CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 14: Commercial Economic Drivers 2
AI summary The text references a redacted section of the 2024 Load Forecast Report, specifically Figure 14, which discusses commercial economic drivers. The content has been marked as confidential and is partially redacted.
ATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 22: Heating Intensity Comparison 2
AI summary The text references a 2024 Load Forecast Report and includes a figure titled 'Heating Intensity Comparison.' However, the content is partially redacted, limiting the availability of detailed information.
y (a measure of 26 whether the vehicle is plugged in and able to charge/discharge). 27 25 Smart Grid Nova Scotia (SGNS) Project Final Report (M11621), March 15, 2024. DATE: April 30, 2024 Page 44 of 100 REDACTED (CONFIDENTIAL INFORMATION R...
AI summary The document references a redacted 2024 Load Forecast Report and mentions the Smart Grid Nova Scotia (SGNS) Project Final Report (M11621), dated March 15, 2024. It includes a redacted section indicating the presence of confidential information.
RMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 42: Illustrative Contribution of Specific End Uses 2 Year HP Heat HP Cool Baseboard Heat Water Heat (GWh) (GWh) (GWh) (GWh) 2024 980 136 1025 816 2025 1067 146 979 831 2026 1142...
AI summary The 2024 Load Forecast Report provides an illustrative breakdown of energy use by end use categories, including heat pump heating and cooling, baseboard heating, and water heating, from 2024 to 2034. The data shows increasing trends in heat pump usage and decreasing trends in baseboard heating.
2024 Load Forecast Report REDACTED 1 Figure 49: Historical and Forecast Annual Small Industrial Sales 2 3 4 5 7.2 Medium Industrial 6 7 Figure 50 depicts historical and projected sales for the Medium Industrial class. Load in 8 this class...
AI summary The 2024 Load Forecast Report discusses historical and projected sales for the Medium Industrial class, noting flat load since 2014, a slight increase from 2019 to 2022, and a projected decline in 2026 due to load migration to the RTR market.
Page 73 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 forecast. Another Large Industrial customer has temporarily reduced load to the point that 2 they have migrated to the Medium Industrial class,...
AI summary The 2024 Load Forecast Report discusses changes in customer load, including a Large Industrial customer temporarily reducing load and migrating to the Medium Industrial class, with expected ramp-up in 2026. There is uncertainty around new facilities and expansions, and past forecasts have been adjusted due to overestimations.
Page 74 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 52: Historical and Forecast Annual Other Industrial Sales 2 3 4 DATE: April 30, 2024 Page 75 of 100 REDACTED (CONFIDENTIAL INFORMATION R...
AI summary The document contains a redacted section of the 2024 Load Forecast Report, which includes historical and forecast data on annual Other Industrial Sales. The report was filed on April 30, 2024, and is part of a larger document spanning 100 pages.
CTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Figure 55: Forecast Components 2 GWh Res Comm Ind Other Losses NSR 2024 Forecast 5,180 3,118 2,267 159 767 11,490 Model 466 352 41 -82 69 986 New Customers 366 32...
AI summary The 2024 Load Forecast Report includes a table showing forecast components for electricity demand across various sectors, including residential, commercial, industrial, and others, as well as adjustments for factors like solar, EV adoption, and demand-side management (DSM). The report also provides a 2034 forecast and highlights the impact of DSM initiatives.
Page 83 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED
AI summary The 2024 Load Forecast Report has been redacted, with confidential information removed. The report likely contains projections and analysis related to electricity demand in Nova Scotia for the year 2024.
Page 87 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 Section 4.4, the EV contribution to peak is expected to be partially mitigated via utility 2 managed charging. The firm peak without EV peak mi...
AI summary The 2024 Load Forecast Report discusses the impact of electric vehicles (EVs) on peak demand, noting that utility-managed charging could mitigate some of the increase. It also highlights the effect of space heating on reducing peak demand. The 2023 system peak was the highest recorded, occurring during extreme cold weather with significant wind speeds, and was partially reduced due to customer interruptions.
