%) drive average consumption. Forecasts show slight increases from XHeat (-0.4%), XCool (+1.6%), and XOther (+0.9%), with NSPI applying adjustments for new customers, EVs, solar, RTR markets, and DSM savings. Appendix B provides regression model results and adjustments.
egory is based on customer surveys and new customer inquiries. Thus, the methodology is different than for the other sectors and should be considered as an informed estimate rather than a calculation. We note too that the survey of the Lar...
AI summary The industrial energy sales forecast for 2022-2032 incorporates survey data and expansion projections, noting pandemic-driven load reductions and a 3.9% overall increase. The methodology is deemed an estimate due to reliance on customer surveys. Uncertainties include major customer operational changes and unclear DSM effects in the industrial sector, prompting a request for NSPI clarification.
conomic impact variations. Details can be found in Appendix D and generally appear plausible, with temperature being the greatest near-term uncertainty and the economic uncertainty dominating by 2032. The peak load sensitivity used a set o...
AI summary The text highlights the need for a 2032 peak load sensitivity analysis, requests clarification on assumptions in Figure D8, and recommends future analyses incorporating proactive policy actions. It also notes improved alignment between the 2031 forecast and 2020 IRP scenarios.
N-11E1(NSPI) RIR-1 to RIR-2
10 passages
Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document outlines Energy and Demand Forecast responses from E1 to NS Power's information requests, referencing the 2022 Load Forecast Report (M10569). It pertains to energy usage patterns and regulatory data disclosure processes.
Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document outlines Energy and Demand Forecast responses from E1 to NS Power's information requests, referencing the 2022 Load Forecast Report (M10569). It pertains to energy usage patterns and regulatory data disclosure processes.
r Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary E1's responses to NS Power's information requests regarding the 2022 Load Forecast Report (M10569). The document addresses energy and demand forecasting methodologies, highlighting interactions between EfficiencyOne and Nova Scotia Power Incorporated.
Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document outlines Energy and Demand Forecast responses from E1 to NS Power's information requests, referencing the 2022 Load Forecast Report (M10569). It pertains to energy usage patterns and regulatory data disclosure processes.
r Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary E1's responses to NS Power's information requests regarding the 2022 Load Forecast Report (M10569). The document addresses energy and demand forecasting methodologies, highlighting interactions between EfficiencyOne and Nova Scotia Power Incorporated.
Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document outlines Energy and Demand Forecast responses from E1 to NS Power's information requests, referencing the 2022 Load Forecast Report (M10569). It pertains to energy usage patterns and regulatory data disclosure processes.
-Year Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document references the 2022 Load Forecast Report (M10569) and EfficiencyOne's (E1) responses to Nova Scotia Power's information requests. The context involves energy demand forecasting and regulatory transparency in a Nova Scotia proceeding.
ear Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document references the 2022 Load Forecast Report (M10569) and EfficiencyOne's (E1) responses to Nova Scotia Power's (NS Power) information requests. It pertains to energy demand forecasting and regulatory compliance processes.
Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document outlines Energy and Demand Forecast responses from E1 to NS Power's information requests, referencing the 2022 Load Forecast Report (M10569). It pertains to energy usage patterns and regulatory data disclosure processes.
-Year Energy and Demand Forecast (2022 Load Forecast Report) – M10569 E1 Responses to NS Power Information Requests NON-CONFIDENTIAL
AI summary The document references the 2022 Load Forecast Report (M10569) and EfficiencyOne's (E1) responses to Nova Scotia Power's information requests. The context involves energy demand forecasting and regulatory transparency in a Nova Scotia proceeding.
86578NSUARB (NSPI) IR-1 to IR-36
10 passages
M10569 NOVA SCOTIA UTILITY AND REVIEW BOARD IN THE MATTER OF: THE PUBLIC UTILITIES ACT - and - IN THE MATTER OF: NOVA SCOTIA POWER INCORPORATED (NS Power) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) NON-CONFIDENTIAL IN...
AI summary The Nova Scotia Utility and Review Board requests Nova Scotia Power Inc. to address the impact of COVID-19 on future electricity sales in its 10-year energy forecast, referencing a 2020 decision letter (M09707). The request emphasizes considering near-term and long-term effects on electricity demand.
ber 20, 2020, the 3 Board directed NS Power to consider the near-term and long-term effects of COVID-19 on future 4 electricity sales. On pages 59-60 of 98 of the application, NS Power states: 5 The COVID-19 variable that was added in 2020...
AI summary The Nova Scotia Utility and Review Board directed NS Power to assess short- and long-term impacts of COVID-19 on electricity sales. NS Power adjusted the pandemic variable in its forecasts, reducing its impact from 2020 to 2022, assuming hybrid work models would persist. The Board questions whether the modified variable in Appendix B should be applied in future forecasts.
Document: 295519 (P-194) Date Filed: June 9/22 UARB (NSPI) Pg. 4 of 10 1 Request IR-9: 2 With reference to Section 4.4 End-Use Intensity Trends, page 37 of 98, the application states that 3 “E3 saturation estimates had a lower starting poi...
