Topic:"Energy Efficiency" in M11108

red by Hour per EV ............................................... 42 31 Figure 29: Peak Demand of ChargePoint EV Charging Fleet ...................................................... 43 32 Figure 30: EV Impact to Energy and Peak Forecasts...

AI summary The document contains a list of figures related to energy demand forecasting, EV charging impacts, solar PV effects, battery potential, residential and commercial electrification trends, and historical vs projected electricity prices. The text is redacted, with confidential information removed, and spans multiple pages of analysis.

1 1.0 EXECUTIVE SUMMARY 2 3 In accordance with the Nova Scotia Wholesale Electricity and Renewable to Retail Market 4 Rules, Nova Scotia Power Incorporated (NS Power, the Company) is required to provide 5 the Nova Scotia Utility and Review...

AI summary NS Power must submit a 10-year load forecast to NSUARB, covering 2023-2033. The forecast considers sales history, weather, economic factors, and uses SAE models. Uncertainties from variables like weather and policy changes are acknowledged.

As with the 2022 Load Forecast, the forecasts developed by third party consultant E3 for 26 space heating and EV load shapes are used. The space heating forecast uses the uptake 27 required to meet stated emission goals over the next 20 ye...

AI summary The 2023 Load Forecast Report highlights the continued growth of heat pump usage in Nova Scotia, driven by incentives and financing options. The forecast estimates a 40% saturation of heat pump usage in 2023, with a significant increase in installations compared to previous forecasts, and assumes full residential saturation by 2050 to meet carbon reduction targets.

a was collected in 17 2021/2022 and analyzed by Itron. 12 The analysis determined that on a weather normalized 18 basis, the average impact of a heat pump was 4400 kWh/year/household, with a coincident 19 peak impact of +1.5 kW/household (...

AI summary The text discusses the energy impact of heat pumps based on data collected in 2021/2022 and analyzed by Itron. It states that the average annual impact is 4400 kWh/year/household, with a peak impact of +1.5 kW/household. The estimated impact for 2023 is 3922 kWh/year/household, aligning with Itron's results, which included the effects of COVID-19 restrictions.

Overall Total Overall Overall Overall % Install Heating Cumulativ % Install % Sat. % Sat. Cooling Year Non-Elec. Intensity e New Elec. Heat for for Intensity Heat (kWh/house Installs Heating Cooling (kWh/house) ) 2023 20,887 66 34 40 1,384...

AI summary The table provides data on the cumulative number of installations, percentage of non-electric and electric heat installations, and heating and cooling intensities from 2023 to 2033. It shows a steady increase in installations and intensity values over time.

1 events. Two bi-directional chargers have been installed as of December 2022 with 2 additional chargers expected to be installed through 2023. The current installations have 3 been installed at non-residential locations with utility contr...

AI summary The document discusses the installation and performance of bi-directional EV chargers in Nova Scotia, noting that two have been installed by December 2022 with more expected in 2023. These chargers are located at non-residential sites and are used to offset building load. The availability of fleet vehicles is a key factor in determining the capacity factor of these chargers. Charging patterns show higher load during summer and peak usage around 11:00 pm on weeknights, influenced by factors like TOU rates and customer perceptions.

) 2023 Load Forecast Report REDACTED 1 Figure 31: PV Impact to Energy (cumulative) 2

AI summary The document presents a redacted section of the 2023 Load Forecast Report, specifically Figure 31, which illustrates the cumulative impact of photovoltaic (PV) systems on energy.

Total New Year Load (GWh) Peak (MW) Installs 2023 2,268 -24 0 2024 4,876 -51 0 2025 7,875 -82 0 2026 11,324 -112 0 2027 15,290 -152 0 2028 19,852 -197 0 2029 25,097 -249 0 2030 31,130 -309 0 2031 37,777 -376 0 2032 45,120 -449 0 2033 53,23...

AI summary The document outlines projected load growth and peak demand from 2023 to 2033, noting minimal impact from distributed solar and battery storage due to high battery costs. It highlights that gas generators are currently more cost-effective than batteries for residential use, though new pricing mechanisms may encourage battery adoption.

t-effective solution. The new critical peak pricing (CPP) and TOU rates currently being 14 piloted might start to encourage battery installation either alone or in conjunction with solar 15 panels, but the initial costs associated with bat...

AI summary The document discusses the potential of new critical peak pricing (CPP) and time-of-use (TOU) rates in encouraging battery installation, either alone or with solar panels. However, it notes that initial battery costs are high, and while improvements in technology may reduce these costs over time, timelines for significant changes are uncertain.

Page 46 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report REDACTED 1 The impacts of technologies related to direct load control (DLC) of heating and hot water 2 loads are discussed in Section 10. 3 4 Intensities 5...

AI summary The document discusses the modeling of residential end-use intensities, including electric heating, cooling, water heating, lighting, and other appliances. It also mentions the inclusion of photovoltaic (PV) and electric vehicle (EV) forecasts in the 'Other' category to illustrate their impact relative to other end uses.

l as smaller appliances such as computers, dehumidifiers, 26 microwaves, etc. This category also includes solar generation (photovoltaic or PV) 27 and EV forecasts. 28 DATE: April 28, 2023 Page 47 of 98 REDACTED (CONFIDENTIAL INFORMATION R...

AI summary The document discusses residential and commercial end-use intensities, highlighting trends such as increased use of heat pumps, changes in electric baseboard heating, and the impact of EV load and PV generation. Supporting data is referenced in Attachment 1.

1 emissions. These programs involve converting heating loads to electricity (mainly from 2 oil), accelerating the uptake of electric cooling technologies, and examining opportunities 3 to power industrial processes through electrification....

AI summary The text discusses electrification programs targeting commercial and industrial sectors, focusing on converting heating loads to electricity, promoting electric cooling technologies, and electrifying industrial processes. Forecasts for electrification growth by customer class are provided, with specific data shown in Figure 36.

e of double counting, the approach used is the same as that used in prior 24 forecasts: to introduce cumulative historical DSM savings as reported by E1 to the 25 regression model as a load modifying variable, and allow the model to determ...

AI summary The text discusses the method used to avoid double counting in load forecasts by incorporating historical DSM savings from EfficiencyOne into a regression model. This approach assumes future DSM activities will mirror past ones, and the coefficient from historical DSM will apply to future forecasts.

Page 57 of 98 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report REDACTED 1 Apart from the shift related to increased work from home, the long-term trend is higher 2 than the previous forecast, with higher EV penetration...

AI summary The 2023 Load Forecast Report indicates an upward trend in residential electricity demand, driven by increased work from home, higher EV penetration, and new customer growth. Efficiency improvements and solar generation will reduce sales, but overall residential sector loads are expected to increase by 1.1% annually from 2023 to 2033. Population growth and new housing construction are also key factors in the forecast.

1 7.4 Municipal 2 3 The Municipal class comprises municipal electric utilities that purchase wholesale 4 electricity from NS Power and distribute it within their own service territories. Utility loads 5 within these municipalities include...

AI summary The Municipal class includes municipal electric utilities that purchase wholesale electricity from NS Power and distribute it within their service territories. Since 2007, these utilities have had the option to source electricity from third-party providers through the Open Access Transmission Tariff (OATT). Some utilities have shifted to 100% third-party supply, reducing their load, but NS Power must still provide backup capacity for these utilities.

REMOVED) 2023 Load Forecast Report REDACTED 1 Figure 64: Weather-Normalized Firm Peak (including DR) 2 3 4 5 Figure 65 below shows the breakdown of the peak forecast by the various components. 6 7 Figure 65: Peak Contribution Components (M...

AI summary The 2023 Load Forecast Report provides a breakdown of peak contribution components, including modeled peak, residential heating, EV impact, demand response, commercial and industrial loads, large customers, DSM programs, and system peak. The report compares forecasted values for 2023 and 2033, with and without EV mitigation.

Residential Commercial Industrial Municipal Total Year Sector Growth Sector Growth Sector Growth and Other Growth Losses Energy Growth GWh % GWh % GWh % GWh % GWh GWh % 2013 4,362 4.8 3,244 1.5 2,604 20.3 201 4.8 784 11,194 6.9 2014 4,404...

AI summary The table presents energy consumption data across residential, commercial, industrial, municipal, and other sectors from 2013 to 2024, showing varying growth rates and energy losses over time.

t Appendix B Page 5 of 33 Appendix B – Forecast Model Details Residential SAE Model Fit Residential Model 2023-2033 Reconciliation The following tables provide details reflecting the changes between 2023 and 2033 forecast years. Some of th...

AI summary This section provides a reconciliation of residential load forecasts from 2023 to 2033, showing changes in key metrics such as existing and new customer load, EV load, solar load, RTR, and DSM. The data highlights increases in customer load and EVs, while solar load decreases slightly.

2023 Load Forecast Report Appendix B Page 27 of 33 Appendix B – Forecast Model Details Combined Model for Commercial and Industrial DSM Coefficient NonResSalesm = b1×NonResEESavingsProfiledm + b2×GenWtXHeatm + b3×GenWtXCoolm + b3×GenWtXOth...

AI summary This section of the 2023 Load Forecast Report Appendix B presents a combined model for commercial and industrial demand-side management (DSM) coefficients, including variables such as non-residential energy efficiency savings, weighted end-uses, and binary variables for billing issues in February 2018 and October 2022. It also provides statistical details of the model.

ACTED 2023 Load Forecast Report Appendix D Page 7 of 9 Appendix D – Forecast Sensitivity Analysis Figure D5: Relative Sensitivity of Peak In terms of the sensitivity of the energy sales forecast to the various input variables, Figures D6 a...

AI summary The document discusses the sensitivity of energy sales and peak demand forecasts to various input variables. In the near term, weather has the strongest impact, while in the long term, economic factors become more dominant. Demand-side management (DSM), electric vehicles (EVs), and hybrid heating peak mitigation are identified as key drivers of forecast sensitivity.

ivers, while on the peak side DSM, EVs, hybrid heating peak mitigation and weather/economics are all similar. Figure D8 shows the relative impact of these items. Figure D8: Relative Impact of Inputs 2023 Energy 2023 Peak 2033 Energy 2033 P...

AI summary The document discusses the impact of various factors on energy and peak demand forecasts for 2023 and 2033, including demand-side management (DSM), solar PV, electric vehicles (EVs), hybrid heating systems, and weather/economics. It outlines scenarios such as the E3 hybrid scenario and mentions the potential for large-scale hydrogen production.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Consumer Advocate Information Requests NON-CONFIDENTIAL 1 Request IR-2: 2 3 Reference: Exhibit N-1, pp. 33-37. 4 5 (a) Please confirm that NS Power’s forecast for residential heat...

AI summary The Consumer Advocate requests NSPI to clarify assumptions in its 2023 load forecast regarding heat pump installations, including whether existing heating systems are retired, how continued use of fossil fuels is modeled, and whether electrification requires additional market interventions. NSPI must provide analysis on load impacts from increased comfort and floor space usage.

oads to program participation.” As stated on 25 page 20 of the report 2, “There are significant potential energy cost savings for 1 F 26 customers that adopt heat pump technology. Customer behaviour will influence 27 whether customers obta...

AI summary NS Power's Load Forecast assumes heat pumps will dominate heating by 2030, noting customer behavior may prioritize comfort over energy savings. The company suggests market interventions, like revising Efficiency One's mandate, could accelerate electrification. The Public Utilities Act amendment in 2022 is cited as enabling such changes.

Nova Scotia government announced changes to 9 the Public Utilities Act 3 to enable EOne to focus on administering a suite of programs and 2 F 10 services that help Nova Scotians transition their energy end uses from fossil fuels to 11 elec...

AI summary The Nova Scotia government has updated the Public Utilities Act to allow EOne to focus on programs that support electrification and reduce greenhouse gas emissions. NS Power supports these initiatives but has not yet analyzed the necessity of intervention or conducted a gap analysis for the load forecast.

𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇 � � 𝑇𝑇𝑇𝑇𝑇𝑇𝑇𝑇� 𝐸𝐸𝐸𝐸𝐸𝐸15 2 Where Type is an end-use, SatyType is the saturation (shares) of an end-use of given 3 Type for a particular year y, EffyType is the efficiency of an end-use of given Type 4 for a particular year y, and EI...

AI summary The text presents a formula for calculating efficiency factors (EIyy) using saturation (Satyy), efficiency (Effyy), and a 2015 calibration weight (EI15). The calculation involves multiplying saturation and efficiency shares for a given end-use type and year, then adjusting by the 2015 reference weight. This appears to be a technical methodology for energy efficiency modeling.

1 Request IR-2: 2 3 Reference: NS Power 2023 Load Forecast, Page 36, Lines 8-14 4 5 “On average, the coefficient of performance (COP) of heat pumps modeled in the RESHAPE 6 scenario supporting the Load Forecast declines from 400 percent at...

AI summary The request seeks details on heat pump performance modeling in NS Power's 2023 Load Forecast, including COP and capacity curves, heat pump type assumptions, and changes from the 2022 forecast. It highlights concerns about cold-temperature performance impacts on peak load and backup heating efficiency.

ase describe the change 26 and the rationale for the change. 27 (i) COP curves 28 (ii) Capacity curves 29 (iii) Outdoor air temperature cut-off point 30 Date Filed: June 20, 2023 NSPI (EOne) IR-2 Page 1 of 3 2023 Load Forecast Report (NSUA...

AI summary NSPI (EOne) responds to queries about heat pump assumptions in the 2023 Load Forecast, detailing COP curves, capacity curves, and outdoor temperature cut-off points. The response outlines a 30% Base, 40% Mid, and 30% Best-in-Class heat pump mix under the 'Current Policies and Trends' scenario, with COP values visualized in a graph.

, E3 modeled 22 a mix of 30 percent Base efficiency, 40 percent Mid efficiency and 30 percent Best in Class 23 heat pumps. The corresponding COPs are shown in the following graph: Date Filed: June 20, 2023 NSPI (EOne) IR-2 Page 2 of 3 2023...

AI summary NSPI (EOne) discusses heat pump modeling assumptions in their 2023 Load Forecast Report, including a 'Hybrid Peak' scenario with non-electric heating retention. They reference E3's RESHAPE model and note no changes from the 2022 forecast except for updated assumptions in the Hybrid Peak scenario.

Use and GHG Emissions Table 4: Space Cooling Secondary Energy Use and GHG Emissions by Cooling System Type Table 5: Space Heating Secondary Energy Use and GHG Emissions by Energy Source Table 6: Space Heating Secondary Energy Use and GHG E...

AI summary The document presents tables analyzing secondary energy use and GHG emissions across various building types, heating systems, and appliance categories, alongside explanatory variables related to housing stock and floor space, as part of the 2023 Load Forecast Report.

ions by Energy Source Table 39: Apartments Secondary Energy Use and GHG Emissions by End-Use Mobile Homes Table 40: Mobile Homes Secondary Energy Use and GHG Emissions by Energy Source Table 41: Mobile Homes Secondary Energy Use and GHG Em...

AI summary The text presents tables detailing energy use and GHG emissions by energy source and end-use for residential and mobile homes in Nova Scotia. It also references the 2023 Load Forecast Report and mentions the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use (PJ) 41.8 44.1 45.3 42.3 40.2 38.4 39.1 44.9 45.2 46.2 46.3 49.5 44.1 43.0 40.9 42.1 38.1 38.9 41.1 41.2 Energy Use by Ene...

AI summary The text presents historical data on total energy use in Nova Scotia from 2000 to 2019, broken down by energy source including electricity, natural gas, heating oil, other, and wood. The data shows fluctuations in energy consumption over time, with notable changes in the use of heating oil and electricity.

5.5 4.9 4.6 4.0 4.8 5.0 5.1 6.5 6.3 6.8 6.2 6.7 6.6 7.6 7.4 8.3 7.5 7.3 7.7 7.5 Shares (%) Electricity 31.8 32.4 32.6 34.2 36.8 38.6 36.9 33.4 33.5 33.0 32.4 31.2 34.3 36.9 38.6 37.6 41.7 42.2 41.2 41.4 Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The text presents statistical data on energy usage shares and activity metrics across various energy sources and housing statistics from 2001 to 2020. It details percentages of electricity, natural gas, heating oil, and other energy sources, alongside total floor space and total households in thousands.

359.5 362.6 366.6 370.6 374.0 377.0 379.6 382.9 387.9 392.5 389.8 391.2 393.4 393.3 397.0 400.0 402.0 406.0 410.8 415.6 2 Energy Intensity (GJ/m ) 0.90 0.94 0.95 0.87 0.81 0.76 0.76 0.85 0.85 0.85 0.84 0.89 0.78 0.75 0.70 0.72 0.64 0.64 0....

AI summary The text presents numerical data on energy intensity measured in GJ/m² and GJ/household across multiple years, indicating trends and variations in energy consumption over time.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.2 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Shares (%) Electricity – – – – – – – – – – – – – – – – – – – – Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.6 0.3 0.4 0.6 0.7 0.8 1.0 1.0 1.1 1.2 Heat...

AI summary The table presents the distribution of shares and GHG intensity across various energy sources over time. It shows the percentage shares of electricity, natural gas, heating oil, other, and wood, along with the corresponding GHG intensity in tonnes per TJ for each year.

41.9 42.4 42.8 41.9 39.0 37.1 38.4 40.2 40.3 40.1 41.3 42.2 39.3 36.2 34.8 34.6 31.7 31.8 32.6 32.6 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The text provides data on energy use and GHG emissions in Nova Scotia, including heating and cooling degree-day indices and a table showing secondary energy use and GHG emissions by end-use from 2000 to 2019. The data excludes electricity production-related emissions and includes a note on the source of the information.

0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.2 0.2 0.1 0.2 0.2 0.2 0.3 0.2 Shares (%) Space Heating 65.4 65.0 65.2 64.8 64.9 63.2 62.0 63.5 67.0 68.1 66.2 67.9 64.7 65.1 66.5 68.2 65.1 66.1 64.7 65.2 Water Heating 18.7 19.0 18.8 18.5...

AI summary The text presents statistical data on energy consumption distribution across various categories such as space heating, water heating, appliances, lighting, and space cooling over time, alongside metrics like total floor space and total households. The data reflects trends and changes in energy usage patterns.

359.5 362.6 366.6 370.6 374.0 377.0 379.6 382.9 387.9 392.5 389.8 391.2 393.4 393.3 397.0 400.0 402.0 406.0 410.8 415.6 2 Energy Intensity (GJ/m ) 0.90 0.94 0.95 0.87 0.81 0.76 0.76 0.85 0.85 0.85 0.84 0.89 0.78 0.75 0.70 0.72 0.64 0.64 0....

AI summary The text presents numerical data on energy intensity in Nova Scotia, measured in gigajoules per square meter and per household over a series of years. The data shows fluctuations in energy intensity, indicating changes in energy consumption patterns.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Space Heating 79.0 78.7 79.0 79.0 79.9 79.0 77.0 76.6 79.8 80.5 78.4 79.4 77.7 79.1 81.3 82.6 81.7 82.7 81.1 81.6 Water Heating 21.0 21.3 21.0 21.0...

AI summary The text presents data on energy usage distribution and GHG intensity across different sectors, showing variations in percentages and tonnes per TJ over time. The data highlights energy consumption patterns in space heating, water heating, and other categories, alongside GHG emissions intensity.

