Topic:"Distribution Planning" in M10569

Zone Population Weight Counties Weather latitude longitude included Station A 56,047 0.05649586 Shelbourne, Yarmouth A 43.8 -66 Yarmouth, Digby B 59,406 0.059881761 Queens, Western 44 -64.7 Lunenburg Head C 85,266 0.085948864 Annapolis, Ke...

AI summary The document presents a table with zones, population weights, counties, weather stations, and geographic coordinates. It discusses a method for comparing load forecasts using temperature data from a single weather station (Shearwater RCS) versus a weighted average of multiple weather stations, with the metric used being the Mean Ab.

2022 Load Forecast Report REDACTED 1 Figure 47: Historical and Forecast Annual Small Industrial Sales 2 3 4 5 7.2 Medium Industrial 6 7 Figure 48 depicts historical and projected sales for the Medium Industrial class. Load in 8 this class...

AI summary The 2022 Load Forecast Report discusses historical and projected sales for the Medium Industrial class, noting flat load since 2014, a slight increase in 2020 due to new facilities, and slow growth expected over the forecast period driven by economic activity.

Page 88 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 Due to the degradation of the sample prior to 2017, class peak trend analysis will require 2 several more years of data collection using the new...

AI summary The 2022 Load Forecast Report discusses the challenges in analyzing load trends due to data degradation prior to 2017. It mentions the inclusion of an estimate for the 'unmetered' class, primarily streetlights, and outlines the methodology used to calculate load research data, which closely aligns with system generation.

vs System Generation, 2021 Annual Peak 2 3 4 DATE: April 29, 2022 Page 90 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2022 Load Forecast Report REDACTED 1 Figure 64: 2021 Monthly Load Research Data vs System Generation 2 3 4 Losses c...

AI summary The 2022 Load Forecast Report discusses methods for estimating system losses by comparing load research sales with system generation, and highlights the inclusion of data from the 2020 and 2021 pandemic years in the residential class peak demand forecast analysis.

Page 3 of 3 Appendix A – Forecast Values Table A2: Coincident Peak Demand - 2021 NS Power Forecast Peak Forecast

AI summary This section provides an appendix with forecast values, specifically focusing on Table A2 which outlines the 2021 NS Power forecast for coincident peak demand.

2022 Load Forecast Report Appendix B Page 23 of 32 Appendix B – Forecast Model Details Medium Industrial Model MedInd_Salesm = MBin.Janm + MBin.Febm + MBin.Marm + MBin.Aprm + MBin.Maym + MBin.Junm + MBin.Julm + MBin.Augm + MBin.Sepm + MBin...

AI summary The Medium Industrial Model in the 2022 Load Forecast Report includes monthly binary variables and an economic indicator for manufacturing employment. A binary variable for 2016 and later years was added to improve model fit as the sales trend transitioned from declining to flat. The model uses historical data from 2006–2021.

2,243 2020 2,237 Actual System Peak: 1,882 2,033 2,118 2015 2111 2,018 2,073 2,060 2050 1968 Percent Error 2011 22.7% 12.0% 5.8% 9.6% 2.9% 5.8% 1.1% 0.0% -1.2% 1.1% 2012 3.2% -1.2% 3.4% -1.8% 2.6% -0.4% 0.2% 0.7% 4.7% 2013 -1.9% 3.7% -1.2%...

AI summary The text provides data on actual system peak demand and percent error over various years, along with lead time statistics. It highlights fluctuations in demand and error percentages across different years, indicating variability in forecasting accuracy.

January-21 January Normal Total Load Load Load Heating Actual Load from Jan Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HD...

AI summary The text presents a table with data on load and heating degree days (HDD) for January, including actual load, load from HDD0 and HDD13, lag values, and total heating load. It includes numerical values for different days in January and the total for the month.

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.

March-21 March 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 Mar HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HDDO H...

AI summary The document presents load data for March, including actual load, load from HDD0 and HDD13, and heating load measurements. It includes data for specific days and totals for the month, highlighting load variations and heating requirements.