AI summary The UARB requests clarification from NSP regarding model adjustments in load forecasting, discrepancies between E3 and NSP models, and changes in heat pump saturation and intensity figures. Questions focus on model assumptions, forecast revisions, and data alignment across different planning periods.
wer’s application in 24 matter M10109. 25 b) Please explain why the heating intensity and cooling intensity has increased from the 2021 26 forecast provided in Figure 13 of NS Power’s application in matter M10109. 27 28 Request IR-12: 29 W...
AI summary The text requests explanations for increases in heating and cooling intensity forecasts from NS Power's 2021 data in matter M10109 and asks for historical energy usage data from 2016–2021 to clarify projected energy usage trends per house.
31 Please explain why NS Power expects that the energy usage per house will increase over this 32 period? Please expand this table with the actual data for the years 2016 to 2021 included. 33
AI summary The text requests NS Power to explain projected increases in residential energy usage per house and to expand a table with actual data from 2016 to 2021. The focus is on energy usage trends and data transparency.
Document: 295519 (P-194) Date Filed: June 9/22 UARB (NSPI) Pg. 6 of 10 1 i. Please provide a copy of the data used in the mode and the source for driving 2 habits. 3 b) If residential sales are expected to be elevated due to increased work...
AI summary The UARB requests data on residential driving habits, expanded tables for PV impact and electrification forecasts, explanations for price elasticity choices, and reasons for declines in DSM savings forecasts. Requests focus on data transparency, methodological consistency, and alignment with Canadian standards in load forecasting.
Document: 295519 (P-194) Date Filed: June 9/22 UARB (NSPI) Pg. 7 of 10 1 Request IR-23: 2 With reference to Section 5.0 Residential Sector, the application discusses the model used to 3 determine the residential sales forecast. 4 a) Please...
AI summary The UARB requests clarifications on residential electricity sales forecasts, including rationale for excluding substitute prices, multi-unit housing trends, weather-adjusted sales metrics, COVID-19 impact variations, and EV penetration rate assumptions. These requests focus on forecasting methodologies, energy usage patterns, and affordability factors affecting residential sector projections.
hicles available for sale in Nova 27 Scotia. If not, please explain. 28 29 Request IR-27: 30 With reference to Section 5.0 Residential Sector, page 61 of 98, the application states, “Analysis 31 of billing data showed that new single-famil...
AI summary Request IR-27 questions whether billing data used in the analysis comes from AMI meters in Nova Scotia, referencing residential sector energy usage statistics (16,000 kWh/year for single-family homes, 4,860 kWh/year for multi-unit homes).
mall Industrial, page 71 of 98, the application indicates that “sales 28 in this class have been flat for the last 10 years and are expected to grow by 0.7 percent annually” 29 because of economic growth. 30 a) Please explain in detail, th...
AI summary The text raises questions about the anticipated 0.7% annual sales growth for the 'mall Industrial' class despite flat performance over the past decade and a discrepancy between the 2021 Load Forecast (0.6% growth) and the current estimate. It seeks clarification on economic factors driving growth and the basis for the updated forecast.
y 33 over the forecast period, given the 2021 Load Forecast had estimated growth of 0.6 34 percent annually over this period, and yet sales growth has been flat since 2011. 35
AI summary The text highlights a discrepancy between the 2021 Load Forecast projecting 0.6% annual growth over the forecast period and the actual flat sales growth observed since 2011, indicating a potential gap between projected and realized energy consumption trends.
86600Synapse (NSPI) IR-1 to IR-41
5 passages
Document #:296069 Date Filed: June 14, 2022 Synapse (NSPI) Page 1 of 16 1 Questions regarding the NSPI “2022 Load Forecast Report” of April 29, 2022 2 Request IR-1: 3 Report Tables 4 a. Please provide in electronic spreadsheet format all t...
AI summary The Board requests detailed data and clarifications on NSPI's 2022 Load Forecast Report, including spreadsheet formats for tables, historical sales data, and explanations of billed vs. accrued sales differences. The focus is on data transparency and methodology validation for load forecasting.
improve the fit.” Please quantify the nature of the improved 28 fit. 29 c. Please identify the effect if the industrial forecast used the same period as the residential 30 and commercial forecasts (that is, January 2012 to December 2021)....
AI summary The document contains requests for detailed weather data (temperature, HDD/CDD) and methodological transparency related to forecasting, including spreadsheet formats, calculation details, and climate resource citations. It seeks clarification on data sources, time periods, and forecasting approaches for energy demand modeling.
he 2 regression? 3 i. Please provide the inflation adjustments used to convert to constant dollars. 4 j. Regarding economic forecasts, identify the scenario/case used for this analysis and the 5 reasons for choosing it. 6 k. Please indicat...
AI summary The regulatory body is requesting detailed information on inflation adjustments, economic forecasts, data sources, and customer heating trends from Nova Scotia Power. They seek specific data on residential and commercial end-use intensities, adjustments made to align with billing data, and forecasts related to heating and heat pump usage.