22 2024 2023 52.0 3.6% 2,266.5 2,302.1 -35.6 -1.5% 23 24 38 Modeled peak does not include all components, it is based on a regression of the system load less large customers. 39 The 2023 Predicted accrued Peak was adjusted by subtracting a...
AI summary The text discusses the 2024 Load Forecast Report, which includes modeled peak load data and adjustments made to the 2023 predicted peak, such as subtracting 150 MW of lighting from the normalized peak. The report is redacted and confidential.
Page 90 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 End Use Peak Estimates 2 3 While the Load Forecast is a good statistical fit for the historical data, it presents challenges 4 when trying to a...
AI summary The 2024 Load Forecast Report discusses end use peak estimates, noting that while the forecast is statistically accurate, individual end use contributions to peak demand by class are challenging to assess. The report highlights that electric vehicle (EV) contributions to peak demand are expected to increase significantly, while contributions from electric heating sources are projected to decrease.
Page 95 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED 1 system peak (the sum of all customer classes) and then AMI informed load factors are used 2 to disaggregate it into all the classes. In the fut...
AI summary The 2024 Load Forecast Report discusses the use of AMI for more accurate load forecasting, including disaggregation of system peak into customer classes, regional forecasting, and testing end-use sensitivities. It also highlights the potential for electrification to impact different regions differently and the importance of updating end-use assumptions.
-use disaggregation may be used to update/validate end-use 20 assumptions (depending on accuracy per appliance type) and then used to evaluate the 21 impact to the Residential peak. DATE: April 30, 2024 Page 96 of 100 REDACTED (CONFIDENTIA...
AI summary The text discusses the use of disaggregation to update and validate end-use assumptions for residential peak load, referencing the 2024 Load Forecast Report, which contains redacted confidential information.
Page 96 of 100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report REDACTED
AI summary The 2024 Load Forecast Report contains redacted information, indicating that confidential details have been removed. The document is part of a larger proceeding and provides insights into load forecasting for the year 2024.
3 -41.8% 763 11,409 -0.7% 2026 5,146 -1.3% 2,993 -2.8% 2,247 -0.7% 171 84.8% 750 11,306 -0.9% 2027 5,140 -0.1% 3,000 0.2% 2,246 0.0% 211 23.5% 751 11,347 0.4% 2028 5,176 0.7% 3,028 0.9% 2,245 0.0% 212 0.2% 755 11,416 0.6% 2029 5,183 0.1% 3...
AI summary The text presents a table of forecast values for various metrics from 2026 to 2034, including demand, capacity, and other related figures. The table is part of the 2024 Load Forecast Report Appendix A, which provides detailed forecasting data.
x A Page 3 of 3 Appendix A – Forecast Values Table A2: Coincident Peak Demand - 2024 NS Power Forecast Peak Forecast
AI summary The document provides a table titled 'Table A2: Coincident Peak Demand - 2024 NS Power Forecast Peak Forecast' as part of an appendix discussing forecast values. The table likely outlines projected peak demand figures for the year 2024.
weekday 2017 67 1,951 2,018 -4.4 -13 -13 evening (between holidays) - January 7 weekend 2018 80 1,993 2,073 2.7 -12 -13 evening - February 27 weekday 2019 111 1,949 2,060 -0.6 -15 -14 morning (min lighting load) - January 17 weekday 2020 9...
AI summary The text presents data on weekday and holiday load forecast reports (LFR) over several years, including metrics such as demand, load forecast, and variations in load. The data includes specific dates and times, such as evenings and mornings, and highlights fluctuations in demand across different years.
2,485 2,670 1.8 -13 Forecast 2034 147 38 2,542 2,727 2.1 -13 Forecast Page 2 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix B Page 1 of 35 Appendix B – Forecast Model Details 2024 NS Power Load Forecast...
AI summary This section of the 2024 Load Forecast Report Appendix B provides details on the residential average use model, which is defined as a function of heating, cooling, and other uses, along with factors such as energy efficiency savings and the impact of the pandemic.
sEcon is Employment Compensation divided by House Hold population, Price is the price of electricity for the specific customer class. Each accompanied by its own elasticities. Base line year is 2015. OtherIndex is defined as: 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 𝑆𝑆𝑆𝑆...