April-21 April Normal Total Load from Load Load Load Heating Actual Month Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HDDO...

AI summary The text presents a table with data on load from different heating degree day (HDD) metrics, including HDD0 and HDD13, along with load values from various time lags and dates. It includes columns for actual load, total heating load, and load from specific dates and months.

May-21 May Normal Total Load from Load Load Load Heating Actual Month Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HDDO HDD...

AI summary The document presents a table with data on load from different heating degree day (HDD) metrics, including HDD0 and HDD13, along with load from lag1 and lag2, and total heating load in MWh for specific days in May.

September-21 September Normal Total Weather Load from Load Total Weather Load Load Load Load related Actual Month Load From Load From Load From Load from from related Load from Feb From From Load Load from Load Day Actual HDD 0 HDD 13 Actu...

AI summary The text presents a table with load data and weather-related metrics for a specific day in September. It includes actual load values, HDD (Heating Degree Days), CDD (Cooling Degree Days), and load from various lag periods, though the data appears incomplete and lacks context.

November-21 November Normal Load from Total current Load Load Heating Actual Load from Load From Load From Load From Load from Total Heating month From From Load Load Load Day Actual HDD 0 HDD 13 Mar HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh)...

AI summary The text presents a table with data on load from different heating degree day (HDD) metrics and lag periods, including actual load, HDD0, HDD13, and load from lag1 and lag2, along with total heating load and month-specific load values.

December-21 December Normal Total Load Load Load Heating Actual Load from Mar Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day...

AI summary The text presents a table with data on heating degree days (HDD) and load measurements for specific days in December, including actual load, HDD values, and related load metrics. It includes figures for total heating load, load from different HDD values, and load from lag periods.

Date Year Month Day HourEnding Temp Load 1/1/2016 2016 1 5 8 Chart Title 1/4/2016 2016 1 1 8 -1.5 1380.152 2000 1/5/2016 2016 1 2 8 -12.3 1606.003 1800 1/6/2016 2016 1 3 8 -3.3 1576.811 1600 1/7/2016 2016 1 4 8 -2.7 1488.919 1400 1/8/2016...

AI summary The text provides a dataset of temperature and load values over time, including dates, temperatures, and corresponding load measurements. A chart title and equation are included, suggesting an analysis of load trends based on temperature data.

Date Year Month Day HourEnding Temp Load 2/1/2016 2016 2 1 8 3.4 1295.501 Chart Title 2/2/2016 2016 2 2 8 0.7 1314.537 2500 2/3/2016 2016 2 3 8 -8.1 1548.827 2/4/2016 2016 2 4 8 10.6 1246.592 2000 2/5/2016 2016 2 5 8 3.8 1198.113 2/8/2016...

AI summary The text presents a table of temperature and load data for specific dates in February 2016 and February 2017, including a chart with a linear regression equation and an R-squared value, indicating a relationship between temperature and load.

Year System Peak (MW) Firm Peak (MW) Temperature (deg C) Adjustment WN System Peak (MW) WN Firm Peak (MW) 2012 1882 1,740 -7.2 130 2,012 1,870 2013 2033 1,897 -12.8 18 2,051 1,915 2014 2118 2,036 -19.3 -112 2,006 1,924 2015 2015 1,874 -12....

AI summary The text presents a table with data on system peak, firm peak, temperature, and adjustment values for various years. The data shows fluctuations in system and firm peak values over time, with some years showing positive adjustments and others negative.

n billed sales and NSR. The loss Date Filed: July 8, 2022 NSPI (CA) IR-15 Page 1 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 10 - Year Energy and Demand Forecast (2022 Load Forecast Report) (NSUARB M10569) NSPI Responses to Consumer A...