41.9 42.4 42.8 41.9 39.0 37.1 38.4 40.2 40.3 40.1 41.3 42.2 39.3 36.2 34.8 34.6 31.7 31.8 32.6 32.6 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The text presents data on energy use and GHG emissions for the residential sector in Nova Scotia, including lighting energy use and heating and cooling degree-day indices over multiple years. It also references the Office of Energy Efficiency and a Load Forecast Report.

1.6 1.7 1.7 1.7 1.7 1.7 1.6 1.6 1.5 1.5 1.5 1.5 1.5 1.6 1.5 1.4 1.5 1.5 1.6 1.5 Activity Total Households (thousands) 359.5 362.6 366.6 370.6 374.0 377.0 379.6 382.9 387.9 392.5 389.8 391.2 393.4 393.3 397.0 400.0 402.0 406.0 410.8 415.6 E...

AI summary The document presents data on energy intensity, household numbers, and GHG emissions for the residential sector in Nova Scotia. It includes statistics on total households, energy intensity, and heat loss over time, excluding electricity-related GHG emissions. The data is sourced from the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Space Heating Energy Use (PJ) 27.4 28.7 29.5 27.4 26.1 24.3 24.3 28.5 30.3 31.5 30.7 33.6 28.5 28.0 27.2 28.7 24.8 25.7 26.6 26.9 Ene...

AI summary The table presents total space heating energy use and its breakdown by energy source from 2000 to 2019. It shows the use of electricity, natural gas, heating oil, other sources, and wood for space heating in Nova Scotia over time.

5.0 4.5 4.2 3.7 4.5 4.6 4.7 6.0 5.9 6.4 5.8 6.3 6.2 7.1 7.0 7.9 7.1 6.9 7.3 7.1 Shares (%) Electricity 15.9 16.6 17.0 18.3 20.5 21.3 19.4 17.2 18.7 18.8 17.8 17.5 18.6 20.6 22.5 22.1 24.2 25.4 23.7 24.2 Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The data presents trends in energy consumption and intensity across various fuel types and total floor space over time, showing fluctuations in shares and energy usage patterns. This information is relevant for understanding energy efficiency and consumption trends.

) 50.6 51.4 51.8 51.2 48.0 46.4 47.6 48.5 48.0 47.4 49.0 49.3 47.2 44.0 42.5 41.9 39.8 39.8 40.9 40.8 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Heat Gains (...

AI summary The document presents data on space heating secondary energy use and GHG emissions by building type in Nova Scotia from 2000 to 2019, including metrics like Heating Degree-Day Index and Heat Gains (PJ). It also notes that GHG emissions data exclude electricity production and includes a disclaimer about confidential information being redacted.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Space Heating Energy Use (PJ) 27.4 28.7 29.5 27.4 26.1 24.3 24.3 28.5 30.3 31.5 30.7 33.6 28.5 28.0 27.2 28.7 24.8 25.7 26.6 26.9 Ene...

AI summary The table presents total space heating energy use and energy use by building type from 2000 to 2019, showing fluctuations in energy consumption across different categories such as single detached, single attached, apartments, and mobile homes.

1.3 1.3 1.4 1.3 1.2 1.1 1.1 1.3 1.4 1.4 1.4 1.5 1.3 1.2 1.2 1.2 1.1 1.1 1.1 1.2 Shares (%) Single Detached 80.3 80.3 80.3 80.3 80.1 80.0 79.9 79.7 79.7 79.7 79.7 79.7 79.6 79.4 79.3 79.2 79.0 78.8 78.7 78.6 Single Attached 6.1 6.1 6.1 6.1...

AI summary The text presents statistical data on housing types and energy usage trends, including shares of different housing categories and total floor space, along with energy intensity measurements over time. The data suggests a shift in housing distribution and changes in energy efficiency.

5.7 5.7 5.7 2011–2015 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 2.1 3.2 4.1 4.9 4.9 4.9 4.9 4.9 2016–2019 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 2.2 3.2 4.2 Activity Total Floor Space (million m2) 46.4 47...

AI summary The text presents data tables showing energy intensity and total floor space over time, indicating trends in energy use and building expansion from 2011 to 2019. Energy intensity decreased slightly over the years, suggesting improved energy efficiency in buildings.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 2006–2010 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 2011–2015 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.1 0.1 0.1 2016–20...

AI summary The document provides a table showing GHG intensity and heating degree-day index data for various time periods, excluding electricity production-related emissions. It is part of the 2023 Load Forecast Report and includes information from the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

Total Space Heating Energy Use (PJ) 27.4 28.7 29.5 27.4 26.1 24.3 24.3 28.5 30.3 31.5 30.7 33.6 28.5 28.0 27.2 28.7 24.8 25.7 26.6 26.9 Energy Use by System Type (PJ) Heating Oil – Normal Efficiency 8.1 7.8 7.1 5.7 4.4 3.1 2.5 2.2 1.8 1.1...

AI summary The document provides data on total space heating energy use and energy use by system type in PJ units over multiple years, showing fluctuations in consumption across different heating systems such as heating oil and natural gas, as well as electric and heat pump usage.

1.8 2.4 2.4 2.7 2.5 3.6 3.8 3.1 3.3 3.2 3.2 2.2 2.1 1.8 1.6 1.9 1.9 1.7 0.3 0.3 Wood 4.2 3.1 2.8 2.7 3.3 3.8 3.8 4.1 3.8 3.9 3.6 3.6 4.1 4.9 5.0 5.4 5.7 5.4 5.5 5.4 Dual Systems Wood/Electric 11.6 10.5 9.6 9.2 11.4 12.6 12.7 13.8 12.9 13.4...

AI summary The text presents numerical data on energy consumption and floor space over time, detailing various fuel types and systems. It includes energy intensity measurements and total floor space in millions of square meters, indicating trends in energy usage and building expansion.

Shares (%) Heating Oil – Normal Efficiency 40.5 36.5 31.9 27.8 24.0 18.8 15.0 11.3 8.7 5.2 3.1 2.6 2.2 1.7 1.0 0.8 0.4 0.2 0.2 0.0 Heating Oil – Medium Efficiency 37.7 42.0 47.1 50.9 52.8 55.3 58.8 62.7 65.2 67.1 70.6 72.5 71.5 69.7 70.2 6...

AI summary The text presents a table showing the distribution of shares over time for various heating and energy sources, including Heating Oil (Normal, Medium, and High Efficiency), Natural Gas (Normal, Medium, and High Efficiency), Electric, Heat Pump, and Other. The data illustrates a decline in the share of Heating Oil – Normal Efficiency and an increase in the share of Heating Oil – Medium Efficiency over time.

0.0 0.0 0.0 0.0 Other2 2.2 2.9 2.8 3.2 3.1 4.7 4.9 3.9 4.2 4.1 4.1 2.8 2.7 2.5 2.4 2.7 2.9 2.6 0.5 0.4 Wood 2.0 1.4 1.2 1.2 1.6 1.9 1.9 2.0 1.9 2.0 1.7 1.7 2.0 2.6 2.8 3.0 3.3 3.2 3.2 3.1 Dual Systems Wood/Electric 5.2 4.6 4.1 4.0 5.3 6.1...

AI summary The text presents numerical data on energy usage and greenhouse gas (GHG) intensity across various fuel types and systems in Nova Scotia. It includes metrics such as GHG intensity, heat gains, and energy consumption for different fuel combinations like wood, electric, and heating oil. The data spans multiple years and provides insights into energy trends and environmental impact.

2.5 2.7 2.9 2.8 2.9 2.7 2.4 2.5 2.8 2.9 2.6 2.8 2.5 2.7 2.9 3.0 2.9 3.2 3.1 3.3 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 1) Data on GHG emissions are prese...

AI summary The text presents numerical data on heating degree-day index and water heating secondary energy use and GHG emissions by energy source in Nova Scotia from 2000 to 2019. It also includes a note about excluded GHG emissions related to electricity production and mentions the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Water Heating Energy Use (PJ) 7.8 8.4 8.5 7.8 7.1 7.0 7.6 8.8 7.8 7.6 8.4 8.6 8.0 7.2 6.2 5.9 5.5 5.4 6.1 6.0 Energy Use by Energy So...

AI summary The table presents total water heating energy use and energy use by source in Nova Scotia from 2000 to 2019. It shows a decline in energy use over time, with electricity and heating oil being the primary sources of energy for water heating. Natural gas and other sources are not used for water heating during this period.

46.9 47.6 48.0 47.5 44.5 43.1 45.3 47.6 47.1 47.2 49.2 50.0 48.2 45.2 42.9 42.4 39.6 39.4 41.2 40.9 Heat Loss (PJ) 0.2 0.3 0.3 0.3 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 1) Data on GHG emissions are presented exclu...

AI summary The text provides numerical data on heat loss and GHG emissions, along with a table showing water heating secondary energy use and GHG emissions by building type in Nova Scotia from 2000 to 2019. It excludes GHG emissions related to electricity production and includes notes on data sources and categories.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Water Heating Energy Use (PJ) 7.8 8.4 8.5 7.8 7.1 7.0 7.6 8.8 7.8 7.6 8.4 8.6 8.0 7.2 6.2 5.9 5.5 5.4 6.1 6.0 Energy Use by Building...

AI summary The text presents historical data on total water heating energy use and energy use by building type in Nova Scotia from 2000 to 2019, showing trends and variations across different categories of buildings.

0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Shares (%) Single Detached 72.1 72.0 72.0 71.9 72.1 72.3 72.4 72.5 72.0 71.4 70.8 70.2 70.1 70.1 70.0 70.1 70.1 70.0 70.0 69.9 Single Attached 7.1 7.2 7.2 7.3...

AI summary The text presents statistical data on household distribution and energy intensity over time, showing changes in the percentage of different types of housing and energy consumption per household. This data may be used for planning and policy-making related to energy use and distribution.

47.1 47.2 49.2 50.0 48.2 45.2 42.9 42.4 39.6 39.4 41.2 40.9 1) Data on GHG emissions are presented excluding GHG emissions related to electricity production only. Office of Energy Efficiency, Demand Policy and Analysis Division, Market Ana...

AI summary The text provides data on appliance energy use and GHG emissions in Nova Scotia from 2000 to 2019, showing trends in energy consumption by electricity and natural gas. It also references the exclusion of electricity production-related emissions and mentions the Office of Energy Efficiency and related divisions.

14.0 14.8 15.0 14.3 14.2 14.5 14.7 15.3 14.3 14.0 14.4 14.6 14.9 15.6 14.9 14.6 15.1 15.1 16.0 15.9 Total Appliance GHG Emissions Excluding Electricity (Mt of CO2e) 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0....

AI summary The text presents data on GHG emissions from appliance use in Nova Scotia, excluding electricity production. It includes figures for total appliance GHG emissions and GHG intensity, with data points spanning multiple years. The data is sourced from the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

Total Appliance Energy Use (PJ) 5.0 5.4 5.5 5.3 5.3 5.5 5.6 5.9 5.5 5.5 5.6 5.7 5.9 6.1 5.9 5.8 6.1 6.1 6.6 6.6 Energy Use by Appliance Type (PJ) Refrigerator 1.2 1.2 1.2 1.1 1.1 1.0 1.0 1.0 0.9 0.9 0.9 0.9 0.9 0.9 0.8 0.8 0.8 0.8 0.8 0.8...

AI summary The text presents a table showing total appliance energy use and energy use by appliance type in PJ units over time. It provides data on energy consumption for various appliances, including refrigerators, freezers, dishwashers, clothes washers, clothes dryers, ranges, and other appliances.

26.3 27.5 29.0 30.3 31.5 32.7 34.0 35.4 37.0 37.9 39.8 41.6 43.0 44.0 45.1 46.0 46.7 47.5 48.3 49.0 Activity Total Households (thousands) 359.5 362.6 366.6 370.6 374.0 377.0 379.6 382.9 387.9 392.5 389.8 391.2 393.4 393.3 397.0 400.0 402.0...

AI summary The text provides numerical data on household activity and energy intensity over time, showing trends in the number of households and energy consumption per household in thousands of gigajoules.

Heat Loss by Appliance Type (PJ) Refrigerator 0.5 0.5 0.5 0.5 0.5 0.4 0.4 0.4 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.3 0.4 Freezer 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.2 0.2 0.2 Dishwasher2 0.0 0.0 0.0 0...

AI summary The table presents heat loss data by appliance type in PJ units, showing varying levels of heat loss for different appliances over time. Refrigerators, freezers, and ranges show relatively consistent heat loss, while other appliances exhibit more fluctuation.

0.5 0.6 0.7 0.7 0.7 0.7 0.7 0.7 0.9 0.9 0.9 1.0 0.9 1.0 1.1 1.2 1.2 1.3 1.3 1.4 1) Data on GHG emissions are presented excluding GHG emissions related to electricity production only. 2) Excludes hot water requirements. 3) “Other Appliances...

AI summary The text includes load forecast data for Nova Scotia's residential sector, with a table showing total households by building type and energy source from 2000 to 2019. Some data exclusions and notes are provided, such as the exclusion of GHG emissions related to electricity production and hot water requirements.

46.9 45.8 46.4 47.0 47.4 48.4 48.5 49.0 49.8 49.9 49.1 48.9 47.5 47.5 47.9 48.3 48.5 49.0 49.6 50.2 Shares (%) Electricity 25.4 25.7 25.1 25.0 25.3 25.2 25.3 25.3 25.4 25.9 26.1 26.3 26.7 26.7 26.7 26.7 26.7 26.7 26.7 26.7 Natural Gas 0.0...

AI summary The text presents statistical data on energy consumption shares by type (electricity, natural gas, heating oil, wood, and other) over a period of years, followed by a reference to a report on residential sector housing stock by building type and vintage in Nova Scotia.

Shares (%) Heating Oil – Normal Efficiency 24.2 21.6 18.8 16.4 14.5 11.9 9.7 7.5 6.1 4.3 3.0 2.6 2.2 1.8 1.1 1.0 0.5 0.2 0.3 0.0 Heating Oil – Medium Efficiency 27.7 30.3 33.5 35.8 37.4 39.8 41.8 43.7 44.8 46.1 47.2 47.8 48.2 48.9 50.3 50....

AI summary The text presents a table showing the percentage shares of different heating and energy sources over time, including Heating Oil (Normal, Medium, High Efficiency), Natural Gas (Normal, Medium, High Efficiency), Electric, Heat Pump, and Other. The data appears to track changes in usage or market share across multiple years.

Total Single Detached Heating System Stock (thousands) 255.8 257.9 260.4 263.8 266.4 269.2 271.7 274.0 276.4 278.2 280.3 282.0 283.6 285.2 286.3 287.3 288.2 290.8 292.5 294.0 (thousands) Heating Oil – Normal Efficiency 55.2 48.8 41.7 35.9...

AI summary The text presents data on the number of single detached heating systems in Nova Scotia across different efficiency categories and fuel types from 2000 to 2020, showing a gradual shift from heating oil to natural gas and electric systems, with increasing efficiency levels over time.

Shares (%) Heating Oil – Normal Efficiency 21.6 18.9 16.0 13.6 11.6 8.9 6.6 4.4 3.0 1.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Heating Oil – Medium Efficiency 27.8 30.4 33.6 36.0 37.6 40.1 42.0 44.0 45.1 46.3 47.3 47.6 47.7 48.0 49.0 49.0...

AI summary The text presents a table showing the share percentages of different heating and energy sources over time, highlighting trends in efficiency and usage for heating oil, natural gas, electric, and heat pump systems.

(thousands) 24.8 25.0 25.3 25.9 26.3 26.8 27.4 27.9 28.4 28.9 29.5 30.1 30.7 31.3 31.8 32.2 32.6 33.5 34.1 34.7 Type (thousands) Heating Oil – Normal Efficiency 6.6 6.1 5.4 4.9 4.5 3.8 3.2 2.7 2.3 1.8 1.4 1.0 0.7 0.5 0.0 0.0 0.0 0.0 0.0 0....

AI summary The text presents data in thousands, showing trends for various energy types including Heating Oil (Normal, Medium, High Efficiency), Natural Gas (Normal, Medium, High Efficiency), Electric, and Heat Pump usage over time, with values decreasing and increasing respectively.

Shares (%) Heating Oil – Normal Efficiency 26.5 24.3 21.5 18.9 16.9 14.2 11.8 9.7 8.1 6.2 4.7 3.4 2.4 1.6 0.0 0.0 0.0 0.0 0.0 0.0 Heating Oil – Medium Efficiency 28.9 31.1 34.3 36.8 38.5 41.0 43.1 45.1 46.3 47.7 49.0 50.1 50.9 51.6 53.4 53...

AI summary The text presents share percentages for various heating and energy sources over time, indicating trends in usage efficiency and distribution across different categories such as Heating Oil, Natural Gas, Electric, and Heat Pumps. It highlights changes in efficiency levels and their corresponding market shares.

(thousands) 15.2 15.4 15.5 15.7 15.8 16.0 16.2 16.3 16.4 16.5 16.6 16.7 16.8 16.9 17.0 17.0 17.1 17.2 17.3 17.4 (thousands) Heating Oil – Normal Efficiency 4.4 4.0 3.6 3.3 3.0 2.6 2.3 2.0 1.8 1.5 1.3 1.1 1.0 0.8 0.4 0.4 0.1 0.0 0.0 0.0 Hea...

AI summary The table presents data on the usage of various heating fuels and electricity over time, showing trends in consumption for different efficiency levels of heating oil, natural gas, and electric heating. The data indicates a decline in the use of heating oil with normal efficiency and an increase in the use of medium efficiency heating oil.

Shares (%) Heating Oil – Normal Efficiency 28.9 26.1 23.4 21.0 19.1 16.5 14.4 12.3 11.0 9.3 7.9 6.8 6.0 5.0 2.6 2.3 0.7 0.0 0.0 0.0 Heating Oil – Medium Efficiency 27.1 30.0 33.3 35.7 37.4 39.9 41.9 43.9 45.0 46.3 47.6 48.6 49.4 50.3 52.7...

AI summary The text presents a table showing the distribution of heating sources over time, with percentages for various heating methods such as Heating Oil (Normal, Medium, and High Efficiency), Natural Gas (Normal, Medium, and High Efficiency), Electric, Heat Pump, and Other. The data indicates a decline in the use of heating oil and an increase in electric and natural gas usage over the years.

21.2 24.0 24.1 20.6 15.8 18.6 19.1 22.2 20.3 22.3 22.6 22.6 23.4 23.5 23.8 24.2 24.3 24.6 24.8 24.9 New Unit Efficiencies Room (EER)1 9.4 9.4 9.4 9.4 9.4 9.4 10.9 10.9 10.9 10.9 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0 12.0 Central (SE...

AI summary The text presents data on new unit and stock efficiencies for room and central air conditioning units, along with unit capacity ratios in Btu/hour. The data includes Energy Efficiency Ratios (EER) and Seasonal Energy Efficiency Ratios (SEER) for different years, indicating improvements in efficiency over time.

873 32,372 31,873 31,872 31,884 31,886 33,236 33,225 33,225 33,220 33,215 33,213 33,208 33,205 33,202 1) Energy Efficiency Ratio. 2) Seasonal Energy Efficiency Ratio. Office of Energy Efficiency, Demand Policy and Analysis Division, Market...

AI summary The document includes numerical data and a table detailing water heater stock by building type and energy source in Nova Scotia from 2000 to 2019. It also references the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group, and mentions the 2023 Load Forecast Report from Synapse.

3.4 3.3 3.1 2.9 2.8 2.9 2.8 2.8 2.8 2.7 2.7 2.7 2.6 2.5 2.5 2.5 2.4 2.4 2.4 2.4 1) “Other” includes coal and propane. Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group. REDACTED (CONFIDENTIAL INFORMATI...