AI summary The text defines 'OtherIndex' using a formula involving variables like Type, SatyType, EffyType, and EI15Type, which are related to end-use saturation, efficiency, and calibration weights. The baseline year is 2015, and the formula is part of the 2024 Load Forecast Report.
-3.8% 28.3% 0.0% 0.0% 24.5% XCool = Cooling x CoolUseVariable x Coeff x Scaling Factor Small General Input Variables – XOther Intensities Econ + Reg Struct Vent Water Cook Refrig Light Office Misc OtherUse Coeff Scaling Total Heat Var Fact...
AI summary The text provides a formula for estimating the General Service rate class model based on monthly heating and cooling requirements, as well as other use variables. The model incorporates end-use intensity projections, GDP, employment, real price, and monthly heating and cooling degree days.
(241) Change 13.3% -4.1% 8.0% -8.0% -2.7% -7.3% -0.8% Gen Sales = Sales + RTR + EV Load + Solar Load + Hybrid + DSM General Demand Sales –Regression XHeat XCool XOther Binaries ARMA Sales (GWh) 2024 543,197 117,739 1,767,734 (56,741) (6,99...
AI summary The document provides a forecast of general demand sales and input variables for 2024 and 2034, including changes in heating, cooling, and other demand factors. It outlines the calculation methods and the impact of various variables on overall demand.
IAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix B Page 22 of 35 General Demand Input Variables – XCool Intensities Econ + Struct Regression Cooling CoolUse Variable Coefficient Scaling Factor Total Xcool 2024 317,164 1.44 0.698...
AI summary The text provides data on general demand input variables for XCool and XOther from the 2024 Load Forecast Report. It includes values for cooling, CoolUseVariable, coefficients, scaling factors, and total Xcool for the years 2024 and 2034, along with percentage changes.
FIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix B Page 24 of 35 Small Industrial Model Statistics Model Statistics Iterations 1 Adjusted Observations 120 Deg. of Freedom for Error 106 R-Squared 0.829 Adjusted R-Squared 0....
AI summary This section presents statistical and model fit details for the Small Industrial and Medium Industrial load forecasting models. Metrics such as R-squared, adjusted R-squared, AIC, BIC, and others are provided, along with the equation for the Medium Industrial model.
IDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix B Page 30 of 35 Combined Model Statistics Model Statistics Iterations 1 Adjusted Observations 108 Deg. of Freedom for Error 101 R-Squared 0.831 Adjusted R-Squared 0.821 AIC 1...
AI summary The document presents statistical results from a load forecasting model, including metrics such as R-squared, AIC, BIC, and MAPE, which indicate the model's accuracy and fit. The model uses monthly peak demand data and factors like heating, cooling, base load, and wind to forecast long-term system peak demand for accrued classes.
REDACTED 2024 Load Forecast Report Appendix D Page 5 of 9 Appendix D – Forecast Sensitivity Analysis Figure D3: Distribution of Peak (Residential, Commercial and Small and Medium Industrial) 8. From these annual forecast distributions, the...
AI summary The appendix discusses probabilistic load forecasting, focusing on the distribution of peak demand across residential, commercial, and small and medium industrial sectors. It highlights the impact of heating degree days (HDD) on peak demand, noting that monthly HDD has surpassed peak HDD importance in 2025 due to year-long residential heating effects.
Impact of Electrification (MW) 8 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Appendix E Page 9 of 18 Renewable to Retail • RTR participation is expected to start in late 2025 (340 GWh of wind production), with a t...
AI summary The 2024 Load Forecast Report Appendix E discusses the impact of Renewable to Retail (RTR) participation, which is expected to start in late 2025, reducing customer sales by 246 GWh compared to the 2023 forecast. The report outlines expected reductions by customer class from 2025 to 2026.
2024 Load Forecast Report (NSUARB M11689) NSPI Responses to Synapse Information Requests NON-CONFIDENTIAL 1 (d) Please indicate the number of new residential customers from 2024 through 2050 and 2 the breakout of their space heating techno...