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.
r the differences from the 2021 22 forecast. 23 b. Please explain and quantify the factors behind the 0.1 percent growth rate. 24 25 Request IR-24: 26 Other Industrial (Section 7.3). 27 a. Please explain and quantify the specific reasons f...
AI summary The document outlines regulatory requests (IR-24 to IR-27) seeking explanations for forecast discrepancies, load changes, system losses, and net system requirements. It focuses on data validation, reliability of projections, and sector-specific load contributions from industrial, municipal, and other sectors.
86618CA (NSPI) IR-1 to IR-23
10 passages
Date Filed: June 16, 2022 CA (NSPI) Page 1 of 11 1 Request IR-1: 2 3 Reference Report p. 7: “As with any forecast, there is a degree of uncertainty around actual future 4 outcomes. In electricity forecasting, much of this uncertainty is du...
AI summary The document contains regulatory requests (IR-1 and IR-2) questioning NS Power's forecasting methodology, specifically regarding uncertainty analysis, inclusion of warming trends in load forecasts, and clarification of 2021 load forecast timelines. Requests focus on scenario analysis, sensitivity to climate factors, and transparency in energy load projections.
ime, this forecast covers the period of 2022-2032.” 28 29 a. Please clarify when the 2021 load forecasts were finalized. 30 31 b. For the major sources of information (economic inputs, load history, etc.) please clarify 32 the date of the...
AI summary The text contains requests for clarification on load forecasts (2021-2032), data sources used (economic inputs, load history), and geographic load data disaggregation. It seeks details on the Conference Board of Canada's economic data and NS Power's geographic load data availability.
Date Filed: June 16, 2022 CA (NSPI) Page 3 of 11 1 b. Please list the parameters in the end use computation that could “capture DSM”. 2 3 c. Please provide a specific example of the manner in which the end use inputs or 4 parameters could...
AI summary The document contains regulatory requests seeking clarification on DSM parameterization in end-use models, peak model limitations, and pandemic-driven customer growth impacts. It asks NS Power to explain how DSM factors are captured in regression analyses, the significance of parameters in peak models, and whether new customer growth relates to pandemic migration patterns.
Date Filed: June 16, 2022 CA (NSPI) Page 4 of 11 1 Request IR-9: 2 3 Reference Report p. 59: “The COVID-19 impact to the Residential forecast is approximately +100 4 GWh in 2022 …” 5 6 a. Does “impact” refer to an estimated change in deman...
AI summary The document contains three regulatory requests (IR-9, IR-10, IR-11) querying NS Power about demand forecasting impacts from COVID-19, economic forecast sources, and load model updates. Requests focus on clarifying methodology, data sources, and confidence in projected demand growth.
nputs and any other inputs that can be updated? If so, provide the 34 updated forecasts. 35 36 Request IR-11: 37 38 With reference to the Report pp. 73-74: “One customer makes up over [redacted] of sales within 39 this class, and after a d...
AI summary The text requests updated forecasts and specific sales data for a customer whose activity significantly impacts a sales class. It references a report noting the customer's sales recovery in 2021 after declines in 2019-2020, and seeks 2021 sales additions and 2022 YoY comparisons for January-May.
Date Filed: June 16, 2022 CA (NSPI) Page 5 of 11 1 Request IR-12: 2 3 Reference report p. 83 regarding the January 2022 peak, please provide monthly energy and peak 4 demand data for January – May 2022 in spreadsheet format. 5 6 Request IR...
AI summary The text includes two requests: IR-12 seeks monthly energy and peak demand data from January–May 2022, while IR-13 challenges NS Power’s reliance on temperature as the sole weather factor in load forecasting, requesting supporting analyses and data on wind, precipitation, cloud cover, and snow variables from Environment Canada.
cover data variables are available from Environment Canada 29 and whether NS Power views each of those variables as subjective or objective. 30 31 f. Please provide any other available data regarding general trends in cloud cover, snow 32...
AI summary The document requests NS Power to provide data on weather variables (cloud cover, snow cover, precipitation, wind speed) and their impact on load trends, including peak loads. It also asks for weather-normalized sales and requirements, distinguishing between firm and system peak load data.
If both firm and system peak load 42 data are available, please provide both where requested in items b, c, and e. 43 44 a. Please provide weather-normalized sales and requirements. 45
AI summary The text requests provision of firm and system peak load data, along with weather-normalized sales and requirements, as part of a regulatory proceeding. It emphasizes data availability for analysis in items b, c, and e.
in Figure 11. 41 42 b. Please explain how, if at all, each of these trends are reflected in Table A1. In your 43 response, please provide the HDD and CDD values by year. 44
AI summary The text requests an explanation of how specific trends are reflected in Table A1, asking for HDD and CDD values by year. It focuses on analyzing energy usage patterns through temperature-related metrics.
dders in each of 31 January, August, September and October. 32 33 b. Has NS Power identified any drivers (e.g., time spent at home) that would account for 34 any of these variations from the general function of heating, cooling, other appl...
AI summary The text contains questions about NS Power's load forecasts, including discrepancies between past predictions (declining/flat trends) and a new forecast predicting increasing energy demand. It also asks about factors driving variations in energy use patterns across specific months.