AI summary The document contains a table showing the appliance stock by appliance type and energy source in Nova Scotia from 2000 to 2019. The data includes a row labeled 'Other' which encompasses coal and propane. The table is part of the 2023 Load Forecast Report from Synapse IR-6 Attachment 1.

12.89 13.50 13.89 14.48 14.78 15.41 15.76 16.02 16.27 16.24 16.42 16.80 17.19 17.53 17.98 18.26 18.69 19.05 19.49 19.92 Stock of Natural Gas Appliances (thousands) Clothes Dryer 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0...

AI summary The text presents statistical data on the stock of natural gas appliances and their distribution per household over time, including clothes dryers and ranges. It also references a load forecast report and mentions the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

Single Detached (GJ/household) Before 1946 100.2 101.5 102.8 104.1 105.5 106.8 108.1 109.5 111.0 112.5 114.0 115.5 116.2 116.9 117.6 118.3 118.3 118.3 118.3 118.3 1946–1960 79.5 80.0 80.5 81.1 81.6 82.1 82.5 83.0 83.5 84.0 84.5 85.0 85.5 8...

AI summary The text presents a table showing energy consumption data for single detached homes in Nova Scotia across different time periods, with varying rates of energy use per household.

Mobile Homes (GJ/household) Before 1946 87.6 88.2 88.8 89.4 90.0 90.5 91.0 91.6 92.1 92.6 93.2 93.7 94.3 94.9 95.4 96.0 96.0 96.0 96.0 96.0 1946–1960 53.5 53.9 54.3 54.6 54.9 55.3 55.6 55.9 56.3 56.6 56.9 57.2 57.6 57.9 58.3 58.6 58.6 58.6...

AI summary The text presents data on energy consumption (in GJ/household) for mobile homes across different time periods, showing a decline in energy use over time, with significant reductions observed from the 1946–1960 period onward.

40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 40.2 2011–2015 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 40.8 40.8 40.8 40.8 40.8 40.8 40.8 40.8 40.8 2016–2019 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 41.5 41.5 41.5 41.5 O...

AI summary The document presents a table showing gross output thermal requirements per square metre by building type and vintage in Nova Scotia from 2000 to 2019. The table includes data for multiple years, but most entries are zero, with some non-zero values appearing in later years.

2 Single Detached (GJ/m ) Before 1946 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.7 1946–1960 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 0.6 1961–1977 0.5 0.5 0.5 0.5 0.5 0...

AI summary The text presents energy consumption data for single detached homes in Nova Scotia, categorized by construction years and measured in gigajoules per month. The data shows a decreasing trend in energy use over time, with significant drops in the 1996–2000 and 2001–2005 periods, and a notable absence of data for 2016–2019.

Apartments (GJ/m2) Before 1946 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 1946–1960 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 0.4 1961–1977 0.4 0.4 0.4 0.4 0.4 0.4 0.4...

AI summary The text presents a table showing energy consumption (in GJ/m2) for apartments across different time periods, indicating a decreasing trend in energy use over time, with some periods showing no energy consumption.

Mobile Homes (GJ/m2) Before 1946 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1.0 1946–1960 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 0.9 1961–1977 0.8 0.8 0.8 0.8 0.8 0.8 0....

AI summary The text presents data on energy consumption (in GJ/m2) for mobile homes across different time periods, showing a decline in energy use over time, with significant drops beginning in the 1980s and continuing through the 2010s.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Single Detached Energy Use (PJ) 32.6 34.3 35.2 32.9 31.2 29.8 30.3 34.7 35.0 35.8 35.7 38.2 33.9 33.0 31.4 32.4 29.1 29.7 31.3 31.4 E...

AI summary The table presents total single detached energy use in Nova Scotia from 2000 to 2019, showing fluctuations in energy use by source, including electricity, natural gas, heating oil, and other sources like wood. Energy use varies annually, with notable changes in consumption patterns over time.

13.1 11.1 10.0 9.5 11.8 12.9 12.9 14.4 14.0 14.7 13.3 13.6 15.1 17.8 18.1 19.8 19.9 18.7 18.8 18.3 Activity 2 Total Floor Space (million m ) 35.2 35.7 36.3 37.0 37.7 38.3 39.0 39.6 40.2 40.8 41.3 41.9 42.3 42.8 43.2 43.5 43.8 44.4 44.8 45....

AI summary The text presents statistical data on energy intensity and related metrics over time, including total floor space, total households, and energy intensity measured in GJ per square meter and per household. These figures illustrate trends in energy usage and residential growth.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 Shares (%) Electricity – – – – – – – – – – – – – – – – – – – – Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.0 0.6 0.3 0.4 0.6 0.7 0.8 1.0 1.0 1.1 1.2 Heat...

AI summary The document presents data on the distribution of energy sources and their corresponding greenhouse gas (GHG) intensity over time. It shows the percentage shares of electricity, natural gas, heating oil, other fuels, and wood, along with GHG intensity measurements in tonnes per terajoule (TJ) for each period.

42.4 42.9 43.3 42.4 39.5 37.6 38.8 40.6 40.7 40.5 41.7 42.6 39.7 36.7 35.3 35.2 32.3 32.5 33.3 33.3 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The text presents data on heating and cooling degree-day indices and GHG emissions for Nova Scotia, excluding emissions from electricity production. It includes a table showing secondary energy use and GHG emissions by end-use in the residential sector from 2000 to 2019.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Single Detached Energy Use (PJ) 32.6 34.3 35.2 32.9 31.2 29.8 30.3 34.7 35.0 35.8 35.7 38.2 33.9 33.0 31.4 32.4 29.1 29.7 31.3 31.4 E...

AI summary The table presents total single detached energy use and energy use by end-use in Nova Scotia from 2000 to 2019. It shows energy use in petajoules (PJ) for categories such as space heating, water heating, appliances, lighting, and space cooling over the years.

242.9 244.9 247.4 249.9 252.1 253.9 255.5 257.6 260.8 263.7 261.8 262.7 264.0 263.8 266.1 268.0 269.2 271.7 274.8 277.9 Energy Intensity (GJ/m2) 0.93 0.96 0.97 0.89 0.83 0.78 0.78 0.88 0.87 0.88 0.87 0.91 0.80 0.77 0.73 0.74 0.67 0.67 0.70...

AI summary The text presents numerical data on energy intensity in Nova Scotia, measured in GJ per square meter and GJ per household across multiple years. The data shows fluctuations in energy intensity over time, indicating changes in energy consumption patterns.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Space Heating 80.9 80.6 80.9 80.9 81.7 80.8 78.8 78.5 81.5 82.3 80.5 81.5 80.0 81.3 83.3 84.5 83.6 84.6 83.1 83.6 Water Heating 19.1 19.4 19.1 19.1...

AI summary The text presents data on energy usage distribution across various categories such as space heating, water heating, and appliances, along with greenhouse gas (GHG) intensity measurements over time. The data shows fluctuations in energy consumption percentages and GHG emissions per unit of energy.

42.4 42.9 43.3 42.4 39.5 37.6 38.8 40.6 40.7 40.5 41.7 42.6 39.7 36.7 35.3 35.2 32.3 32.5 33.3 33.3 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The text presents statistical data on energy use and GHG emissions in the residential sector of Nova Scotia from 2000 to 2019. It includes metrics such as heating and cooling degree-day indices, secondary energy use, and GHG emissions by energy source. The data excludes emissions related to electricity production.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Single Attached Energy Use (PJ) 2.7 2.8 2.9 2.7 2.6 2.5 2.5 2.9 3.0 3.1 3.1 3.4 3.1 3.0 2.9 3.0 2.8 2.8 3.0 3.1 Energy Use by Energy...

AI summary This table presents the total single attached energy use and energy use by energy source in Nova Scotia from 2000 to 2019. Electricity and heating oil are the primary energy sources, with heating oil showing a decline over time, while electricity use remains relatively stable.

0.4 0.4 0.3 0.3 0.3 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.6 0.6 Shares (%) Electricity 32.6 33.3 33.7 35.4 37.9 39.7 38.0 34.4 34.6 34.3 33.8 32.7 35.9 38.5 40.5 39.5 43.4 44.0 42.9 43.2 Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The text presents a table with data on energy consumption shares and activity metrics over time. It includes percentages for electricity, natural gas, heating oil, other fuels, and wood, as well as total floor space and total households in thousands. The data spans multiple years, showing trends and changes in energy usage and population growth.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity – – – – – – – – – – – – – – – – – – – – Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.6 0.3 0.4 0.6 0.7 0.8 0.9 1.0 1.0 1.1 Heat...

AI summary The text presents data on the distribution of shares among different energy sources (Natural Gas, Heating Oil, Wood, and Others) over time, along with GHG Intensity measurements in tonnes per TJ. The data shows fluctuations in the share of each energy source and a general decline in GHG Intensity over the years.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Single Attached Energy Use (PJ) 2.7 2.8 2.9 2.7 2.6 2.5 2.5 2.9 3.0 3.1 3.1 3.4 3.1 3.0 2.9 3.0 2.8 2.8 3.0 3.1 Energy Use by End-Use...

AI summary The document presents historical data on total single attached energy use and energy use by end-use in Nova Scotia from 2000 to 2019, showing fluctuations in energy consumption across various sectors such as space heating, water heating, appliances, and lighting.

ands) 23.5 24.0 24.5 25.0 25.5 25.9 26.3 26.8 27.4 27.9 27.9 28.3 28.6 28.8 29.3 29.7 30.1 30.6 31.1 31.7 Energy Intensity (GJ/m2) 0.82 0.85 0.86 0.79 0.74 0.69 0.69 0.77 0.76 0.77 0.76 0.80 0.70 0.67 0.63 0.64 0.58 0.57 0.60 0.59 Energy I...

AI summary The text presents data on energy intensity in Nova Scotia, measured in both GJ per square meter and GJ per household, over a time series from 23.5 to 31.7. The data shows fluctuations in energy intensity, indicating changes in energy consumption patterns over time.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Space Heating 75.9 75.3 75.4 75.4 76.8 76.3 74.5 74.7 77.4 77.6 74.6 75.0 73.1 74.8 77.1 78.1 77.2 78.5 76.6 77.3 Water Heating 24.1 24.7 24.6 24.6...

AI summary The text presents data on energy usage distribution across different categories such as space heating, water heating, and appliances, along with GHG intensity measurements over time. The data indicates fluctuations in energy consumption percentages and greenhouse gas emissions intensity across various periods.

40.6 41.1 41.4 40.5 37.5 35.6 36.8 38.6 38.7 38.5 39.7 40.4 37.6 34.4 32.7 32.6 29.9 30.0 30.8 30.9 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The text presents data on heating and cooling degree-day indices, GHG emissions, and energy use in the residential sector of Nova Scotia, including tables with historical data from 2000 to 2019. The data excludes GHG emissions related to electricity production and is sourced from the Office of Energy Efficiency.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Apartments Energy Use (PJ) 4.8 5.1 5.2 4.9 4.7 4.5 4.7 5.4 5.3 5.4 5.5 5.9 5.4 5.2 4.9 5.1 4.7 4.8 5.1 5.2 Energy Use by Energy Sourc...

AI summary The text presents a table showing the total energy use in apartments in Nova Scotia from 2000 to 2019, with data broken down by energy source including electricity, natural gas, heating oil, other, and wood. The table highlights trends in energy consumption over time.

sehold) 61.0 64.1 65.1 60.4 57.3 55.0 56.3 63.9 62.6 63.2 65.0 68.8 62.2 60.8 56.9 57.7 53.2 53.9 56.9 56.6 Total Apartments GHG Emissions Excluding Electricity (Mt of CO2e) 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0...

AI summary The text presents numerical data on total apartments GHG emissions excluding electricity and emissions by energy source over a series of years. The data shows minimal changes in emissions, with the majority attributed to heating oil.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity – – – – – – – – – – – – – – – – – – – – Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.9 0.6 0.3 0.4 0.6 0.7 0.9 1.0 1.1 1.1 1.3 Heat...

AI summary The text presents data on the distribution of shares and GHG intensity across various energy sources over time. It shows the percentage distribution of electricity, natural gas, heating oil, other, and wood, along with GHG intensity measurements in tonnes per TJ for each year.

39.0 39.5 39.8 39.0 36.1 34.2 35.6 37.5 37.7 37.7 39.1 39.9 36.9 33.7 31.8 31.7 28.6 28.6 29.4 29.2 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The document presents data on heating and cooling degree-day indices, GHG emissions, and energy use in the residential sector in Nova Scotia from 2000 to 2019, excluding emissions from electricity production. It includes data on energy use by end-use in apartments.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Apartments Energy Use (PJ) 4.8 5.1 5.2 4.9 4.7 4.5 4.7 5.4 5.3 5.4 5.5 5.9 5.4 5.2 4.9 5.1 4.7 4.8 5.1 5.2 Energy Use by End-Use (PJ)...

AI summary The table presents total apartment energy use and energy use by end-use in Nova Scotia from 2000 to 2019. It shows energy consumption in petajoules (PJ) for categories such as space heating, water heating, appliances, and lighting. Energy use fluctuated over the years, with space heating being the largest contributor.

usehold) 61.0 64.1 65.1 60.4 57.3 55.0 56.3 63.9 62.6 63.2 65.0 68.8 62.2 60.8 56.9 57.7 53.2 53.9 56.9 56.6 Total Apartments GHG Emissions Excluding Electricity (Mt of CO2e) 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2...

AI summary The text presents numerical data on household energy use and greenhouse gas (GHG) emissions from apartments, excluding electricity. It outlines emissions by end-use categories such as space heating and water heating, with consistent values across years, indicating stable emissions levels.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Space Heating 65.5 65.1 65.5 65.7 67.3 66.4 63.9 63.8 67.6 68.2 65.0 65.8 63.4 65.5 68.4 70.4 69.1 70.8 68.5 69.3 Water Heating 34.5 34.9 34.5 34.3...

AI summary The text presents data on energy usage distribution across different categories such as space heating, water heating, and appliances, along with GHG intensity measurements over time. The data shows fluctuations in energy consumption percentages and greenhouse gas emissions intensity.

) 39.0 39.5 39.8 39.0 36.1 34.2 35.6 37.5 37.7 37.7 39.1 39.9 36.9 33.7 31.8 31.7 28.6 28.6 29.4 29.2 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degr...

AI summary The text presents data on Heating and Cooling Degree-Day Index values and GHG emissions data for Nova Scotia, excluding electricity production emissions. It is part of a 2023 Load Forecast Report by the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Mobile Homes Energy Use (PJ) 1.8 1.9 1.9 1.8 1.7 1.6 1.6 1.9 1.9 1.9 1.9 2.0 1.8 1.7 1.6 1.7 1.5 1.5 1.6 1.6 Energy Use by Energy Sou...

AI summary The text presents a table showing the total energy use in mobile homes in Nova Scotia from 2000 to 2019, with data broken down by energy source including electricity, natural gas, heating oil, other, and wood. The data indicates fluctuations in energy use over time, with heating oil and wood being the primary sources.

0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.3 0.3 0.3 0.3 Shares (%) Electricity 29.3 29.8 29.9 31.4 33.8 35.5 33.7 30.3 30.4 29.9 29.3 28.0 31.2 33.8 35.8 34.9 39.0 39.7 38.6 38.8 Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The text provides statistical data on energy consumption shares and activity metrics such as total floor space and total households over time. The data includes percentages for electricity, natural gas, heating oil, and other energy sources, along with corresponding figures for total floor space and household numbers in thousands.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity – – – – – – – – – – – – – – – – – – – – Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 1.1 0.6 0.4 0.4 0.7 0.8 1.0 1.2 1.2 1.3 1.5 Heat...

AI summary The document presents data on the distribution of energy sources and greenhouse gas (GHG) intensity over time. It shows the percentage shares of electricity, natural gas, heating oil, other fuels, and wood, along with corresponding GHG intensity measurements in tonnes per terajoule (TJ). The data indicates a shift in fuel usage and a decrease in GHG intensity over the years.

43.3 43.9 44.3 43.6 40.7 38.8 40.2 41.9 42.1 42.0 43.2 44.0 41.3 38.0 36.2 36.0 32.9 32.9 33.8 33.8 Heating Degree-Day Index 0.94 0.94 0.97 0.99 1.02 0.94 0.83 0.81 0.99 1.02 0.89 0.95 0.83 0.87 0.98 1.04 0.96 1.04 0.96 1.00 Cooling Degree...

AI summary The text presents numerical data on energy use and GHG emissions for residential mobile homes in Nova Scotia across multiple years, including Heating and Cooling Degree-Day Indices and a table summarizing energy use and emissions by end-use from 2000 to 2019.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Mobile Homes Energy Use (PJ) 1.8 1.9 1.9 1.8 1.7 1.6 1.6 1.9 1.9 1.9 1.9 2.0 1.8 1.7 1.6 1.7 1.5 1.5 1.6 1.6 Energy Use by End-Use (P...

AI summary The text presents a table showing total energy use by mobile homes in Nova Scotia from 2000 to 2019, with data broken down by end-use categories such as space heating, water heating, appliances, and lighting. The data indicates fluctuations in energy use over time, with space heating being the largest contributor.

14.5 14.5 14.5 14.6 14.6 14.7 14.7 14.7 14.8 14.9 14.7 14.7 14.6 14.6 14.6 14.6 14.6 14.7 14.8 14.9 Energy Intensity (GJ/m2) 1.30 1.35 1.36 1.24 1.16 1.09 1.09 1.24 1.24 1.25 1.22 1.28 1.11 1.06 1.00 1.02 0.90 0.91 0.95 0.94 Energy Intensi...

AI summary The text presents numerical data on energy intensity measured in GJ per square meter and GJ per household across multiple time points, showing fluctuations over time.

End Use Table 8: Transportation and Warehousing Secondary Energy Use and GHG Emissions by Energy Source Table 9: Transportation and Warehousing Secondary Energy Use and GHG Emissions by End Use Table 10: Information and Cultural Industries...

AI summary The text presents a series of tables detailing secondary energy use and GHG emissions across various sectors, including transportation, warehousing, offices, education, health care, and others, categorized by energy source and end use. These tables are part of a load forecast report from the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

es Non-Space Conditioning Secondary Energy Use by End Use and by Energy Source Table 42: Information and Cultural Industries Space Conditioning Secondary Energy Use by End Use and by Energy Source Office of Energy Efficiency, Demand Policy...

AI summary The document contains multiple tables detailing secondary energy use by end use and energy source across various sectors, including offices, educational services, health care, and others. It also notes that GHG emissions data excludes emissions related to electricity production.

Table 54: Other Services Space Conditioning Secondary Energy Use by End Use and by Energy Source 1) Data on GHG emissions are presented excluding GHG emissions related to electricity production. Office of Energy Efficiency, Demand Policy a...

AI summary The text includes a table presenting data on secondary energy use and GHG emissions by energy source for the Commercial/Institutional Sector in Atlantic Canada, with a note that GHG emissions related to electricity production are excluded. It also references the 2023 Load Forecast Report and mentions the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use (PJ) 57.2 58.4 57.6 61.8 67.6 63.0 56.3 63.6 60.6 54.3 52.7 61.6 59.5 54.7 60.1 61.5 59.3 57.4 55.5 56.3 Energy Use by Ene...