AI summary NSPI is responding to Synapse's information requests regarding the 2024 Load Forecast Report. The report includes questions about residential customer growth, heat pump saturation rates, and detailed breakdowns of heating technologies in commercial buildings.
18.1 40.2 17.0 5.4 3.2 2029 20,159 14,322 729 428 35,639 33,586 150 144 33.7 0.95 32 63.7 61 71.4 23.8 54.8 22.3 7.1 4.3 2030 26,451 18,517 900 550 46,419 44,365 195 189 43.9 0.94 42 82.7 80 93.3 31.1 70.1 29.1 9.3 5.5 2031 35,961 24,858 1...
AI summary The text presents a series of numerical data points spanning from 2029 to 2034, likely related to energy forecasting or planning. It includes values for various metrics, but the content is partially redacted, indicating the presence of confidential information. The mention of the '2024 Load Forecast Report Synapse IR-9' suggests a connection to energy load forecasting.
201 220 660 602 46,696 10,042 56,738 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-10 Attachment 1 Page 2 of 2 2022 System Load Commercial Production at Peak Monthly Coincidence Factor Site1 Site2 Site3 S...
AI summary The text presents a table with data related to system load, commercial production at peak, and monthly coincidence factors for various sites. The data includes numerical values and references to the 2024 Load Forecast Report Synapse IR-10 Attachment 1.
tem Load Commercial Production at Peak Monthly Coincidence Factor Site1 Site2 Site3 Site4 Site5 Site6
AI summary The text presents a table with columns including 'tem Load', 'Commercial Production at Peak', 'Monthly Coincidence Factor', and site-specific data (Site1 to Site6). The table appears to be related to energy load and production metrics, though the context and purpose of the data are not explicitly explained.
Heat Heat Heat Cool Cool Cool Other Other Other Intensity Intensity Intensity Intensity Intensity Intensity Intensity Intensity Intensity Heat Share Heat share Heat share Cool Share Cool share 2024 2023 2022 2024 2023 2022 2024 2023 2022 2...
AI summary The text presents data on heat and cool intensity, heat and cool share percentages, and other metrics from 2014 to 2022. It includes yearly values for intensity and share percentages, showing trends over time.
0.768 1.301 0.698 3.182 90.298 1.000 1.000 2034 0.789 1.307 0.698 3.191 91.732 1.000 1.000 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-24 Attachment 1 Page 3 of 3 2014 2015 2016 2017 2018 2019 2020 2021...
AI summary The text includes a table with years from 2014 to 2034 and numerical data, likely related to load forecasting. The document is part of a 2024 Load Forecast Report by Synapse, with a note that confidential information has been redacted.
2024 Load Forecast Report Synapse IR-24 Attachment 1 Page 3 of 3 2014 2015 2016 2017 2018 2019 2020 2021 2022 2023 2024 2025 2026 2027 2028 2029 2030 2031 2032 2033 2034
AI summary The text presents a timeline spanning from 2014 to 2034, likely representing a forecast or planning horizon for a load forecast report. It includes years in sequence, possibly indicating the scope of the analysis or planning period.
2024 Load Forecast Report Synapse IR-37 Attachment 1 Page 1 of 6
AI summary The text references the 2024 Load Forecast Report by Synapse, specifically Attachment 1, Page 1 of 6. It does not provide further details or discussion of the content within the report.
2024 Load Forecast Report Synapse IR-37 Attachment 1 Page 4 of 6
AI summary This document is a page from the 2024 Load Forecast Report, specifically Attachment 1, which is part of Synapse IR-37. The content is currently not visible, but it likely contains data or analysis related to load forecasting.
N REMOVED) 2024 Load Forecast Report Synapse IR-38 Attachment 1 Page 2 of 9
AI summary The document is a page from the 2024 Load Forecast Report by Synapse IR-38, Attachment 1. It provides a portion of the load forecast analysis, though the main content has been redacted or removed.