AI summary The document discusses the use of load research data to estimate peak losses and allocate system peak to different classes, noting a 10% precision target and challenges with sample degradation due to legacy meters. It also mentions the preference for using AMI data for more accurate estimates.

kWh/year kW/vehicle on peak LDV 4,323 0.85 MDV 8,205 1.62 Transit Bus 113,890 7.33 2022 Energy 2022 Peak Year BEV tot PHEV tot MDV HDV Total GWh Peak MW Avg kW per car 2021 709 238 947 4 0.8 0.9 2022 1,768 1,096 2,864 12 2.4 0.85 2023 3,50...

AI summary The document presents data on energy consumption and peak demand for different vehicle types over the years 2021 to 2032, including statistics on battery electric vehicles (BEVs), plug-in hybrid electric vehicles (PHEVs), medium-duty vehicles (MDVs), and heavy-duty vehicles (HDVs). It also includes metrics such as total energy consumption in gigawatt-hours and peak demand in megawatts.

eased heat share in 2022 Load Forecast Report Attachment 2 Small General 10 Intensities on the Shares tab (column B), filed electronically. 11 12 (e) Please refer to Attachment 1. Date Filed: July 8, 2022 NSPI (Synapse) IR-34 Page 2 of 2 R...

AI summary The document includes a reference to the 2022 Load Forecast Report and mentions the submission of an attachment related to small general intensities on the Shares tab. It also includes a page reference and a filing date.

ariable Coefficients Month HDD13 HDD 13 HDD0 lag1 lag2 424.273 232.686 -97.305 177.016 43.995 Summary Jan 2021 heating load 374,860 MWh Normal heating load 416,593 MWh 2021 Variance to Normal (41,732) MWh

AI summary The text provides data on heating load for January 2021, showing a variance of -41,732 MWh compared to the normal heating load of 416,593 MWh. It also includes variable coefficients and lag values related to heating degree days (HDD).

January-21 January Normal Total Load Load Load Heating Actual Load from Jan Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HD...

AI summary The text presents a table with data on load and heating degree days (HDD) for January, including actual load, load from HDD0 and HDD13, lag values, and total heating load. It includes figures for different days and months, but lacks detailed context or analysis.

HDD CDD 2018 31 653.56 0 CONST 21647.659 72.618 298.105 0.00% Jan 1,052,758 28 593.83 0 Daily.JanHDD18 584.003 7.033 83.037 0.00% Feb 945,992 31 557.82 0.21 Daily.FebHDD18 572.314 7.369 77.661 0.00% Mar 957,259 30 393.94 0 Daily.MarHDD18 5...

AI summary The text presents a table containing data on heating degree days (HDD) and cooling degree days (CDD) for various months in 2018, along with associated values such as daily averages, totals, and percentages. The data appears to be related to energy usage or climatic conditions.

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 text presents a table with data on heating load and temperature differences over several days in February. It includes metrics such as HDD0, HDD13, and actual load values, along with load from various lag periods and total heating load in MWh.

March-21 March 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 Mar HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HDDO H...

AI summary The text presents a table with load data for March 21, including actual load, load from HDD0 and HDD13, and heating load measurements. It includes information on load from different time lags and total heating load for the month and day.

May-21 May Normal Total Load from Load Load Load Heating Actual Month Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HDDO HDD...

AI summary The text presents a table with load data, including actual load, HDD values, and heating load measurements across different days in May. It includes metrics such as load from various HDD thresholds, lag values, and total heating load in MWh.

June-21 June Normal Total Load from Load Load Load Load Load Heating Month Load From Load From Load From Load from from Total Heating Actual from Feb From From Load Load from Load Day Actual HDD 0 Actual HDD 13 Actual CDD 18 HDD13 HDD 13 H...

AI summary The document contains a table with load data, including heating and cooling degree days (HDD and CDD), load values, and lag values for different days in June. The data includes load from various sources, total load, and heating load details.

July-21 July Normal Total Load from Load Load Load Load Heating 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 Actual CDD18 HDD13 HDD 13 HD...

AI summary The text presents a table containing load data for a specific period, including information on heating degree days (HDD) and cooling degree days (CDD), along with load measurements in megawatt-hours (MWh). The data appears to be related to energy consumption analysis.