AI summary The text presents a table showing total energy use and energy use by source in Nova Scotia from the year 2000 to 2019. It includes data on electricity, natural gas, light fuel oil, heavy fuel oil, steam, and other energy sources measured in petajoules (PJ).

pace (million m2) 41.9 42.7 43.1 43.8 44.4 45.1 45.8 46.3 46.8 47.4 47.8 48.3 48.9 49.2 49.2 49.2 49.1 49.3 49.3 49.0 Energy Intensity3 (GJ/m2) 1.35 1.35 1.32 1.39 1.50 1.38 1.21 1.35 1.28 1.13 1.08 1.26 1.20 1.09 1.20 1.23 1.19 1.15 1.11...

AI summary The text presents data on building floor space and energy intensity over time, showing a gradual increase in floor space and fluctuating energy intensity levels.

0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.2 GHG Intensity (tonne/TJ) 33.5 33.8 32.1 33.9 36.9 35.6 35.4 32.9 30.4 25.8 27.1 30.9 29.2 28.1 26.8 27.9 25.2 23.3 20.1 20.8 Heating Degree-Day Index 0.95 0.95...

AI summary The text provides data on GHG intensity and degree-day indices across multiple years, along with footnotes explaining data exclusions. It also references a 2023 Load Forecast Report and mentions the Commercial/Institutional Sector and a table on energy use and emissions by end use.

1.2 1.3 1.2 1.4 1.1 1.2 1.3 1.4 1.5 1.7 1.8 1.5 1.5 1.6 1.5 1.3 1.3 1.3 1.3 1.3 Activity Total Floor Space (million m 2) 41.9 42.7 43.1 43.8 44.4 45.1 45.8 46.3 46.8 47.4 47.8 48.3 48.9 49.2 49.2 49.2 49.1 49.3 49.3 49.0 Energy Intensity2...

AI summary The text presents data on total floor space and energy intensity over time, showing trends in building activity and energy usage. The figures indicate fluctuations in both metrics, with energy intensity decreasing in some periods and increasing in others.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 33.5 33.8 32.1 33.9 36.9 35.6 35.4 32.9 30.4 25.8 27.1 30.9 29.2 28.1 26.8 27.9 25.2 23.3 20.1 20.8 Heating Degree-Day Index 0.95 0.95...

AI summary The text provides data on GHG emissions intensity and degree-day indices for various years, excluding electricity production and street lighting. It references the Office of Energy Efficiency and a load forecast report, indicating a focus on energy use and emissions in the commercial/institutional sector.

Total Energy Use (PJ) 57.2 58.4 57.6 61.8 67.6 63.0 56.3 63.6 60.6 54.3 52.7 61.6 59.5 54.7 60.1 61.5 59.3 57.4 55.5 56.3 Energy Use by Activity Type 2 (PJ) Wholesale Trade 3.3 3.3 3.3 3.4 4.0 3.6 3.2 3.7 3.5 3.1 2.8 3.5 3.4 3.1 3.4 3.4 3....

AI summary The text presents data on total energy use across various sectors in Nova Scotia, including Wholesale Trade, Retail Trade, Transportation and Warehousing, Information and Cultural Industries, Offices, and Educational Services, with energy use measured in petajoules (PJ) over multiple years.

33.5 33.8 32.1 33.9 36.9 35.6 35.4 32.9 30.4 25.8 27.1 30.9 29.2 28.1 26.8 27.9 25.2 23.3 20.1 20.8 Heating Degree-Day Index 0.95 0.95 0.99 0.98 1.02 0.94 0.85 0.92 0.97 0.99 0.87 0.93 0.80 0.86 0.97 1.03 0.94 1.03 0.95 0.99 Cooling Degree...

AI summary The text provides statistical data on heating and cooling degree-day indexes, along with GHG emissions data and energy use information, primarily for the commercial/institutional sector in Atlantic Canada, with a focus on Nova Scotia. It references a 2023 Load Forecast Report and mentions data exclusions related to electricity production and street lighting.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Wholesale Trade (PJ) 3.3 3.3 3.3 3.4 4.0 3.6 3.2 3.7 3.5 3.1 2.8 3.5 3.4 3.1 3.4 3.4 3.3 3.1 3.0 3.0 Energy Use by Ene...

AI summary The table presents historical data on total energy use for wholesale trade in Nova Scotia from 2000 to 2019, broken down by energy source. It shows fluctuations in energy consumption across electricity, natural gas, fuel oils, and other sources over the years.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Wholesale Trade (PJ) 3.3 3.3 3.3 3.4 4.0 3.6 3.2 3.7 3.5 3.1 2.8 3.5 3.4 3.1 3.4 3.4 3.3 3.1 3.0 3.0 Energy Use by End...

AI summary The table presents total energy use for wholesale trade and energy use by end use in PJ from 2000 to 2019. It shows fluctuations in energy consumption across various categories such as space heating, water heating, and lighting over time.

Cooling 0.2 0.3 0.2 0.3 0.2 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.3 Shares (%) Space Heating 53.1 52.1 53.5 50.2 57.1 52.0 50.9 54.7 51.0 46.1 40.5 49.3 49.0 48.2 49.0 49.3 48.1 47.9 41.9 44.4 Water Heating 5.6 5.3 5.2...

AI summary The text presents data on energy consumption distribution across various categories, including cooling, heating, and lighting, along with energy intensity metrics and floor space measurements over time. It outlines the percentage shares of different energy uses and provides numerical values for analysis.

Cooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 31.7 32.6 30.3 31.9 36.1 34.7 35.4 30.7 27.0 20.9 21.4 24.9 25.3 24.2 21.7 22.8 21.1 17.8 14.9 15.4 1) Data on GHG emissions a...

AI summary The text provides data on GHG intensity and energy use in the commercial/institutional sector, including a table with historical energy use and GHG emissions data from 2000 to 2019. It also notes that data excludes electricity production-related emissions.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Retail Trade (PJ) 8.4 8.8 8.7 9.2 10.9 10.6 9.5 11.0 10.4 9.2 8.4 10.3 10.3 9.4 10.2 10.5 10.1 9.6 9.2 9.3 Energy Use...

AI summary The text provides a table showing total energy use for retail trade in Nova Scotia from 2000 to 2019, broken down by energy source. It includes data for electricity, natural gas, light fuel oil, heavy fuel oil, steam, and other energy sources, measured in petajoules (PJ).

0.9 1.2 1.1 1.0 1.0 0.9 1.0 1.1 1.3 1.3 1.1 1.0 0.8 0.7 0.8 0.9 0.9 0.7 0.5 0.5 Shares (%) Electricity 56.3 54.6 57.7 55.3 49.7 49.5 47.7 54.6 58.4 66.0 64.8 58.7 58.8 58.2 63.3 60.7 62.0 67.0 71.4 70.6 Natural Gas 0.0 0.0 0.0 1.4 2.0 3.7...

AI summary The text presents a series of numerical data tables showing energy consumption shares and floor space activity over time, with percentages and values for different energy sources and metrics. The data appears to be related to energy usage and infrastructure activity, but the context and discussion themes are not explicitly detailed.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 30.2 31.0 28.8 30.5 34.7 34.6 35.7 30.9 27.2 21.0 21.5 25.1 25.5 24.2 21.8 23.3 21.7 18.1 15.2 15.6 1) Data on GHG emissions are prese...

AI summary The text presents data on GHG emissions and energy use in the commercial/institutional sector, specifically in the retail trade category, with values provided for various years. The data excludes electricity production-related emissions and includes 'Other' categories such as coal and propane.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Retail Trade (PJ) 8.4 8.8 8.7 9.2 10.9 10.6 9.5 11.0 10.4 9.2 8.4 10.3 10.3 9.4 10.2 10.5 10.1 9.6 9.2 9.3 Energy Use...

AI summary The document presents a table showing total energy use and energy use by end use in the retail trade sector from 2000 to 2019, with data measured in petajoules (PJ). It outlines trends in energy consumption across categories such as space heating, water heating, and lighting over time.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Transportation and Warehousing (PJ) 2.4 2.4 2.4 2.3 2.7 2.4 2.1 2.3 2.2 1.9 1.8 2.3 2.2 2.0 2.2 2.2 2.1 2.1 1.9 2.0 En...

AI summary The text presents historical data on total energy use for transportation and warehousing in Nova Scotia from 2000 to 2019, categorized by energy source. It shows fluctuations in energy use across different sources such as electricity, natural gas, and various types of fuel oil.

0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.1 0.1 Shares (%) Electricity 50.1 47.6 52.0 50.5 45.1 46.6 45.3 53.9 57.5 65.1 63.2 57.4 57.6 56.2 62.2 60.0 60.5 67.5 72.1 71.2 Natural Gas 0.0 0.0 0.0 1.7 2.2 4.1...

AI summary The text presents data on energy consumption and intensity over time, showing the distribution of electricity, natural gas, and other fuels, along with floor space and energy intensity metrics. The data reflects trends in energy use and efficiency across different periods.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 34.6 35.9 32.8 33.8 37.9 36.7 37.5 31.4 27.9 21.5 22.5 25.9 26.2 25.5 22.6 23.8 22.7 17.8 14.8 15.2 1) Data on GHG emissions are prese...

AI summary The text provides data on GHG emissions and energy use in the commercial/institutional sector, specifically focusing on transportation and warehousing. It includes a table showing secondary energy use and GHG emissions by end use from 2000 to 2019, with a note that data excludes electricity production-related emissions.

ooling 0.1 0.1 0.1 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Shares (%) Space Heating 62.9 61.8 62.6 57.7 63.9 58.8 57.7 60.1 57.1 52.8 47.2 56.0 55.8 55.1 55.6 55.5 54.5 52.6 47.1 49.5 Water Heating 3.0 2.8 2.8 3...

AI summary The text presents data on energy consumption distribution across different categories such as space heating, water heating, and lighting, along with energy intensity metrics over time. It includes percentages of energy use by category and floor space in million square meters, with energy intensity measured in GJ per square meter.

ooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 34.6 35.9 32.8 33.8 37.9 36.7 37.5 31.4 27.9 21.5 22.5 25.9 26.2 25.5 22.6 23.8 22.7 17.8 14.8 15.2 1) Data on GHG emissions ar...

AI summary The text provides data on GHG emissions intensity and excludes emissions related to electricity production. It also references a 2023 Load Forecast Report by Synapse and mentions the Commercial/Institutional Sector and Atlantic region energy use and emissions data.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 31.1 33.4 31.2 29.4 32.1 29.1 29.6 24.4 22.9 20.3 20.8 24.3 24.3 23.4 21.0 22.5 20.9 17.2 14.4 14.8 1) Data on GHG emissions are prese...

AI summary The document presents data on GHG emissions and energy use, focusing on the Commercial/Institutional Sector in the Atlantic region. It includes a table with secondary energy use and GHG emissions by end use from 2000 to 2019. The GHG intensity data is also provided, excluding emissions related to electricity production.

ling 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 Shares (%) Space Heating 51.4 50.5 51.8 48.6 55.5 50.4 49.3 53.1 49.3 44.4 38.9 47.6 47.4 46.6 47.3 48.6 47.4 46.4 40.5 42.8 Water Heating 6.1 5.7 5.6 6.7...

AI summary The text presents data on energy consumption distribution across various categories, including space heating, water heating, and lighting, along with energy intensity metrics and floor space measurements over time. It provides a detailed breakdown of energy usage percentages and intensity in GJ/m2.

ling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 31.1 33.4 31.2 29.4 32.1 29.1 29.6 24.4 22.9 20.3 20.8 24.3 24.3 23.4 21.0 22.5 20.9 17.2 14.4 14.8 1) Data on GHG emissions are...

AI summary The text presents data on GHG emissions intensity and energy use in the commercial/institutional sector, with a focus on office buildings. It excludes emissions related to electricity production and includes a table with energy use and GHG emissions data from 2000 to 2019.

2 Total Energy Use for Offices (PJ) 18.5 18.9 18.6 21.5 19.6 19.3 17.1 19.0 18.6 17.1 18.8 19.7 17.6 16.1 17.6 18.1 17.5 17.0 16.5 16.7 Energy Use by Energy Source (PJ) Electricity 8.9 9.2 9.1 9.8 8.6 9.0 8.6 8.8 9.0 8.9 9.1 8.3 8.9 8.6 9....

AI summary The text presents a table showing total energy use for offices and energy use by energy source over a period of years, measured in petajoules (PJ). It includes data for electricity, natural gas, light fuel oil, heavy fuel oil, steam, and other energy sources.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 37.4 36.7 36.6 39.1 40.6 38.7 36.0 38.6 36.9 34.1 36.7 41.2 35.1 32.2 31.9 32.3 30.1 27.3 23.3 24.1 1) Data on GHG emissions are prese...

AI summary The text presents data on GHG emissions and energy use in the commercial/institutional sector, specifically in the offices category, across multiple years. It excludes emissions related to electricity production and includes various activities such as finance, insurance, and public administration.

Total Energy Use for Offices2 (PJ) 18.5 18.9 18.6 21.5 19.6 19.3 17.1 19.0 18.6 17.1 18.8 19.7 17.6 16.1 17.6 18.1 17.5 17.0 16.5 16.7 Energy Use by End Use (PJ) Space Heating 9.5 9.4 9.6 11.3 10.5 9.8 8.1 9.6 9.0 7.8 9.2 10.8 8.2 7.4 8.2...

AI summary The text presents energy use data for offices across multiple years, categorized by end use such as space heating, water heating, auxiliary equipment, lighting, and space cooling. It provides detailed figures in petajoules (PJ) for each category and year, highlighting fluctuations in energy consumption over time.

5.3 7.1 6.3 7.0 5.0 6.4 5.5 4.6 5.3 4.1 4.5 3.7 8.1 7.6 7.0 8.0 8.7 9.3 12.0 8.9 Activity Floor Space (million m2) 15.28 15.61 15.81 16.16 16.43 16.74 17.03 17.30 17.51 17.86 18.05 18.25 18.53 18.65 18.63 18.67 18.67 18.81 18.84 18.73 Ener...

AI summary The text presents numerical data on energy intensity and floor space over a series of time periods, indicating fluctuations in energy use and building expansion. These metrics may be relevant to energy efficiency and resource planning discussions.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 37.4 36.7 36.6 39.1 40.6 38.7 36.0 38.6 36.9 34.1 36.7 41.2 35.1 32.2 31.9 32.3 30.1 27.3 23.3 24.1 1) Data on GHG emissions are prese...

AI summary The text presents data on GHG emissions intensity and energy use in the Commercial/Institutional Sector, specifically in the Educational Services subsector, across multiple years. The data excludes emissions from electricity production and includes information on energy sources and their contribution to GHG emissions.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Educational Services (PJ) 8.3 8.4 8.2 8.6 10.4 9.2 8.1 9.1 8.5 7.6 7.1 8.7 8.6 7.9 8.8 9.1 8.8 8.6 8.3 8.4 Energy Use...

AI summary The text presents energy use data for educational services in Nova Scotia from 2000 to 2019, detailing total energy use and breakdown by energy source in petajoules (PJ). It shows fluctuations in energy consumption across different fuels over time.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 32.6 34.0 31.8 32.3 36.0 34.4 35.3 29.4 26.5 21.7 22.1 25.7 26.2 24.9 22.4 23.9 16.8 20.7 17.5 18.1 1) Data on GHG emissions are prese...

AI summary The text presents data on GHG emissions intensity and energy use in the commercial/institutional sector, specifically in educational services, across various years. It notes that data excludes electricity production emissions and includes categories like coal and propane under 'Other'.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Educational Services (PJ) 8.3 8.4 8.2 8.6 10.4 9.2 8.1 9.1 8.5 7.6 7.1 8.7 8.6 7.9 8.8 9.1 8.8 8.6 8.3 8.4 Energy Use...

AI summary The document presents a table showing total energy use and energy use by end use for educational services in Nova Scotia from 2000 to 2019, with data measured in petajoules (PJ). It includes categories such as space heating, water heating, auxiliary equipment, and lighting.

pace (million m2) 6.76 6.83 6.88 6.94 6.97 7.02 7.03 7.00 7.00 7.06 7.24 7.32 7.39 7.43 7.56 7.59 7.57 7.64 7.63 7.57 2 Energy Intensity (GJ/m ) 1.22 1.23 1.20 1.23 1.49 1.31 1.16 1.31 1.22 1.07 0.97 1.19 1.17 1.06 1.17 1.20 1.16 1.12 1.09...

AI summary The text presents data on space (in million square meters) and energy intensity (in GJ per square meter) over a time series. The data shows fluctuations in both metrics, with energy intensity varying significantly between years.

ooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 32.6 34.0 31.8 32.3 36.0 34.4 35.3 29.4 26.5 21.7 22.1 25.7 26.2 24.9 22.4 23.9 16.8 20.7 17.5 18.1 1) Data on GHG emissions ar...

AI summary The text provides GHG intensity data and energy use statistics for the Health Care and Social Assistance sector in the Commercial/Institutional sector, with data spanning from 2000 to 2019. It excludes GHG emissions related to electricity production and is part of a 2023 Load Forecast Report.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Health Care and Social Assistance (PJ) 8.5 8.6 8.4 8.5 10.2 9.2 8.3 9.3 8.7 7.7 6.8 8.6 8.8 8.3 9.3 9.5 9.2 8.7 8.5 8....

AI summary The table presents total energy use and energy use by source for the Health Care and Social Assistance sector from 2000 to 2019, measured in petajoules (PJ). Electricity, natural gas, light fuel oil, and heavy fuel oil are the primary energy sources tracked over the period.

0.0 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 33.9 33.8 30.8 33.1 37.4 35.9 36.7 34.1 31.9 26.0 24.3 29.7 31.2 32.3 32.1 32.9 30.4 28.6 26.0 26.7 1) Data on GHG emissions are prese...

AI summary The text provides data on GHG emissions intensity and energy use in the commercial/institutional sector, specifically in the health care and social assistance subsector. It includes a table with energy use and emissions data from 2000 to 2019, with a note that electricity production emissions are excluded.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Health Care and Social Assistance (PJ) 8.5 8.6 8.4 8.5 10.2 9.2 8.3 9.3 8.7 7.7 6.8 8.6 8.8 8.3 9.3 9.5 9.2 8.7 8.5 8....

AI summary The text presents energy use data for the Health Care and Social Assistance sector in Nova Scotia from 2000 to 2019, detailing total energy consumption and breakdown by end use, including space heating, water heating, auxiliary equipment, lighting, and space cooling.

ling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 33.9 33.8 30.8 33.1 37.4 35.9 36.7 34.1 31.9 26.0 24.3 29.7 31.2 32.3 32.1 32.9 30.4 28.6 26.0 26.7 1) Data on GHG emissions are...

AI summary The text presents data on GHG intensity and energy use in the Commercial/Institutional Sector, specifically in the Arts, Entertainment and Recreation sub-sector, across various years. It excludes GHG emissions related to electricity production and is part of a 2023 Load Forecast Report.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Shares (%) Electricity 53.2 50.4 53.8 52.5 47.8 49.4 48.2 57.3 59.7 65.8 64.1 58.5 57.6 57.2 62.8 59.8 60.6 66.8 70.9 70.6 Natural Gas 0.0 0.0 0.0 1.7 2.3 4.6...

AI summary The text presents data on energy consumption distribution across various fuel types over time, including percentages for electricity, natural gas, light and heavy fuel oil, and other sources. It also includes metrics such as floor space and energy intensity in GJ/m2.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 32.2 33.9 31.5 32.2 35.7 34.3 35.0 28.6 25.9 21.0 21.9 25.2 26.0 24.8 22.1 23.9 22.6 18.3 15.4 15.6 1) Data on GHG emissions are prese...