1,823.81 19,687.61 49,987.17 13,934.37 32,148.65 0.00 15.920 2034 1,808.41 19,510.20 49,206.02 14,037.78 32,034.26 0.00 16.100 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-38 Attachment 1 Page 3 of 9
AI summary The document contains a table with numerical data and a redacted section from a 2024 Load Forecast Report, specifically Attachment 1, Page 3 of 9. The table includes values that may relate to load forecasting, though the exact context is not fully visible due to redaction.
RMATION REMOVED) 2024 Load Forecast Report Synapse IR-38 Attachment 1 Page 5 of 9 Year SmlGenIndices Heating SmlGenIndices Cooling SmlGenIndices Others XHeat XCool XOther Mar 23-Sep Dec 22-Oct May 20 Jun 20 Yr22Plus ARMA
AI summary The text presents a portion of a 2024 Load Forecast Report, including data related to small generation indices for heating, cooling, and other categories, as well as various months and years. The content appears to be part of a technical analysis or modeling effort.
Year SmlGenIndices Heating SmlGenIndices Cooling SmlGenIndices Others XHeat XCool XOther Mar 23-Sep Dec 22-Oct May 20 Jun 20 Yr22Plus ARMA
AI summary The text appears to be a table containing various indices and metrics related to heating, cooling, and other factors, along with abbreviations such as 'XHeat,' 'XCool,' and 'XOther.' The data spans multiple months and years, including 'Mar,' '23-Sep,' 'Dec,' '22-Oct,' 'May 20,' 'Jun 20,' and 'Yr22Plus,' with 'ARMA' listed as a possible reference.
RMATION REMOVED) 2024 Load Forecast Report Synapse IR-38 Attachment 1 Page 7 of 9 Year Regression Coefficients MStructS MStructS MStructSml mlGen.Wt mlGen.Wt Gen.WtXOt MBin.May MBin.Jun2 MBin.Oct MBin.Yr22 2014 Variable XHeat XCool her MBi...
AI summary The text presents a table of regression coefficients from a 2024 Load Forecast Report. It includes variables related to heating, cooling, and various monthly bin coefficients, along with statistical values such as standard error, t-statistics, and p-values for the years 2014 to 2018. This data is used for load forecasting and analysis.
r GenIndices Heating GenIndices Cooling GenIndices Others XHeat XCool XOther Feb 18 May 20 Jun 20 22-Oct 22-Sep Covid 23-May ARMA
AI summary The text presents a table with various indices related to heating, cooling, and other factors, along with dates and an ARMA model. The content appears to be technical data used for analysis, possibly related to energy generation or demand forecasting.
707,162.9 0 0 0 0 0 7.8 0 0 2032 635,007.3 308,981.9 1,140,261.9 912,474.2 205,157.7 1,715,870.2 0 0 0 0 0 7.8 0 0 2033 655,518.5 308,366.4 1,130,058.7 944,862.2 209,211.3 1,716,178.0 0 0 0 0 0 7.8 0 0 2034 676,075.0 307,871.3 1,119,458.2...
AI summary The text presents numerical data related to load forecasting for various years, including details on heat, cooling, and other new loads, along with specific dates and metrics such as ARMA new and total kWh. The data is part of a confidential report, likely related to energy forecasting and planning.
6 148,836.35 1,857,456.36 - - - - - (56,741.28) - - 2,679,690.79 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-39 Attachment 1 Page 5 of 7 Year Regression Coefficients MStructG MStructG MStructGen. en.WtX...
AI summary The text presents statistical data related to load forecasting, including regression coefficients, standard errors, t-statistics, and p-values for various years. It includes a table with technical terms and statistical measures used in forecasting load demand.
Year Month ResEndUse.ResHeat NResEndUse.SmlGenHeat NResEndUse.GenHeat mVars.HeatLoad mVars.Days mVars.Heat_AvgMW mPkDayWthr.PkHDDIdx mVars.Heat_Var 2014 1 295,769.1 12,368.1 80,996.1 389,133.3 31.0 523.0 1.4 744.5 2014 2 273,603.8 11,451.8...