October-21 October 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 Mar HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day HD...

AI summary The text provides a table with data on load and heating degree days (HDD) for a specific period, including actual load, load from HDD0, HDD13, lag1, lag2, and total heating load in MWh. This data is likely used for energy planning and load forecasting.

November-21 November Normal Load from Total current Load Load Heating Actual Load from Load From Load From Load From Load from Total Heating month From From Load Load Load Day Actual HDD 0 HDD 13 Mar HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh)...

AI summary The document presents a table with data on load from different heating degree day (HDD) categories, including HDD0 and HDD13, and load from lag1 and lag2, with values provided for specific days in November. It includes information on total load, heating load, and load from various sources.

December-21 December Normal Total Load Load Load Heating Actual Load from Mar Load From Load From Load From Load from Total Heating from Feb From From Load Load Load Day Actual HDD 0 HDD 13 HDD13 HDD 13 HDD0 lag1 lag2 Load (MWh) Month Day...

AI summary The text presents a table with data related to heating load and HDD (Heating Degree Days) values for different days in December. It includes columns for actual load, load from HDD13, load from HDD0, and lag values. The data appears to be used for analyzing heating patterns and energy consumption trends.

Date Year Month Day HourEnding Temp Load 1/1/2016 2016 1 5 8 Chart Title 1/4/2016 2016 1 1 8 -1.5 1380.152 2000 1/5/2016 2016 1 2 8 -12.3 1606.003 1800 1/6/2016 2016 1 3 8 -3.3 1576.811 1600 1/7/2016 2016 1 4 8 -2.7 1488.919 1400 1/8/2016...

AI summary The text presents a dataset containing temperature, load, and date information over a period of time, including a chart with a linear regression equation and an R-squared value indicating the relationship between temperature and load.

Date Year Month Day HourEnding Temp Load 1/1/2016 2016 1 5 18 Chart Title 1/4/2016 2016 1 1 18 -2.2 1589.985 2500 1/5/2016 2016 1 2 18 -8.2 1718.745 1/6/2016 2016 1 3 18 2.6 1525.711 2000 1/7/2016 2016 1 4 18 2.2 1485.471 1/8/2016 2016 1 5...

AI summary The text presents a table with dates, temperatures, and load data, including a chart title and a linear regression equation (y = -25.222x + 1522.6) with an R-squared value of 0.7961. The data spans from January 2016 to January 2017 and includes various temperature and load measurements.

Date Year Month Day HourEnding Temp Load 2/1/2016 2016 2 1 8 3.4 1295.501 Chart Title 2/2/2016 2016 2 2 8 0.7 1314.537 2500 2/3/2016 2016 2 3 8 -8.1 1548.827 2/4/2016 2016 2 4 8 10.6 1246.592 2000 2/5/2016 2016 2 5 8 3.8 1198.113 2/8/2016...

AI summary The text contains a table with dates, temperatures, and load data over multiple days in February 2016 and February 2017, including a chart title and equation related to load trends.

Year System Peak (MW) Firm Peak (MW) Temperature (deg C) Adjustment WN System Peak (MW) WN Firm Peak (MW) 2012 1882 1,740 -7.2 130 2,012 1,870 2013 2033 1,897 -12.8 18 2,051 1,915 2014 2118 2,036 -19.3 -112 2,006 1,924 2015 2015 1,874 -12....

AI summary The table provides historical data on system peak and firm peak demand (in MW), temperature, and adjustments from 2012 to 2028. It shows variations in demand and temperature over time, with some years showing positive adjustments and others negative.

nd won’t be suitable for all 30 homes and users 31 32 (c) Natural gas availability is limited to portions of a small number of urban 33 areas in the province DATE FILED: September 26, 2022 Page 22 of 25 2022 Load Forecast Report Rebuttal N...

AI summary The document discusses the limitations of natural gas availability, noting that it is only accessible in certain urban areas of the province, and highlights that not all homes and users will be suitable for natural gas service.