AI summary The document presents data on GHG emissions intensity and energy use in the commercial/institutional sector, focusing on the arts, entertainment, and recreation industry. It includes a table with historical data from 2000 to 2019, excluding emissions from electricity production.

ooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.0 0.0 0.1 0.1 0.1 0.1 0.1 Shares (%) Space Heating 54.3 53.9 55.0 52.0 58.4 53.8 52.4 55.9 52.3 46.9 41.6 50.1 51.1 50.0 50.6 52.2 51.1 50.2 44.8 46.4 Water Heating 5.7 5.4 5.3 6...

AI summary The text presents data on energy consumption across various categories such as space heating, water heating, and lighting, along with energy intensity metrics over time. It includes percentages of energy use by category and floor space in million square meters, providing insights into energy usage patterns.

ooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 32.2 33.9 31.5 32.2 35.7 34.3 35.0 28.6 25.9 21.0 21.9 25.2 26.0 24.8 22.1 23.9 22.6 18.3 15.4 15.6 1) Data on GHG emissions ar...

AI summary The text presents data on GHG emissions intensity and energy use in the Commercial/Institutional Sector, specifically in the Accommodation and Food Services subsector, across multiple years. The data excludes emissions related to electricity production and is part of a 2023 Load Forecast Report.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Accommodation and Food Services (PJ) 3.8 3.8 3.8 3.9 4.8 4.4 4.0 4.6 4.3 3.8 3.3 4.1 4.3 3.9 4.3 4.5 4.4 4.4 4.3 4.4 E...

AI summary The document presents historical data on total energy use and energy use by source for the Accommodation and Food Services sector from 2000 to 2019, highlighting trends in electricity, natural gas, and various fuel oils.

0.2 0.3 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Shares (%) Electricity 54.8 54.9 59.6 55.7 48.5 50.1 48.7 53.6 56.9 63.2 67.7 57.3 57.1 51.6 52.7 51.5 53.9 57.4 60.6 59.4 Natural Gas 0.0 0.0 0.0 1.2 1.7 3.1...

AI summary The text presents statistical data on energy consumption distribution across different fuel types, along with energy intensity metrics and floor space activity over time. The data includes percentages of electricity, natural gas, fuel oil, and other energy sources, alongside energy intensity measured in GJ/m2 and total floor space in million m2.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 31.9 31.8 28.3 30.8 36.2 34.7 35.8 32.3 29.8 24.9 22.0 29.4 29.2 32.1 31.5 32.5 30.6 27.8 25.2 25.9 1) Data on GHG emissions are prese...

AI summary The text presents GHG intensity data and energy use statistics for the Commercial/Institutional Sector, specifically focusing on the Accommodation and Food Services industry. The data spans from 2000 to 2019 and includes secondary energy use and GHG emissions by end use. The data excludes emissions related to electricity production and includes a note on 'Other' fuels like coal and propane.

ooling 0.2 0.3 0.3 0.4 0.3 0.4 0.3 0.3 0.3 0.2 0.3 0.2 0.4 0.4 0.4 0.4 0.5 0.5 0.6 0.5 Shares (%) Space Heating 50.6 49.5 50.7 46.2 54.4 49.6 48.7 52.3 48.5 42.7 33.7 44.5 46.1 45.5 46.3 47.5 46.3 45.4 39.5 41.9 Water Heating 7.8 7.3 7.2 8...

AI summary The text presents data on energy usage distribution across different categories such as space heating, water heating, and lighting, along with energy intensity over time. It includes percentages of energy use and floor space in million square meters, as well as energy intensity measured in gigajoules per square meter.

ooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 31.9 31.8 28.3 30.8 36.2 34.7 35.8 32.3 29.8 24.9 22.0 29.4 29.2 32.1 31.5 32.5 30.6 27.8 25.2 25.9 1) Data on GHG emissions ar...

AI summary The text presents data on GHG emissions intensity and energy use in the Commercial/Institutional Sector, specifically focusing on the Atlantic region. The data spans from 2000 to 2019 and excludes emissions related to electricity production. It is part of a 2023 Load Forecast Report by Synapse.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Other Services (PJ) 1.4 1.4 1.4 1.4 1.6 1.4 1.2 1.4 1.3 1.1 1.0 1.2 1.1 1.0 1.1 1.1 1.0 0.9 0.9 0.9 Energy Use by Ener...

AI summary The table presents total energy use for Other Services in Nova Scotia from 2000 to 2019, categorized by energy source. It shows trends in energy consumption for electricity, natural gas, fuel oil, and other sources over time.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 32.5 34.0 31.7 32.3 35.9 34.5 35.2 28.9 26.1 21.3 22.0 25.4 26.2 24.8 22.2 23.8 22.5 18.2 15.4 15.6 1) Data on GHG emissions are prese...

AI summary The document presents data on GHG emissions and energy use in the Commercial/Institutional Sector, focusing on secondary energy use and GHG emissions by end use. It includes a table with data from 2000 to 2019, excluding emissions related to electricity production, and notes that 'Other' includes coal and propane.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Energy Use for Other Services (PJ) 1.4 1.4 1.4 1.4 1.6 1.4 1.2 1.4 1.3 1.1 1.0 1.2 1.1 1.0 1.1 1.1 1.0 0.9 0.9 0.9 Energy Use by End...

AI summary The text presents a table showing total energy use for Other Services and energy use by end use in PJ from 2000 to 2019. It details the breakdown of energy consumption across categories such as space heating, water heating, lighting, and others over time.

Cooling 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Shares (%) Space Heating 54.2 53.6 54.8 51.7 58.2 53.5 52.3 55.8 52.2 46.9 41.6 50.1 50.6 49.7 50.4 51.8 50.7 49.8 44.2 46.1 Water Heating 6.1 5.7 5.6...

AI summary The text presents data on energy consumption distribution across various categories such as space heating, water heating, and lighting, along with the associated floor space in millions of square meters. The data spans multiple years, indicating trends in energy usage and building area over time.

Cooling 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 32.5 34.0 31.7 32.3 35.9 34.5 35.2 28.9 26.1 21.3 22.0 25.4 26.2 24.8 22.2 23.8 22.5 18.2 15.4 15.6 1) Data on GHG emissions a...

AI summary The document provides data on GHG emissions intensity and energy use, focusing on the Commercial/Institutional Sector and excluding electricity production emissions. It includes a table with energy use and GHG emissions data from 2000 to 2019.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Total Space Heating Energy Use (PJ) 29.0 28.9 29.2 30.2 36.4 31.5 27.2 32.8 29.3 23.9 21.5 30.1 27.6 25.0 27.9 29.4 27.6 26.4 22.3 23.8 Ene...

AI summary The text presents a table showing total space heating energy use and energy use by energy source in PJ from 2000 to 2019, highlighting fluctuations in energy consumption across different sources over time.

0.2 0.2 0.2 0.2 0.2 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 GHG Intensity (tonne/TJ) 57.1 59.5 54.6 59.4 60.0 62.0 63.4 54.6 53.2 49.2 55.6 54.0 52.2 53.2 49.6 50.7 47.5 43.7 41.3 40.8 Heating Degree-Day Index 0.95 0.95...

AI summary The text presents data on GHG emissions intensity and heating degree-day index over time, excluding electricity production emissions. It also references a table detailing space heating energy use and GHG emissions by activity type in the commercial/institutional sector for Atlantic Canada.

roduction. 2) “Offices” includes activities related to finance and insurance; real estate and rental and leasing; professional, scientific and technical services; public administration; and others. Office of Energy Efficiency, Demand Polic...

AI summary The text discusses the Commercial/Institutional Sector in the context of energy use and GHG emissions, focusing on water heating and energy sources across various years from 2000 to 2019.

1.1 1.3 1.1 1.0 0.8 0.7 0.9 0.7 1.1 1.3 1.1 0.9 0.8 0.6 0.8 0.9 0.7 0.5 0.4 0.4 Shares (%) Electricity 2.3 1.7 1.6 2.5 5.8 5.6 5.4 5.7 5.6 7.4 14.0 9.3 5.8 5.0 5.3 5.3 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 1.9 2.0 3.1 4.5 3.3 11.8 19.2 2...

AI summary The text presents numerical data showing the distribution of energy consumption across different fuel types and the total floor space over time. The data includes percentages of electricity, natural gas, light and heavy fuel oil, and other energy sources, along with the total floor space in million square meters.

m2) 41.88 42.67 43.13 43.76 44.43 45.05 45.77 46.34 46.77 47.36 47.84 48.29 48.89 49.16 49.21 49.23 49.11 49.35 49.25 48.98 2 Energy Intensity (GJ/m ) 0.07 0.07 0.07 0.08 0.09 0.08 0.07 0.08 0.07 0.06 0.07 0.08 0.08 0.06 0.07 0.07 0.06 0.0...

AI summary The text presents numerical data with two sets of values, possibly related to energy metrics such as energy intensity measured in gigajoules per square meter (GJ/m²) over a series of time points. The data appears to be part of a larger analysis or report.

0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.0 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.1 0.0 0.0 0.0 0.0 GHG Intensity (tonne/TJ) 66.2 65.7 66.0 66.1 64.5 64.6 63.8 64.4 61.7 58.1 53.4 55.4 58.6 50.6 51.1 51.0 50.5 49.5 48.3 48.4 1) Data on GHG emissions are prese...

AI summary The text presents data on GHG emissions intensity and energy use in the Commercial/Institutional Sector, focusing on water heating and activity types across various years. It excludes GHG emissions related to electricity production and includes notes on data categorization.

ent and Recreation 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.8 1.9 1.9 1.9 1.9 1.9 2.0 2.0 2.0 Accommodation and Food Services 9.4 9.4 9.5 9.5 10.0 9.7 10.0 10.1 10.1 10.1 9.8 9.9 9.9 9.9 9.8 10.1 10.1 10.6 10.7 10.8 Other Services 2.7...

AI summary The text presents data on energy consumption across various sectors, including entertainment and recreation, accommodation and food services, and other services, along with total floor space and energy intensity metrics over time.

roduction. 2) “Offices” includes activities related to finance and insurance; real estate and rental and leasing; professional, scientific and technical services; public administration; and others. Office of Energy Efficiency, Demand Polic...

AI summary This text provides a heading and context for a document that includes a table showing auxiliary equipment secondary energy use and GHG emissions by energy source for the Commercial/Institutional Sector in Atlantic Canada from 2000 to 2019.

e (million m2) 41.88 42.67 43.13 43.76 44.43 45.05 45.77 46.34 46.77 47.36 47.84 48.29 48.89 49.16 49.21 49.23 49.11 49.35 49.25 48.98 Energy Intensity (GJ/m2) 0.17 0.18 0.18 0.20 0.21 0.21 0.20 0.21 0.21 0.22 0.23 0.22 0.20 0.20 0.22 0.21...

AI summary The text presents data on energy consumption and intensity over time, showing a steady increase in energy use and fluctuating energy efficiency metrics. These metrics are likely used for analyzing energy efficiency trends and policy impacts.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.1 0.1 GHG Intensity (tonne/TJ) 7.7 7.3 7.7 7.3 7.5 7.3 7.3 7.6 7.6 5.6 5.5 5.7 5.7 5.5 5.6 5.5 3.4 6.4 6.3 6.3 1) Data on GHG emissions are presented excluding GHG e...

AI summary The text presents data on GHG emissions and energy use in the Commercial/Institutional Sector, focusing on auxiliary equipment and activity types. It includes a table with historical data from 2000 to 2019 and notes that GHG emissions related to electricity production are excluded.

Total Auxiliary Equipment Energy Use (PJ) 7.1 7.8 7.6 8.9 9.2 9.3 9.3 9.9 10.0 10.5 10.8 10.5 9.9 9.9 10.7 10.4 10.8 9.4 10.1 10.7 Energy Use by Activity Type (PJ) Wholesale Trade 0.3 0.4 0.4 0.4 0.5 0.5 0.4 0.5 0.5 0.5 0.5 0.6 0.5 0.5 0.5...

AI summary The text provides a table showing energy use by activity type in PJ units over multiple years, including categories such as wholesale trade, retail trade, transportation, offices, educational services, and health care. The data reflects energy consumption trends across different sectors.

roduction. 2) “Offices” includes activities related to finance and insurance; real estate and rental and leasing; professional, scientific and technical services; public administration; and others. Office of Energy Efficiency, Demand Polic...

AI summary The text discusses the Commercial/Institutional Sector in the context of auxiliary motors' secondary energy use and GHG emissions by activity type, as presented in Table 30 of the 2023 Load Forecast Report by Synapse IR-6 Attachment 2.

Total Auxiliary Motors Energy Use2 (PJ) 3.9 3.3 3.2 3.4 3.5 3.4 2.8 3.0 3.0 3.3 2.8 3.5 2.8 2.2 3.0 2.8 2.6 2.7 2.3 2.3 Energy Use by Activity Type (PJ) Wholesale Trade 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.1 0.2 0.2 0.2 0....

AI summary The text provides a detailed breakdown of energy use by activity type in PJ units over multiple years, showing variations in energy consumption across sectors such as Wholesale Trade, Retail Trade, Transportation, and Offices. The data highlights fluctuations in energy use, with some sectors showing consistent usage while others exhibit notable changes.

9 13.8 13.7 Arts, Entertainment and Recreation 1.8 1.9 1.9 1.9 1.9 1.9 1.9 1.9 1.9 2.0 2.0 2.0 2.0 2.0 2.1 2.1 2.1 2.2 2.2 2.2 Accommodation and Food Services 6.8 6.8 6.8 6.8 7.2 7.3 7.5 7.5 7.5 7.5 7.4 7.4 7.4 7.4 7.4 7.5 7.6 8.0 8.1 8.2...

AI summary The text presents statistical data on energy use and related metrics across various sectors, including arts, entertainment, accommodation, and other services, along with floor space and energy intensity measurements. The data includes energy intensity and greenhouse gas emissions, but some values are missing or not applicable.

– – – – – – – – – – – – – – – – – – – – 1) Data on GHG emissions are presented excluding GHG emissions related to electricity production. 2) Auxilliary motors consumes only electricity 3) “Offices” includes activities related to finance an...

AI summary The text provides data on GHG emissions and energy use in the commercial/institutional sector, focusing on lighting and excluding electricity production emissions. It includes a table with secondary energy use and GHG emissions by activity type from 2000 to 2019.

– – – – – – – – – – – – – – – – – – – – 1) Data on GHG emissions are presented excluding GHG emissions related to electricity production. 2) Lighting consumes only electricity and does not include street lighting. 3) “Offices” includes act...

AI summary The text provides a note that data on GHG emissions excludes electricity production emissions and clarifies that lighting data does not include street lighting. It also defines 'Offices' as including various professional and administrative activities. The document is part of a 2023 Load Forecast Report and includes a table on space cooling energy use and GHG emissions by energy source in the Commercial/Institutional Sector in Atlantic Canada.

Total Space Cooling Energy Use (PJ) 3.0 4.2 3.7 4.6 3.5 4.6 3.4 3.1 3.6 2.5 3.0 2.6 5.0 4.4 4.4 5.1 5.4 5.5 6.9 5.2 Energy Use by Activity Type (PJ) Wholesale Trade 0.2 0.3 0.2 0.3 0.2 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0....

AI summary The text presents data on total space cooling energy use and energy use by activity type in PJ units across various years. It includes figures for different sectors such as wholesale trade, retail trade, transportation, offices, educational services, and health care.

.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Health Care and Social Assistance 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Arts, Entertainment and Recreation 0.0 0.0 0.0 0.0 0.0...

AI summary The text contains a table with numerical data, including categories such as 'Health Care and Social Assistance' and 'Arts, Entertainment and Recreation,' alongside a 'Cooling Degree-Day Index' with varying values across different periods. The data appears to be related to energy consumption or environmental metrics but lacks contextual explanation.

0.99 1.63 1.34 1.59 1.18 1.70 1.39 1.10 1.66 1.60 2.20 1.22 2.24 2.03 1.92 1.98 2.03 1.99 2.78 1.68 1) Data on GHG emissions are presented excluding GHG emissions related to electricity production. 2) “Offices” includes activities related...

AI summary The text presents data on energy use and GHG emissions for street lighting in the commercial/institutional sector, including energy use in PJ and GHG emissions in Mt of CO2e, along with GHG intensity in tonnes per TJ from the year 2000 to 2019.

2.79 2.83 2.85 2.89 2.94 2.99 3.03 3.08 3.14 3.16 3.17 3.18 3.20 3.19 3.15 3.14 3.13 3.12 3.11 3.10 2 Energy Intensity (MJ/m ) 207.42 205.12 198.33 195.53 201.36 189.92 182.21 190.95 189.69 186.05 186.04 186.20 159.03 159.74 170.36 167.95...

AI summary The text presents a series of numerical data points related to energy intensity and auxiliary motors energy use for wholesale trade over a period of time, along with floor space measurements. These data points appear to be part of a larger analysis or report on energy usage and efficiency metrics.

Auxiliary Equipment Energy Use for Wholesale Trade (PJ) 0.3 0.4 0.4 0.4 0.5 0.5 0.4 0.5 0.5 0.5 0.5 0.6 0.5 0.5 0.5 0.5 0.5 0.5 0.5 0.5 Energy Use by Energy Source (PJ) Electricity 0.3 0.3 0.3 0.4 0.4 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 0....

AI summary The text provides data on auxiliary equipment energy use for wholesale trade and energy use by energy source, measured in petajoules (PJ) across multiple time periods. Electricity is the primary energy source, with minimal use from other sources such as natural gas and fuel oils.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 Shares (%) Electricity 92.3 92.0 92.3 92.1 91.2 90.9 90.5 91.3 91.2 92.4 92.1 92.3 92.4 92.1 92.4 92.3 96.0 90.1 90.1 90.1 Natural Gas 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The text presents a table showing the percentage of shares attributed to different energy sources over time, with electricity consistently holding the highest share, followed by other categories such as light fuel oil, heavy fuel oil, steam, and other. Natural gas is not represented in the data.

0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity 2.7 1.8 1.6 3.1 6.4 6.2 5.9 6.2 6.4 8.7 17.5 11.1 6.6 5.0 5.9 5.9 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 2.0 2.0 3.3 4.7 3.4 12.2 20.0...

AI summary The text presents a table showing the distribution of shares (%) across various energy sources over time, indicating changes in the proportion of electricity, natural gas, light fuel oil and kerosene, heavy fuel oil, steam, and other energy sources.

32.8 41.2 38.0 26.6 20.0 17.2 24.8 18.3 31.1 39.8 33.2 21.8 16.3 17.9 22.2 24.4 23.0 17.9 11.8 12.5 Activity Floor Space (million m 2) 2.79 2.83 2.85 2.89 2.94 2.99 3.03 3.08 3.14 3.16 3.17 3.18 3.20 3.19 3.15 3.14 3.13 3.12 3.11 3.10 Ener...

AI summary The text provides data on energy intensity and floor space for the commercial/institutional sector in the Atlantic region from 2000 to 2019, including energy use by end use and energy source. It includes a table with figures for energy intensity in MJ/m² and floor space in million m², along with a note on energy use categories.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Wholesale Trade (PJ) 0.2 0.3 0.2 0.3 0.2 0.3 0.2 0.2 0.2 0.2 0.2 0.2 0.3 0.3 0.3 0.3 0.3 0.3 0.4 0.3 Energy Us...