AI summary The text presents a table with data spanning multiple years and months, including various metrics related to residential and non-residential end-use heating, heat load, days, average heat in megawatts, peak heating degree day index, and heat variability. The data appears to be related to energy usage and heating patterns.
Year Month ResEndUse.ResHeat NResEndUse.SmlGenHeat NResEndUse.GenHeat mVars.HeatLoad mVars.Days mVars.Heat_AvgMW mPkDayWthr.PkHDDIdx mVars.Heat_Var 2021 3 311,421.5 14,685.2 75,062.4 401,169.0 31.0 539.2 1.1 587.2 2021 4 218,754.8 10,359.3...
AI summary The text presents a table of data from 2021 and 2022 showing residential and non-residential end-use heating energy consumption, heat load, and related variables across different months. The data includes values for residential and non-residential heating, average heat load, number of days, and other metrics.
Year Month ResEndUse.ResHeat NResEndUse.SmlGenHeat NResEndUse.GenHeat mVars.HeatLoad mVars.Days mVars.Heat_AvgMW mPkDayWthr.PkHDDIdx mVars.Heat_Var 2028 5 184,005.4 8,980.0 41,578.6 234,564.0 31.0 315.3 0.5 143.7 2028 6 81,540.1 3,984.2 18...
AI summary The text presents a table containing energy usage data for residential and non-residential heating across various months in 2028 and 2029, including metrics such as heat load, days, average megawatts, and peak heating degree day index. The data is structured with multiple variables and appears to be related to energy consumption analysis.
Year Month ResEndUse.ResCool NResEndUse.SmlGenCool NResEndUse.GenCool mVars.CoolLoad mVars.Days mVars.Cool_AvgMW mPkDayWthr.PkCDDIdx mVars.Cool_Var 2014 1 - - - - 31.0 - - 2014 2 - - - - 28.0 - - - 2014 3 - - - - 31.0 - - - 2014 4 2.1 0.4...
AI summary The text presents a table with data spanning from 2014, including monthly values for various energy-related metrics such as cooling load, days, average megawatts, and peak cooling degree day index. The data appears to be related to energy usage and load management.
3.4 9.8 30.0 0.0 - - 2026 5 2,158.1 166.7 1,238.7 3,563.5 31.0 4.8 - - 2026 6 17,080.3 1,322.4 9,819.5 28,222.2 30.0 39.2 0.2 5.8 2026 7 69,264.0 5,374.2 39,885.1 114,523.3 31.0 153.9 0.7 110.3 2026 8 82,984.7 6,452.9 47,865.8 137,303.3 31...
AI summary The document presents a table with numerical data spanning multiple years and categories, including load forecasts and related metrics. The data is part of a 2024 Load Forecast Report by Synapse, with some sections redacted due to confidentiality.
179.3 558.0 30.0 0.8 - - 2032 12 - - - - 31.0 - - - 2033 1 - - - - 31.0 - - - 2033 2 - - - - 28.0 - - - 2033 3 - - - - 31.0 - - - 2033 4 8.1 0.6 4.0 12.8 30.0 0.0 - - 2033 5 2,956.1 208.7 1,466.3 4,631.0 31.0 6.2 - - 2033 6 23,415.0 1,655....
AI summary The text presents a table with numerical data, potentially related to energy load forecasts, but the content is partially redacted. The table includes years, numbers, and categories, but the exact context and discussion points are not fully visible due to confidentiality.
Year Month ResEndUse.ResCool NResEndUse.SmlGenCool NResEndUse.GenCool mVars.CoolLoad mVars.Days mVars.Cool_AvgMW mPkDayWthr.PkCDDIdx mVars.Cool_Var 2033 10 5,492.4 390.9 2,735.8 8,619.1 31.0 11.6 - - 2033 11 366.8 26.1 182.8 575.7 30.0 0.8...
AI summary The text presents a table containing data related to cooling load, days, and average megawatts for various months and years, with values for residential and non-residential end-use cooling, as well as variables and weather indices.