AI summary The text presents data on space cooling energy use for wholesale trade from 2000 to 2019, showing energy use by source (electricity and natural gas) and the share of each source, along with floor space activity over the same period.

Space Heating Energy Use for Wholesale Trade (PJ) 1.7 1.7 1.8 1.7 2.3 1.9 1.6 2.0 1.8 1.4 1.1 1.7 1.7 1.5 1.7 1.7 1.6 1.5 1.3 1.3 Energy Use by Energy Source (PJ) Electricity 0.4 0.3 0.5 0.4 0.4 0.3 0.2 0.6 0.6 0.6 0.3 0.5 0.5 0.4 0.6 0.6...

AI summary The document presents data on space heating energy use for wholesale trade and energy use by energy source in PJ units over a series of years, showing variations in consumption from different energy sources such as electricity, natural gas, fuel oil, and others.

16.0 20.9 19.2 17.9 13.6 13.1 16.2 14.4 18.1 23.4 25.2 14.7 10.7 11.7 11.2 13.3 14.6 10.9 7.1 7.5 Activity 2 Floor Space (million m ) 2.79 2.83 2.85 2.89 2.94 2.99 3.03 3.08 3.14 3.16 3.17 3.18 3.20 3.19 3.15 3.14 3.13 3.12 3.11 3.10 2 Ene...

AI summary The text presents statistical data on energy use, including floor space, energy intensity, heating and cooling degree-day indices, and a note indicating that 'Other' includes coal and propane. The data is provided by the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

Auxiliary Equipment Energy Use for Retail Trade (PJ) 0.9 1.0 1.0 1.1 1.2 1.2 1.2 1.3 1.3 1.4 1.4 1.5 1.4 1.4 1.5 1.4 1.5 1.3 1.4 1.5 Energy Use by Energy Source (PJ) Electricity 0.8 0.9 0.9 1.0 1.1 1.1 1.1 1.2 1.2 1.3 1.3 1.4 1.3 1.3 1.4 1...

AI summary The text provides a table showing the energy use for auxiliary equipment in retail trade, measured in petajoules (PJ), across different energy sources and time periods. The data indicates that electricity is the primary energy source, with usage increasing slightly over time.

0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Shares (%) Electricity 2.7 1.8 1.6 3.1 6.4 6.2 5.9 6.2 6.4 8.7 17.5 11.1 6.6 5.0 5.9 5.9 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 2.0 2.0 3.3 4.7 3.4 12.2 20.0...

AI summary The text presents statistical data on energy consumption shares and floor space activity over time, showing fluctuations in the percentage distribution of electricity, natural gas, and various fuel types, alongside changes in floor space measurements.

6.12 6.38 6.49 6.63 6.85 6.94 7.15 7.36 7.46 7.53 7.55 7.58 7.74 7.74 7.65 7.63 7.57 7.54 7.49 7.45 Energy Intensity (MJ/m2) 77.06 72.46 69.52 85.61 90.65 88.38 78.37 87.10 82.54 71.89 73.75 92.64 95.59 72.42 76.27 76.68 67.29 60.18 64.96...

AI summary The text presents numerical data on energy intensity and secondary energy use by end use and energy source in the commercial/industrial sector, including a table with years ranging from 2000 to 2019. It also mentions the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group, and references a 2023 Load Forecast Report.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Retail Trade (PJ) 0.5 0.7 0.6 0.8 0.7 0.9 0.6 0.6 0.7 0.5 0.6 0.5 1.0 0.8 0.8 1.0 1.0 1.0 1.3 1.0 Energy Use b...

AI summary The text presents a table showing the space cooling energy use for retail trade in PJ from 2000 to 2019, with all energy use attributed to electricity and no use of natural gas. It also includes floor space in million square meters over the same period.

16.0 20.9 19.2 17.9 13.6 13.1 16.2 14.4 18.1 23.4 25.2 14.7 10.7 11.7 11.2 13.3 14.6 10.9 7.2 7.5 Activity Floor Space (million m 2) 6.12 6.38 6.49 6.63 6.85 6.94 7.15 7.36 7.46 7.53 7.55 7.58 7.74 7.74 7.65 7.63 7.57 7.54 7.49 7.45 Energy...

AI summary The text presents numerical data on energy use, floor space, and degree-day indices for a commercial/industrial sector in Atlantic Canada, with a focus on transportation and warehousing. It includes energy intensity metrics and references a 'Load Forecast Report' from Synapse IR-6, Attachment 2, Page 42 of 57.

Water Heating Energy Use for Transportation and Warehousing (PJ) 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Energy Use by Energy Source (PJ) Electricity 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0...

AI summary The document presents data on water heating energy use for transportation and warehousing, showing consistent usage of 0.1 PJ across all years, with minimal variations in energy sources such as light fuel oil and kerosene.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity 2.7 1.8 1.6 3.1 6.4 6.2 5.9 6.2 6.4 8.7 17.5 11.1 6.6 5.0 5.9 5.9 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 2.0 2.0 3.3 4.7 3.4 12.2 20.0...

AI summary The text presents a table showing the distribution of energy sources by share percentage across different years. It outlines the proportion of electricity, natural gas, light fuel oil, heavy fuel oil, steam, and other energy sources over time.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Transportation and Warehousing (PJ) 0.1 0.1 0.1 0.2 0.1 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0....

AI summary The table presents energy use data for space cooling in the transportation and warehousing sector from 2000 to 2019, showing consistent electricity use and no natural gas use. It also includes floor space activity data over the same period.

2.36 2.36 2.36 2.37 2.40 2.43 2.44 2.46 2.52 2.53 2.54 2.55 2.55 2.53 2.51 2.50 2.49 2.48 2.47 2.48 2 Energy Intensity (MJ/m ) 648.82 635.25 623.83 564.72 731.30 577.24 491.07 561.73 499.19 403.83 334.82 499.59 486.09 436.63 487.81 486.59...

AI summary The text presents a series of numerical data points related to energy intensity, heating and cooling degree-day indices, and energy use in the commercial/institutional sector. It includes a table with historical data spanning from 2000 to 2019 and references a report from the Office of Energy Efficiency.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Lighting Energy Use for Information and Cultural Industries1 (PJ) 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0...

AI summary The text presents a table showing lighting and auxiliary motors energy use, along with floor space and energy intensity for Information and Cultural Industries from 2000 to 2019. The data indicates consistent energy use and slight variations in energy intensity over time.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity 94.3 94.1 94.3 93.7 92.7 92.4 92.1 92.8 92.7 94.5 94.3 94.5 94.5 94.3 94.5 94.5 97.2 92.8 92.8 92.8 Natural Gas 0.0 0.0 0.0 0.4 0.4 0.4...

AI summary The text presents a table showing the distribution of shares across various energy sources over time, with electricity comprising the majority of shares, followed by natural gas and other categories. The data reflects changes in energy consumption patterns across different periods.

5.7 5.9 5.7 5.9 6.9 7.1 7.4 6.8 6.8 4.9 5.1 5.0 4.9 4.9 4.8 4.8 2.5 6.4 6.2 6.2 Activity Floor Space (million m2) 0.71 0.72 0.73 0.74 0.75 0.77 0.78 0.79 0.79 0.81 0.82 0.82 0.83 0.83 0.83 0.83 0.83 0.84 0.85 0.84 2 Energy Intensity (MJ/m...

AI summary The text presents numerical data representing energy intensity and floor space over a series of time periods. The data shows fluctuations in energy intensity and slight increases in floor space, indicating changes in energy usage patterns over time.

0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity 1.5 1.5 1.5 1.3 5.0 5.0 5.9 5.8 5.0 6.2 13.0 7.8 5.0 5.0 5.7 5.7 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 1.5 1.4 2.1 3.3 2.7 9.5 15.9 18...

AI summary The text presents a table showing the distribution of shares across various energy sources over time, with significant variations in the percentage of shares attributed to electricity, natural gas, light fuel oil and kerosene, and other categories.

41.1 46.2 42.3 35.4 34.2 37.1 41.6 34.0 55.9 68.2 55.1 40.3 42.4 30.8 36.6 39.4 37.8 30.9 21.6 22.8 Activity 2 Floor Space (million m ) 0.71 0.72 0.73 0.74 0.75 0.77 0.78 0.79 0.79 0.81 0.82 0.82 0.83 0.83 0.83 0.83 0.83 0.84 0.85 0.84 2 E...

AI summary The text presents data on energy use in the commercial/institutional sector, including floor space, energy intensity, and breakdown of energy sources. It includes a table with years from 2000 to 2019 and notes that lighting and auxiliary motors consume only electricity, while 'Other' includes coal and propane.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Information and Cultural Industries (PJ) 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0...

AI summary The text presents a table showing the energy use for space cooling in information and cultural industries from 2000 to 2019, with data on energy use by source (electricity and natural gas) and the share of each energy source. It also includes data on floor space activity over the same time period.

0.48 0.50 0.52 0.54 0.56 0.58 0.60 0.61 0.62 0.64 0.65 0.66 0.66 0.67 0.67 0.67 0.68 0.69 0.71 0.71 Energy Intensity (MJ/m2) 128.46 169.62 143.98 173.92 136.12 168.45 122.30 111.18 124.37 84.31 101.82 85.35 162.55 139.06 139.54 160.90 168....

AI summary The text presents a series of numerical values related to energy intensity, measured in MJ/m2, over a sequence of time points. These values appear to represent data points for analysis in a regulatory proceeding, possibly related to energy efficiency or consumption patterns.

Space Heating Energy Use for Information and Cultural Industries (PJ) 0.6 0.6 0.6 0.6 0.8 0.6 0.5 0.7 0.6 0.5 0.4 0.6 0.6 0.5 0.6 0.6 0.6 0.5 0.5 0.5 Energy Use by Energy Source (PJ) Electricity 0.1 0.1 0.1 0.1 0.2 0.2 0.1 0.3 0.2 0.2 0.1...

AI summary The document presents data on space heating energy use by energy source for information and cultural industries in Nova Scotia, showing varying consumption levels of electricity, natural gas, light fuel oil, heavy fuel oil, and other sources across different periods.

0.71 0.72 0.73 0.74 0.75 0.77 0.78 0.79 0.79 0.81 0.82 0.82 0.83 0.83 0.83 0.83 0.83 0.84 0.85 0.84 Energy Intensity (MJ/m2) 797.51 785.01 786.41 762.45 1,005.57 801.84 691.99 838.91 727.96 577.30 461.75 688.16 669.24 601.15 671.61 709.42...

AI summary The document contains tables with energy intensity data, heating and cooling degree-day indices, and a section on commercial/industrial energy use by end use and energy source, indicating a focus on energy consumption analysis and forecasting.

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Lighting Energy Use2 for Offices (PJ) 1 3.6 3.6 3.5 3.5 3.3 3.2 3.1 3.3 3.3 3.4 3.4 2.9 3.0 3.0 3.2 3.2 3.1 3.4 3.5 3.6 Activity Floor Space (mi...

AI summary The text presents a table showing the energy use and intensity for lighting and auxiliary motors in offices from 2001 to 2019. It includes data on energy use in petajoules (PJ), floor space in million square meters, and energy intensity in megajoules per square meter (MJ/m²).

1 Auxiliary Equipment Energy Use for Offices (PJ) 2.7 2.9 2.8 3.4 3.2 3.5 3.6 3.7 3.8 3.8 4.0 3.5 3.5 3.3 3.5 3.4 3.5 3.0 3.2 3.4 Energy Use by Energy Source (PJ) Electricity 2.5 2.7 2.6 3.1 2.9 3.2 3.3 3.4 3.5 3.6 3.9 3.3 3.4 3.2 3.3 3.3...

AI summary The text presents energy use data for auxiliary equipment in offices, primarily sourced from electricity, with no usage reported for other energy sources such as natural gas, fuel oil, or steam. The data spans multiple years, showing a general trend of increasing electricity consumption.

7.3 7.3 7.3 8.3 8.3 8.3 8.3 8.3 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 4.0 Activity Floor Space (million m2) 15.28 15.61 15.81 16.16 16.43 16.74 17.03 17.30 17.51 17.86 18.05 18.25 18.53 18.65 18.63 18.67 18.67 18.81 18.84 18.73 2 Energy...

AI summary The text presents numerical data showing changes in floor space and energy intensity over time, indicating potential trends in energy usage and building expansion.

Water Heating Energy Use for Offices1 (PJ) 0.5 0.5 0.5 0.7 0.5 0.5 0.5 0.6 0.5 0.5 0.6 0.7 0.6 0.5 0.5 0.5 0.4 0.4 0.4 0.4 Energy Use by Energy Source (PJ) Electricity 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The text presents data on energy use for water heating in offices, measured in petajoules (PJ), across various energy sources including light fuel oil, natural gas, and other sources. The data appears to be tabular and may be part of a larger analysis or report on energy consumption patterns.

1 Space Heating Energy Use for Offices (PJ) 9.5 9.4 9.6 11.3 10.5 9.8 8.1 9.6 9.0 7.8 9.2 10.8 8.2 7.4 8.2 8.7 8.2 7.8 6.7 7.1 Energy Use by Energy Source (PJ) Electricity 0.6 0.5 0.8 0.5 0.3 0.3 0.4 0.3 0.3 0.2 0.2 0.3 0.2 0.4 0.4 0.4 0.5...

AI summary The text presents data on space heating energy use for offices and energy use by energy source in PJ units over a period of time. It includes figures for electricity, natural gas, light fuel oil and kerosene, heavy fuel oil, steam, and other sources.

206.34 204.05 197.30 194.51 208.71 197.98 189.98 198.81 197.79 193.89 193.94 193.91 165.48 166.25 177.25 174.73 167.63 183.01 188.48 198.49 Auxiliary Motors Energy Use for Educational Services1 (PJ) 0.6 0.5 0.5 0.5 0.6 0.5 0.4 0.5 0.5 0.5...

AI summary The text presents numerical data on energy use and intensity for educational services in Nova Scotia, including auxiliary motors energy use and floor space over time. It provides metrics that may be relevant to energy efficiency and resource planning discussions.

Auxiliary Equipment Energy Use for Educational Services (PJ) 1.0 1.0 1.0 1.2 1.3 1.3 1.2 1.3 1.3 1.4 1.4 1.5 1.4 1.4 1.5 1.5 1.5 1.4 1.5 1.6 Energy Use by Energy Source (PJ) Electricity 0.9 1.0 0.9 1.1 1.2 1.1 1.1 1.2 1.2 1.3 1.4 1.4 1.3 1...

AI summary The document presents data on auxiliary equipment energy use for educational services, measured in petajoules (PJ), across multiple years. It details energy use by source, primarily electricity, with negligible contributions from other fuels. The data shows a general trend of increasing energy use over time.

7.5 7.8 7.5 7.7 8.7 9.0 9.3 8.6 8.6 4.9 5.1 5.0 4.9 5.1 4.9 5.0 2.6 6.4 6.4 6.4 Activity Floor Space (million m2) 6.76 6.83 6.88 6.94 6.97 7.02 7.03 7.00 7.00 7.06 7.24 7.32 7.39 7.43 7.56 7.59 7.57 7.64 7.63 7.57 2 Energy Intensity (MJ/m...

AI summary The text presents numerical data including activity levels, floor space in million square meters, and energy intensity measured in MJ per square meter over a series of time points. The data appears to track changes in energy usage and building space over time.

Water Heating Energy Use for Educational Services (PJ) 0.6 0.5 0.5 0.6 0.7 0.6 0.6 0.6 0.6 0.5 0.5 0.7 0.7 0.5 0.6 0.6 0.5 0.5 0.5 0.5 Energy Use by Energy Source (PJ) Electricity 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.1 0.1 0.0 0.0 0.0...

AI summary The document presents data on water heating energy use for educational services in PJ units, categorized by energy sources such as electricity, natural gas, fuel oil, and others. The data spans multiple years, showing variations in energy consumption.

0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Shares (%) Electricity 2.7 1.8 1.6 3.1 6.4 6.2 5.9 6.2 6.4 8.7 17.5 11.1 6.6 5.0 5.9 5.9 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 2.0 2.0 3.3 4.7 3.4 12.2 20.0...

AI summary The text presents a table showing the distribution of shares (%) across various energy sources over time, including Electricity, Natural Gas, Light Fuel Oil and Kerosene, Heavy Fuel Oil, Steam, and Other. The data reflects changing proportions of each energy source over multiple periods.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Educational Services (PJ) 0.4 0.6 0.5 0.7 0.6 0.7 0.5 0.5 0.5 0.4 0.5 0.4 0.8 0.7 0.7 0.8 0.8 0.9 1.1 0.8 Ener...

AI summary The text presents a table showing the space cooling energy use for educational services in Nova Scotia from 2000 to 2019, including energy use by source (electricity and natural gas) and floor space. Electricity is the sole energy source used for cooling, with no use of natural gas. Floor space has increased slightly over the years.

6.76 6.83 6.88 6.94 6.97 7.02 7.03 7.00 7.00 7.06 7.24 7.32 7.39 7.43 7.56 7.59 7.57 7.64 7.63 7.57 2 Energy Intensity (MJ/m ) 637.89 628.06 629.16 607.26 835.95 670.66 580.23 702.06 609.93 483.42 384.89 574.97 559.99 503.13 561.93 593.52...

AI summary The text provides numerical data on energy intensity, heating and cooling degree-day indices, and secondary energy use in the commercial/industrial sector, specifically in the health care and social assistance category. The data spans multiple years and includes energy sources and end-use categories.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Lighting Energy Use for Health Care and Social Assistance1 (PJ) 1.4 1.4 1.4 1.4 1.4 1.4 1.3 1.4 1.4 1.4 1.4 1.4 1.2 1.3 1.4 1.3 1.3 1.4 1.4...

AI summary The text presents energy use data for lighting and auxiliary motors in health care and social assistance facilities from 2000 to 2019, showing trends in energy consumption and intensity over time. It includes metrics such as energy use in petajoules (PJ), floor space in million square meters, and energy intensity in megajoules per square meter.

Auxiliary Equipment Energy Use for Health Care and Social Assistance (PJ) 1.4 1.5 1.4 1.7 1.8 1.7 1.7 1.8 1.8 1.9 2.0 2.1 1.9 1.9 2.2 2.1 2.1 1.9 2.0 2.1 Energy Use by Energy Source (PJ) Electricity 0.9 1.1 1.0 1.2 1.3 1.3 1.3 1.3 1.3 1.4...

AI summary The text presents energy usage data for auxiliary equipment in health care and social assistance sectors, measured in petajoules (PJ) across multiple years. It details energy consumption by source, primarily electricity and other unspecified sources, with natural gas, fuel oil, and steam showing no usage.

32.1 28.7 32.4 29.7 26.2 24.7 24.0 28.3 28.3 24.8 23.3 23.5 25.0 21.3 22.4 21.9 12.0 23.7 23.7 23.7 Activity Floor Space (million m2) 3.87 3.92 3.95 3.92 3.90 3.92 3.98 3.99 3.97 4.00 4.05 4.15 4.22 4.34 4.43 4.40 4.38 4.37 4.32 4.29 2 Ene...

AI summary The text presents numerical data on energy intensity and floor space over time, indicating fluctuations in energy usage and building area. The numbers suggest variations in energy efficiency across different periods.

0.3 0.3 0.3 0.2 0.2 0.1 0.2 0.2 0.2 0.3 0.2 0.2 0.2 0.1 0.2 0.2 0.2 0.1 0.1 0.1 Shares (%) Electricity 2.7 1.8 1.6 3.1 6.4 6.2 5.9 6.2 6.4 8.7 17.5 11.1 6.6 5.0 5.9 5.9 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 2.0 2.0 3.3 4.7 3.4 12.2 20.0...

AI summary The text presents a table with percentages across different energy sources over multiple time periods. It shows the distribution of shares for electricity, natural gas, light fuel oil and kerosene, heavy fuel oil, steam, and other energy sources.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Health Care and Social Assistance (PJ) 0.4 0.6 0.5 0.6 0.5 0.7 0.5 0.5 0.5 0.4 0.4 0.4 0.7 0.6 0.7 0.8 0.8 0.8...

AI summary The document provides data on space cooling energy use for health care and social assistance facilities in Nova Scotia from 2000 to 2019, showing energy use by electricity and natural gas, along with the share of each energy source and floor space activity over time.

2.62 2.71 2.79 2.83 2.88 2.96 3.03 3.07 3.09 3.14 3.20 3.29 3.36 3.47 3.56 3.55 3.55 3.58 3.57 3.58 Energy Intensity (MJ/m2) 166.35 219.75 186.51 225.27 180.68 224.49 162.92 148.00 165.70 112.30 135.65 113.41 215.87 184.72 185.33 213.69 22...

AI summary The text provides numerical data representing energy intensity values (MJ/m2) over a series of time points, indicating fluctuations in energy usage efficiency across different periods.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 Shares (%) Electricity 26.9 23.6 35.0 23.5 19.4 15.3 11.1 26.1 27.3 36.3 28.3 28.2 27.6 13.2 15.8 14.8 14.8 22.0 21.4 22.6 Natural Gas 0.0 0.0 0.0 2.5 3.0 6.0...

AI summary The text presents a table showing the distribution of shares (%) across various energy sources, including Electricity, Natural Gas, Light Fuel Oil and Kerosene, Heavy Fuel Oil, Steam, and Other, over multiple time periods. The data indicates varying percentages for each energy source, highlighting shifts in energy consumption patterns.

1.9 2.6 2.6 2.3 1.8 1.8 1.8 1.6 1.7 1.6 0.7 0.5 1.0 0.7 0.7 0.8 1.2 1.3 1.2 1.4 Activity Floor Space (million m2) 3.87 3.92 3.95 3.92 3.90 3.92 3.98 3.99 3.97 4.00 4.05 4.15 4.22 4.34 4.43 4.40 4.38 4.37 4.32 4.29 Energy Intensity (MJ/m2)...

AI summary The text presents data on energy intensity, floor space, and degree-day indices for the commercial/institutional sector in the Atlantic region, including a table with energy use by end use and energy source. The data spans multiple years and includes categories such as heating and cooling degree-day indices.

0.72 0.74 0.75 0.76 0.76 0.78 0.79 0.80 0.80 0.85 0.86 0.88 0.90 0.92 0.93 0.94 0.95 0.97 0.97 0.96 Energy Intensity (MJ/m2) 98.55 82.57 79.74 82.82 86.38 81.92 67.84 71.14 70.86 77.50 63.13 78.58 62.84 49.79 65.96 61.88 57.32 61.33 53.31...

AI summary The text presents numerical data showing energy intensity values over time, indicating a fluctuation in energy consumption per square meter. These figures may be used for analysis related to energy efficiency and consumption trends.

Auxiliary Equipment Energy Use for Arts, Entertainment and Recreation (PJ) 0.1 0.1 0.1 0.1 0.2 0.2 0.1 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 0.2 Energy Use by Energy Source (PJ) Electricity 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2...

AI summary The text presents energy use data for auxiliary equipment in arts, entertainment, and recreation, showing electricity consumption in PJ units across multiple years. Natural gas, fuel oil, and other energy sources show negligible usage in this sector.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 Shares (%) Electricity 25.4 19.1 26.7 22.3 21.4 17.8 13.5 34.9 35.6 40.6 30.1 31.1 31.8 27.7 38.8 34.7 34.1 44.5 48.6 49.1 Natural Gas 0.0 0.0 0.0 2.9 3.8 8.2...

AI summary The text presents a table showing the distribution of shares (%) across various energy sources over time, including Electricity, Natural Gas, Light Fuel Oil and Kerosene, Heavy Fuel Oil, Steam, and Other. The data reflects changes in the proportion of each energy source over multiple periods.

16.0 19.9 18.2 19.4 15.2 15.9 20.4 18.0 20.5 23.4 25.3 14.8 10.8 11.8 11.3 13.4 14.7 11.0 7.1 7.5 Activity 2 Floor Space (million m ) 0.72 0.74 0.75 0.76 0.76 0.78 0.79 0.80 0.80 0.85 0.86 0.88 0.90 0.92 0.93 0.94 0.95 0.97 0.97 0.96 Energ...

AI summary The text presents data on energy intensity, floor space, and degree-day indices for the commercial/institutional sector in the Atlantic region, including Accommodation and Food Services Non-Space Conditioning Secondary Energy Use by End Use and by Energy Source.

Auxiliary Equipment Energy Use for Accommodation and Food Services (PJ) 0.4 0.5 0.5 0.5 0.6 0.6 0.6 0.6 0.6 0.7 0.7 0.7 0.7 0.7 0.7 0.7 0.8 0.7 0.8 0.8 Energy Use by Energy Source (PJ) Electricity 0.4 0.4 0.4 0.5 0.5 0.5 0.5 0.5 0.5 0.6 0....

AI summary The text presents energy use data for auxiliary equipment in accommodation and food services, primarily focusing on electricity consumption over multiple years. Electricity use increases gradually from 0.4 to 0.8 PJ, while other energy sources such as natural gas, fuel oil, and steam show no usage. Other energy sources remain consistent at 0.1 PJ.

Water Heating Energy Use for Accommodation and Food Services (PJ) 0.3 0.3 0.3 0.3 0.4 0.3 0.3 0.4 0.3 0.3 0.3 0.4 0.4 0.3 0.3 0.3 0.3 0.3 0.3 0.3 Energy Use by Energy Source (PJ) Electricity 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0 0.0...

AI summary The text presents energy use data for water heating in accommodation and food services, detailing the use of various energy sources such as light fuel oil, kerosene, natural gas, and others, measured in petajoules (PJ) across multiple time periods.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.2 0.2 0.2 0.2 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Shares (%) Electricity 2.0 1.6 1.5 2.1 5.5 5.4 5.7 5.8 5.5 6.8 13.1 8.8 5.8 5.0 5.7 5.7 5.0 5.0 5.0 5.0 Natural Gas 0.0 0.0 0.0 1.6 1.5 2.3 3.5 2.8 9.1 14.7 17...

AI summary The text presents a table showing the percentage shares of different energy sources over time. It includes electricity, natural gas, light fuel oil and kerosene, heavy fuel oil, steam, and other energy sources. The data reflects changes in energy consumption distribution across various years.

1.43 1.49 1.55 1.60 1.70 1.79 1.89 1.94 1.97 2.02 2.03 2.06 2.09 2.11 2.13 2.18 2.22 2.30 2.34 2.37 2 Energy Intensity (MJ/m ) 161.68 213.57 181.26 218.93 171.26 212.04 153.85 139.89 156.47 106.07 128.10 107.17 204.10 174.60 175.21 202.02...

AI summary The text presents numerical data on energy intensity over time, showing fluctuations in values from 1.43 to 2.37 and corresponding energy intensity measurements in MJ/m² ranging from 106.07 to 267.88. These figures likely represent historical trends or projections related to energy usage.

1.9 2.4 2.5 2.1 1.7 1.7 1.8 1.5 1.6 1.6 0.6 0.5 0.9 0.7 0.6 0.8 1.2 1.3 1.2 1.3 Activity 2 Floor Space (million m ) 1.92 1.95 1.99 2.01 2.09 2.15 2.25 2.28 2.30 2.33 2.34 2.36 2.38 2.40 2.40 2.45 2.48 2.55 2.56 2.58 Energy Intensity (MJ/m...

AI summary The text presents data on floor space, energy intensity, heating and cooling degree-day indexes for the commercial/institutional sector in the Atlantic region, including a table of energy use by end use and energy source. The data includes figures for various years and is part of a load forecast report.

1.35 1.34 1.34 1.34 1.33 1.31 1.29 1.28 1.26 1.24 1.21 1.20 1.17 1.14 1.11 1.08 1.05 1.03 1.01 0.99 Energy Intensity (MJ/m2) 77.03 64.54 62.33 64.73 67.52 64.03 53.03 55.61 55.39 60.58 49.34 61.42 49.12 38.92 51.56 48.37 44.81 47.94 41.67...

AI summary The text presents numerical data related to energy intensity (MJ/m2) over a series of time points, showing fluctuations in values from 77.03 to 40.83. These figures may reflect changes in energy consumption efficiency or other related metrics over time.

5.3 5.3 5.3 5.3 6.3 6.3 6.3 6.3 6.5 5.5 5.5 5.5 5.5 5.4 5.4 5.4 5.5 5.4 5.3 5.3 Activity Floor Space (million m2) 1.35 1.34 1.34 1.34 1.33 1.31 1.29 1.28 1.26 1.24 1.21 1.20 1.17 1.14 1.11 1.08 1.05 1.03 1.01 0.99 Energy Intensity (MJ/m2)...

AI summary The text provides data on floor space and energy intensity over time, showing a decreasing trend in floor space and fluctuating energy intensity values.

1.35 1.34 1.34 1.34 1.33 1.31 1.29 1.28 1.26 1.24 1.21 1.20 1.17 1.14 1.11 1.08 1.05 1.03 1.01 0.99 Energy Intensity (MJ/m2) 63.55 59.76 57.34 70.60 74.76 64.69 57.36 63.75 60.41 52.62 53.98 67.80 69.96 53.01 55.82 56.13 49.25 44.05 47.54...

AI summary The text presents energy intensity data and load forecast information for the Commercial/Institutional Sector in the Atlantic region, including energy use by end use and energy source. It includes tables with historical data and a mention of the Office of Energy Efficiency, Demand Policy and Analysis Division, Market Analysis Group.

2000 2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 2012 2013 2014 2015 2016 2017 2018 2019 Space Cooling Energy Use for Other Services (PJ) 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.1 0.0 0.0 0.0 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 Energy Use...

AI summary The text presents a table showing energy use data for space cooling in 'Other Services' from 2000 to 2019. It details energy use by source (electricity and natural gas) and their respective shares, along with floor space activity in million square meters over the same period.

Space Heating Energy Use for Other Services (PJ) 0.8 0.7 0.7 0.7 1.0 0.7 0.6 0.8 0.7 0.5 0.4 0.6 0.6 0.5 0.5 0.5 0.5 0.5 0.4 0.4 Energy Use by Energy Source (PJ) Electricity 0.2 0.1 0.2 0.2 0.2 0.1 0.1 0.3 0.2 0.2 0.1 0.2 0.2 0.1 0.2 0.2 0...

AI summary The text presents data on space heating energy use for other services, measured in petajoules (PJ), across various energy sources including electricity, natural gas, light fuel oil, heavy fuel oil, and others. It provides a detailed breakdown of energy consumption over time.

0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.1 0.0 0.0 Shares (%) Electricity 25.4 19.1 26.7 22.3 21.4 17.8 13.5 34.9 35.6 40.6 30.1 31.1 31.8 27.7 38.8 34.7 34.1 44.5 48.6 49.1 Natural Gas 0.0 0.0 0.0 2.9 3.8 8.2...

AI summary The text presents statistical data on energy consumption by type (electricity, natural gas, fuel oils, etc.) and floor space over time, indicating trends and proportions of energy usage across different categories.

1.35 1.34 1.34 1.34 1.33 1.31 1.29 1.28 1.26 1.24 1.21 1.20 1.17 1.14 1.11 1.08 1.05 1.03 1.01 0.99 Energy Intensity (MJ/m2) 567.11 558.33 559.28 542.46 715.17 570.36 493.32 597.92 518.74 411.66 329.23 490.74 477.35 428.78 479.04 506.01 47...

AI summary The text provides energy intensity and degree-day index data for various years, along with a reference to the 2023 Load Forecast Report (NSUARB M11108) and responses from NSPI to Synapse Energy Economics information requests. The data includes metrics such as energy intensity and heating and cooling degree-day indices.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 Request IR-7: 2 3 Residential and Commercial Heating and Heat Pumps (Section 4.4, pp 33-37) 4 5 (a) Please provide...

AI summary The document outlines a series of information requests related to the 2023 Load Forecast Report, focusing on residential and commercial heating technologies, heat pump usage, customer saturation, data sources, peak load impacts, energy consumption estimates, and modeling documentation. These requests aim to gather detailed insights into heating trends and forecast accuracy.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 Request IR-8: 2 3 Residential Water Heaters (WH) (Section 4.4, p 37-38) 4 5 (a) Are more efficient hot water end-u...

AI summary NSPI's response to Synapse Energy Economics' request regarding the 2023 Load Forecast Report discusses the consideration of efficient water heaters, efficiency standards, and the impact of heat pump (HP) adoption on water heating load. It notes that efficiency improvements are factored into the intensity equation based on EIA forecasts.

1 2 (b) Water heaters must meet the following standard as of 2008: CAN/CSA-C191-04, 3 Performance of Electrical Storage Tank Water Heaters for Domestic Hot Water Service. 4 NS Power is not aware of any proposed standards to improve efficie...

AI summary The text discusses water heater efficiency standards, rebate programs, and projected adoption rates of heat pump water heaters. It highlights the current standard (CAN/CSA-C191-04), the lack of proposed efficiency improvements, and the impact of increased heat pump usage on water heating intensity. A table provides estimated intensity per electric water heating household from 2023 to 2027.

. REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forecast Report Synapse IR-9 Attachment 2 Page 14 of 205 January 31, 2023 C. Henwood Phase 2 progress during the reporting period included: • Refinement of pilot design eleme...

AI summary Phase 2 of a pilot project is ongoing, with efforts focused on refining customer agreements, DR event criteria, incentives, and baseline methodology. NS Power is submitting reports to the Strategic Innovation Fund (SIF) as part of its funding commitments, including several confidential and non-confidential appendices.

under ‘electric vehicle (EV) vehicle-to-grid (V2G) Chargers,’ as highlighted in Attachment 3. 1 0 F • Customer Tesla vehicles continue to be excluded from use case events to protect from undue risks placed on Tesla protection systems. The...

AI summary The document outlines modifications to an EV charging and demand response project, including the exclusion of Tesla vehicles from use case events, the addition of managed EV charging via the ev.energy platform, and the inclusion of Commercial and Industrial Building Management System (BMS) controls for Demand Response (DR). These changes were first reported in various semi-annual reports.

1 Modification first reported in July 2021 Semi-Annual Report. 2 Modification first reported in February 2022 Semi-Annual Report. 3 Modification first reported in July 2022 Semi-Annual Report. Page 6 of 48 . . REDACTED (CONFIDENTIAL INFORM...

AI summary The document discusses modifications to use cases during the reporting period, including the addition of the Wind Following use case for ev.energy and the BMS10 – Critical Peak Reduction use case to the C&I BMS program. Baseline data collection for smart chargers began in January 2021 and excludes test events, providing insights into energy consumption patterns.

is based on energy used at the charger level. Figure 1 accounts for data collected from January 1, 2021, to December 31, 2022. Baseline data is considered for days without events, excluding holidays. To date, aggregated charging data was e...

AI summary The text discusses the analysis of EV charging data collected from January 2021 to December 2022, highlighting baseline energy consumption patterns by hour of the day. It notes a shift in charging activity from the evening to early morning hours, with peak consumption remaining between 23:00 and 00:00. Data was captured using the ChargePoint portal and analyzed in Excel, with some Tesla vehicles transitioning from the ChargePoint user group.

:00 hours. Figure 1 shows the comparison of previously reported average baseline data to the overall average baseline EV consumption for each hour of the day from January 2021 to December 31, 2022. Page 7 of 48 . . REDACTED (CONFIDENTIAL I...

AI summary The document discusses the average baseline EV consumption data over a 24-hour period from January 2021 to December 31, 2022, highlighting that the 22:00 to 23:00 period had the highest consumption. It also explains how ev.energy uses an algorithm to schedule smart charging and presents a counterfactual baseline for comparison.

ndicates that the 22:00 to 23:00 period is the highest consumption throughout the reporting period. Figure 2 – ev.energy Data Baseline Plot – June 14 to December 31, 2022, by Hour (Counterfactual) Page 8 of 48 . . REDACTED (CONFIDENTIAL IN...

AI summary The text discusses data from ev.energy, showing peak electricity consumption during late evening hours and the timing of vehicle charging sessions. It highlights managed and unmanaged charging patterns, including 'boosted' charging, and provides insights into EV charging behavior.

ed’ charging, which is when the driver opts out of both demand response events and smart charging in order to receive energy to their vehicle immediately. It is observed that smart charging sessions Page 9 of 48 . . REDACTED (CONFIDENTIAL...

AI summary The document discusses patterns in EV charging behavior, noting that smart charging sessions are typically longer and consume more energy, often occurring overnight. Charging away from home is shorter, and boosted charging events are not high energy consumption events. Seasonal variations in baseline energy consumption from ChargePoint devices are also analyzed.

on to the average between summer and winter has occurred. Understanding these types of patterns and metrics will support building an accurate business model where metrics can be applied seasonally. Page 10 of 48 . . REDACTED (CONFIDENTIAL...

AI summary The document discusses seasonal variations in EV charging energy consumption, noting higher usage in summer than winter, which contradicts the initial hypothesis that colder temperatures would increase energy needs. This pattern is being monitored for future analysis.

id not surpass the peak from the previous period, as noted above and in the July 2022 report. Figure 9 – Screen Capture of the Peak Demand (171.1 kW) seen by ChargePoint EV Charging Fleet, to Date Page 13 of 48 . . REDACTED (CONFIDENTIAL I...

AI summary The document discusses peak demand data from the ChargePoint EV Charging Fleet, including a peak of 171.1 kW and a later peak of 145.81 kW, with the latter influenced by the ev.energy algorithm shifting charging times. Testing events involving ChargePoint chargers are also described.

charger on January 25, 2021 and continued as chargers were available to be added, with up to 61 involved by December 31, 2021. A larger testing group was planned; however, the charge control issue Page 14 of 48 . . REDACTED (CONFIDENTIAL I...

AI summary The report discusses challenges with EV charger testing, particularly with Tesla vehicles, and the transition to the ev.energy platform. Issues such as defective units, customer changes, and Wi-Fi reliability impacted the number of available chargers. Testing expanded to include the entire registered fleet, with 108 vehicles participating by the end of the reporting period.

sting on ev.energy included the entire registered fleet. The number of vehicles receiving events fluctuated with user acquisition growth, which totaled 108 vehicles at the end of the reporting period. Figure 12 and Table 1 summarize all Ch...

AI summary The report details the performance of the ev.energy platform, including the number of vehicles in the registered fleet and the use of ChargePoint events for curtailment. The majority of events were for the EVSE3 use case, with metrics like 'Received Event Ratio' and 'Estimated Average Shed per Event' providing insights into participation and curtailment effectiveness.

ese figures would remain relatively unchanged for all chargers that are participating in a smart charging program and receiving an event. 2 Detailed in the July 2021 Semi-Annual Report. Page 15 of 48 . . REDACTED (CONFIDENTIAL INFORMATION...

AI summary The text discusses the use of ChargePoint EV chargers in a smart charging program, referencing event counts and dispatches since January 2021. It includes a figure and table summarizing event data for various EVSE units and their use-case testing.