218,580.8 17,497.7 141,280.8 21,739.6 40,986.0 6,491.2 446,576.1 30.0 620.2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-43 Attachment 1 Page 10 of 11
AI summary This document contains a redacted section of a 2024 Load Forecast Report, specifically Attachment 1, Page 10 of 11. The content appears to be related to load forecasting, though specific details are confidential and not visible.
Year Month ResEndUse.ResOther NResEndUse.SmlGenOther NResEndUse.GenOther Sales.SmlInd Sales.MedInd Sales.Unm mVars.OthrUse mVars.Days mVars.Other_AvgMW 2027 5 224,769.5 18,079.2 146,394.3 21,939.6 39,977.4 6,459.6 457,619.7 31.0 615.1 2027...
AI summary The text presents a table with data spanning from May 2027 to April 2028, including various metrics such as sales, usage, and other variables. The data appears to be related to energy consumption and distribution, but no specific claims or arguments are discussed.
258,036.5 16,601.4 153,522.4 22,147.5 42,260.5 6,407.2 498,975.4 31.0 670.7 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2024 Load Forecast Report Synapse IR-43 Attachment 1 Page 11 of 11
AI summary The text presents a table with numerical data and references a confidential 2024 Load Forecast Report from Synapse IR-43, Attachment 1, Page 11 of 11. The content has been redacted, indicating the presence of confidential information.
Year Month ResEndUse.ResOther NResEndUse.SmlGenOther NResEndUse.GenOther Sales.SmlInd Sales.MedInd Sales.Unm mVars.OthrUse mVars.Days mVars.Other_AvgMW 2034 1 304,395.6 19,814.6 152,188.7 28,022.2 43,337.0 6,383.8 554,141.9 31.0 744.8 2034...
AI summary The text presents a table of energy usage and sales data for various categories across months in the year 2034. The table includes figures for residential end-use, non-residential end-use, sales by industry size, and other variables such as average megawatts and days.
and jurisdictions, design of retail rates, and performance-based ratemaking for electric 20 utilities. 21 My professional qualifications are further summarized in Attachment 1. 22 Q: Have you testified previously in utility proceedings? 23...
AI summary John D. Wilson, testifying for the Nova Scotia Consumer Advocate, reviews the 2023 Load Forecast Report, noting changes in NS Power’s methods, areas for improvement, and inconsistencies between load forecasts and distribution planning.
er heater loads, for other domestic service, both a demand factor and a 17 coincidence factor are used to reduce the expected maximum load on the transformer from 18 the fuse size. 19 Q: Is the 2024 load forecast consistent with the 2024 n...
AI summary NS Power’s 2024 load forecast and new customer budget for distribution planning show inconsistencies. The residential load forecast includes 7,021 new customers based on the Conference Board’s housing data, while distribution planning uses a lower figure of 4,374 new customers. Exhibits and undertakings are cited to support these discrepancies.
Power’s commercial load forecast does not include an estimate of the number of new customers. 34 Exhibit N-6, Synapse RIR-5, Attachment 1. 35 Exhibit N-26, NSUARB Undertaking U-5. Evidence of John D. Wilson Matter No. M11689 July 11, 2...
AI summary NS Power's load forecast excludes new customer growth and unmetered services, leading to discrepancies with distribution planning forecasts. The testimony highlights the need to align forecasts with electrification strategies and account for housing supply initiatives.
1 necessarily representative of a typical peak. The 2024 Load Forecast report cites SGNS results 2 that indicate managed peak values of 0.35 kW/vehicle, with unmanaged averages across all winter 3 months of 0.2-0.6 kW/vehicle and single hi...
AI summary The text discusses load forecasting for electric vehicles based on SGNS project data, noting wide variation in peak load values and the need for revised assumptions in NS Power's load forecasts. It also references a recent NSUARB decision regarding an ATO application and highlights factors like population and economic growth affecting cost increases.
Disclaimer: These summaries were generated by AI from the filings they describe. We take care to make them accurate, but errors are possible - and they aren't advice. Only the filings themselves are the record: if you're relying on something here, confirm it against the source documents or the Nova Scotia Energy Board's own record. Full disclaimer →