(kW) 0.99 0.97 1.04 0.83 1.00 Estimated Average Shed per Event per Opt-in and Charged (kW) 5.3 5.2 4.0 5.4 4.7 Page 16 of 48 . . REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forecast Report Synapse IR-9 Attachment 2 Page...

AI summary The text presents data on load shedding and EVSE use-case summaries, including event dates and periods, from a Smart Grid Semi-Annual Report and a Load Forecast Report. It includes statistical data on kW and average shed per event, along with details on EVSE use cases.

leaves a gap during early morning hours. This will be improved through additional events across all 24 hours as additional use cases are executed, and further analysis is completed in future reports. As use case testing progresses, more co...

AI summary The text discusses the analysis of power shed opportunities during different event start times, highlighting the need for further testing and analysis to improve confidence in hourly shed potential. This data will be used to evaluate the value of shed capacity in relation to hourly system costs.

gorithm created a new, unintended, morning peak at approximately 05:00. Figure 19 – Actual Energy Delivered to Customers using ev.energy, June 14 to July 17, Before Any Use Case Events were Issued By iterating on the experiment, ev.energy...

AI summary The ev.energy scheduling algorithm initially created an unintended morning peak at 05:00. By introducing a proxy price signal, the algorithm was adjusted to smooth overnight charging, reducing the morning peak. Demand response events during 17:00 to 19:00 showed a 62% reduction in energy delivery during system peak times, with an estimated 1.01 kW shed per event.

NS Power will issue a customer survey to ev.energy project participants in 2023. Customer feedback data will be included in the final SGNS report. 3.2. BI-DIRECTIONAL CHARGING 3.2.1 . OB SERVATIONS AVAILAB ILITY In both residential and com...

AI summary NS Power plans to survey participants in the ev.energy project in 2023, with feedback included in the final SGNS report. The document discusses the importance of EV availability for bi-directional charging, using data from the Coritech charger at NSCC Annapolis Valley Campus, showing that the Nissan Leaf is typically available for testing outside of working hours.

ce August 9, 2022. A reoccurring inverter fault with the Coritech charger has impacted charger functionality and data availability, and NS Power is working with Coritech and NSCC to resolve the issue. NS Power has access to Fermata Energy...

AI summary The document discusses issues with Coritech chargers, including a recurring inverter fault that has affected data availability and functionality. NS Power is working with Coritech and NSCC to resolve the issue. Fermata Energy's FE-15 model is currently in use, but the FE-20 model is expected to replace it in the second or third quarter of 2023. Use-cases are cycled weekly, and tables summarize bi-directional charging events.

t course of business may provide additional insight for this use case to be presented in future reporting. The application of this use case will also be further evaluated throughout testing in 2023. E V S E8 – PARTIAL OR WHOLE HOME B AC KU...

AI summary The document discusses the evaluation of EVSE use cases, including partial or whole home backup and C&I customer demand reduction. Testing was conducted using Coritech and Fermata units, with further evaluation planned for future phases. The C&I use case involved discharging EVs during peak demand periods to reduce demand charges.

ed to be a period of high demand for the building. Ideally, the testing period would align with the top monthly demand peaks which would then be reduced – resulting in a reduced monthly demand charge. An ESET student at NSCC has compiled d...

AI summary Testing of bi-directional EV chargers at NSCC showed potential for reducing monthly demand charges, but operational issues and scheduling conflicts hindered full implementation. Automation and integration with building management systems could improve effectiveness, especially in facilities with consistent and substantial peak demand periods.

-directional EV chargers would be more impactful at reducing monthly demand at facilities with consistent energy demand profiles and peak periods that are substantial and shorter in duration. Page 34 of 48 . . REDACTED (CONFIDENTIAL INFORM...

AI summary The document discusses the impact of bidirectional EV chargers on demand charge management, particularly for customers with consistent energy demand profiles and peak periods. It highlights the Fermata charger's capability to automatically discharge battery power to offset high building demand when a pre-set meter target is exceeded.

Attachment 2 – SGNS Use Case Testing Update Report series interval data through the ESP integration for additional in-depth data review and use within the business model. Tesla Powerwall baseline data was captured from the Tesla Powerhub p...

AI summary The report discusses the integration of series interval data through the ESP platform for in-depth analysis and the use of Tesla Powerwall baseline data from the Powerhub portal. Due to technical challenges, data is based on 85 of 109 installed units. The report also presents baseline energy consumption by hour and discusses limitations on residential battery export capacity.

CI C0010788 – Smart Grid Semi-Annual Report Attachment 3 Page 2 of 4 SGNS Customer Program Enrollment Value to be Tested Data and Metrics to Measure System Impact and Value Project Scenarios for Comparison Measuring Outcomes ESP

AI summary The document outlines a Smart Grid Semi-Annual Report Attachment 3, focusing on customer program enrollment, value to be tested, data and metrics for measuring system impact and value, project scenarios for comparison, and measuring outcomes, with ESP as a key component.

• Connection Status & Alarm Status - The availability of EVSE for control during each test (including communication to the chargers, and the customer participation level) • Aggregated EV charger load (kW) Customer charges as Curtailment of...

AI summary The text outlines parameters related to electric vehicle supply equipment (EVSE) monitoring, including connection status, alarm status, load curtailment, and the value of curtailed load. It discusses aspects of EVSE control, customer participation, and the impact of load curtailment on generation contingency and residential load.

• Connection Status & Alarm Status - The availability of EVSE for control during each test (including Electric Vehicle communication to the chargers, and the customer participation level) Distribution Congestion • Curtailment of EVSE charg...

AI summary The text outlines parameters for monitoring and managing EVSE (Electric Vehicle Supply Equipment) during testing, including connection status, alarm status, load curtailment, and monitoring signal latency, with a focus on residential load and customer participation.

Customer charges as • Curtailment of EVSE charge • Value of load curtailed ($/kW, Further leverage EVSE out-of-the- Cold Load Pickup Relief • Net residential load (kW) convenient (document impact power (kW) by control of • Time delay (resp...

AI summary The text discusses customer charges related to EVSE (Electric Vehicle Supply Equipment) curtailment, including the value of load curtailed, net residential load, and restoration processes involving EVSE6. It also mentions leveraging EVSE out-of-the-box functionality for delayed restoration and deferred distribution.

• Connection Status & Alarm Status - The availability of EVSE for control during each test (including Utilize local EVSE settings, controls communication to the chargers, and the customer participation level) through vendor provided softwa...

AI summary The text discusses the monitoring and control of EVSE during testing, including connection status, alarm status, customer participation, and the monitoring of EVSE signals and latency. It also references customer demand charges, load curtailment values, and scheduled charging times.

EV charge • Utility event statistics • Energy delivered (kWh) • Value of load curtailed ($/kW, convenient (charging times will Avoided Generation & Demand Reduction) • Intra-day generation planning EV charging patterns influenced by • Day-...

AI summary The text discusses EV charging statistics, energy delivery, load curtailment value, and the influence of EV charging patterns on generation planning, including intra-day and day-ahead planning, as well as unmanaged energy consumption.

charging timing peaks to understand impact of EVSE1, 2, 3 • Time varying curtailment • Time varying curtailment schedule uninfluenced charging) Deferred T&D System (EVSE3) Upgrades

AI summary The text discusses the timing of electric vehicle supply equipment (EVSE) charging and its impact on peak demand, including time-varying curtailment schedules and deferred transmission and distribution system upgrades.

Customer charges as Generation Contingency (10 Curtailment of EV in response to a • Curtailment of EV charge • Utility event statistics • Energy delivered (kWh) • Value of load curtailed ($/kW, convenient (charging times will Minute Operat...

AI summary The text discusses customer charges, energy curtailment related to EV charging during contingency events, and the impact of EV charging patterns on utility operations, including statistics on vehicle charging sessions and energy consumption.

Vehicle charging session data • Unmanaged energy consumption (kWh) $/kWh) be compared with system N/A Industrial Rate platform algorithim minute operating reserve Capacity charging timing peaks to understand impact of EVSE5 requirements un...

AI summary The text discusses vehicle charging session data, focusing on unmanaged energy consumption and industrial rates. It references platform algorithms, minute operating reserve capacity, and the impact of charging timing on system peaks and requirements.

CI C0010788 – Smart Grid Semi-Annual Report Attachment 3 Page 3 of 4 SGNS Customer Program Enrollment Value to be Tested Data and Metrics to Measure System Impact and Value Project Scenarios for Comparison Measuring Outcomes ESP

AI summary The document outlines a Smart Grid Semi-Annual Report Attachment 3, focusing on customer program enrollment, value testing, data and metrics for measuring system impact and value, project scenarios for comparison, and outcomes measurement using the ESP platform.

• Feeder Voltage (V), Current (A) and Load (MVA) • Connection Status & Alarm Status - The availability of batteries for control during each test (including • Battery Real Power (kW) Manage optimal control strategy for • Target Power Factor...

AI summary The text outlines technical parameters related to power factor management in a C&I context, including voltage, current, load, battery functionality, and monitoring signal latency, focusing on optimal control strategies for power factor correction.

modes: Reactive power or real • PV Inverter Reactive Power Output (kVAR) power output and energy ($/kW, Voltage Support • PV Inverter grid support • Forecasted PV Output (kW) and energy (kWh) versus actuals (%) PV Inverter out-of-the-box f...

AI summary The text discusses various aspects of PV inverter functionality, including reactive power output, voltage support, and system upgrades. It mentions metrics such as forecasted PV output versus actuals, power factor, and response times, as well as pilot programs related to grid services.

CI C0010788 – Smart Grid Semi-Annual Report Attachment 3 Page 4 of 4 SGNS Customer Program Enrollment Value to be Tested Data and Metrics to Measure System Impact and Value Project Scenarios for Comparison Measuring Outcomes ESP

AI summary The document outlines a section from a Smart Grid Semi-Annual Report, focusing on customer program enrollment, value to be tested, data and metrics for measuring system impact and value, project scenarios for comparison, measuring outcomes, and ESP.

frequency falling outside of None Pilot 2/R3B functionality • Forecasted PV Output (kW) and energy (kWh) versus actuals (%) • PV Inverter Control Variable Input: Feeder output and energy ($/kW, $/kWh) operating modes stacking with other gr...

AI summary The text discusses metrics related to the performance of solar PV systems, including forecasted versus actual output, inverter response times, and system response to frequency changes, focusing on functionality and capacity within the context of grid services.

Wh) to understand impact of BMS 1, 2, 3 • Time varying curtailment or • Aggregated load curtailed (kW) • Time varying curtailment schedule turn off) • BMS response time to curtailment after receiving signal (seconds) uninfluenced operation...

AI summary The text discusses the impact of Building Management Systems (BMS) 1, 2, and 3 on time-varying curtailment, aggregated load curtailed in kW, and BMS response time to curtailment signals. It also mentions deferred transmission and distribution system upgrades.

3.50 3.75 – – 7.25 1,228.00 Total 1,224.50 61.00 – (57.50) 1,228.00 – NS Power relies on customers to self-identify as low income. No subscribers have identified themselves as low income. NS Power is otherwise unable to discern the level o...

AI summary The document outlines estimated average participant bill impacts for residential and commercial classes related to community solar programs. It notes that NS Power relies on customers to self-identify as low income, and no subscribers have done so. The bill impacts show a cost increase for both residential and commercial participants.

part on the consent of the EV manufacturer to operate without explicit contracts in place. This creates a ’platform risk’ that ev.energy may be prevented from connecting to certain manufacturers’ EVs. For example, in November 2022, some Ch...

AI summary The text discusses challenges with the ev.energy platform, including platform risks due to lack of explicit contracts with EV manufacturers, and issues with token expiration affecting user experience. It also covers the cancellation of EV Smart Charging DR events before weather events and the implementation of a 'storm mode' by NS Power to improve reliability during severe weather.

CI C0010788 – Smart Grid Semi-Annual Report Attachment 5 Page 11 of 14 Attachment 5 – SGNS Project Lessons Learned The fire damaged the customer’s solar array, but did not damage other property or persons, as it was discovered and mitigate...

AI summary A fire damaged a customer's solar array, but the manufacturer provided compensation and improved equipment. An issue with a current transformer metering system during the installation of a Fermata bi-directional charger led to incomplete load data capture, requiring alternative solutions to ensure proper demand charge management.

9,152,691 9,959,113 Please use the Current Claim total (1) and the Total to Date (2) to complete the Appendix A - Recipient's Claim Summary . Veuillez SVP utiliser le total de la Réclamation Actuelle (1) ainsi que le Total à ce Jour (2) po...

AI summary The document includes a claim summary form, a redacted 2023 Load Forecast Report, and a Smart Grid Semi-Annual Report. It also includes a progress report from Siemens Canada Limited, New Brunswick Power Corporation, and Nova Scotia Power Incorporated under the Strategic Innovation Fund for the Smart Grid Atlantic project.

Report Date: 2022-08-10 Unrestricted Page 1 of 15 Document # PM-FM-011 Version 5 2022-07-22 . . REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forecast Report Synapse IR-9 Attachment 2 Page 96 of 205 REDACTED CI C0010788 –...

AI summary The document outlines project activities related to the Energy Services Platform (ESP), Microgrid Control Platform (MCP), and the Shediac Smart Energy Community Demonstration, as part of a Smart Grid Nova Scotia Demonstration. It includes progress percentages, status, and comments for each activity.

i-Annual Report Attachment 6d Page 6 of 15 Activity #2 Shediac Smart Energy Community Demonstration % Completion Status Comments Details of Activity Performed • • Activity # 3 Smart Grid Nova Scotia Demonstration % Completion Status Commen...

AI summary The document outlines several demonstration activities related to energy initiatives in Nova Scotia, including the Shediac Smart Energy Community, Smart Grid Nova Scotia, Tobique Microgrid, and North Branch Smart Energy Development. These projects involve university collaborations, community engagement, and advisory support from Efficiency One.

Report Date: 2022-11-07 Unrestricted Page 1 of 15 Document # PM-FM-011 Version 5 2022-11-07 . . REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forecast Report Synapse IR-9 Attachment 2 Page 114 of 205 REDACTED CI C0010788 –...

AI summary The document outlines several projects related to energy services and smart grid initiatives, including the development of an Energy Services Platform (ESP) and Microgrid Control Platform (MCP), the Shediac Smart Energy Community Demonstration, and the Smart Grid Nova Scotia Demonstration. Progress and details of activities performed are outlined, though much of the content is redacted.

ctivity #5: North Branch (previously Halls Creek) Smart Energy Development % Completion Status Comments Unrestricted Page 4 of 15 Document # PM-FM-011 Version 5 2022-08-10 . . REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load...

AI summary The text outlines several activities related to smart energy development in Nova Scotia, including the North Branch Smart Energy Development, Program Governance and Management, Energy Services Platform (ESP) and Microgrid Control Platform (MCP) software development, Shediac Smart Energy Community Demonstration, and Smart Grid Nova Scotia Demonstration. These activities are part of a larger project with ongoing status and completion percentages noted.

Not a formal work package under this program, however, collaborations noted below: Unrestricted Page 5 of 15 Document # PM-FM-011 Version 5 2022-08-10 . . REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forecast Report Synap...

AI summary The text outlines various activities related to energy projects in Nova Scotia, including DER monitoring by Dalhousie University, a student's involvement in modeling DER program potential, and community engagement for a solar garden site. It also mentions the Tobique Microgrid Demonstration and North Branch Smart Energy Development, though details are sparse. A cost report for Siemens is included, focusing on foreign costs and deviations from the Contribution Agreement.

ogramming added to system design in order to prevent export to grid at C&I sites, per interconnection agreements. Initial design and implementation work was ongoing during this reporting period. Operational issues and other barriers/challe...

AI summary The document discusses operational issues with the Energy Services Platform (ESP), including software bugs and data correlation challenges. It also highlights a three-day outage at the Community Solar Garden due to faulty equipment and a 13% shortfall in solar production. Firmware updates for residential batteries and portal improvements were requested. Budget status is mentioned but not detailed.

elop extension module for Desigo CC V5 & configure connection for Site existing BMS and ESP $ GP Joule PV Canada Site 1 - Substantial completion (C&I Solar + Battery project) $ Mattatall Signs Ltd. Smart Grid NS project branding wrap insta...

AI summary The text lists various eligible and ineligible expenditures related to energy and infrastructure projects, including equipment, contracting services, and costs incurred for DERs, BMS, and ESP. It also references a redacted load forecast report and a smart grid semi-annual report.

ration defects including constraint management and connectivity to third-party vendor clouds. • Additional functionality being delivered to enable data extract for analysis in external platforms. Community Solar • Hurricane Fiona impacted...

AI summary The text discusses impacts from Hurricane Fiona on a community solar garden, including damage to solar modules and repairs completed by late September. It also covers solar production performance in July, August, and September, and ongoing discussions with NS Power regarding the temporary disabling of zero export mode for testing solar inverter functions.

ect (i.e. major effect on budget and/or the critical path schedule is at risk; an amendment is likely ☐ required) Percentage of total tasks completed to date 80 % pg. 1 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forec...

AI summary The report outlines the status of EV smart charger installations and bi-directional charger testing. All 100 EV smart chargers are installed, and testing for bi-directional chargers is ongoing, with delays due to certification and installation scheduling.

nstallation is underway. • NS Power has scheduled the installation of the Fermata 15kW bi-directional charger for October 2022 and anticipates this project will be completed by the end of October. ev.energy • ev.energy program launched 14...

AI summary NS Power is installing a Fermata 15kW bi-directional charger, with completion expected by late October 2022. The ev.energy program was launched in June 2022, onboarding new and transitioning existing Tesla drivers. Challenges include delays in bi-directional charger deliveries due to certification requirements, leading to the cancellation of one purchase order.

(2) No SIF, but the development of the new product was not part of the SIF iii) Other, please describe below: 5) Between Jan 2021 and Dec 2021, did your business or institution realise any cost savings (2) No from new or significantly impr...

AI summary The text includes redacted sections from a regulatory proceeding, including a Load Forecast Report and a Smart Grid Semi-Annual Report. It references cost savings and processes developed between January 2021 and December 2021, though no specific details are provided due to redaction.

lease note if estimates and/or different definitions of concepts were used from the APBR definitions) Sunday, January 1, 2017 Sunday, December 31, 2017 Friday, January 1, 2016 Saturday, December 31, 2016 Thursday, January 1, 2015 Thursday,...

AI summary The text includes dates and notes related to baseline data years calculated by the APBR form based on project start dates and fiscal years. It also references a redacted 2023 Load Forecast Report and a Smart Grid Semi-Annual Report, indicating the presence of confidential information.

ty or Region Halifax Latitude 44.64547° N Province/Territory Nova Scotia Longitude -63.5766° E 2 – WEB HIGHLIGHTS Title of Highlight Details & Description of Highlight • Customer selection for distributed batteries completed. • C&I custome...

AI summary The document highlights progress in NS Power's distributed battery customer selection and C&I contracts, the approval of the Solar Garden Rate Rider, and the development of a new Siemens ESP User Guide. It also outlines knowledge and media products generated during the fiscal year, including publications, presentations, and policy contributions.

of 205 CI C0010788 – Smart Grid Semi-Annual Report Attachment 13 Page 4 of 11 NATURAL RESOURCES CANADA EVID Annual Performance Report 2 – WEB HIGHLIGHTS Title of Highlight Details & Description of Highlight The Nova Scotia Power (NSP) Elec...

AI summary The document highlights progress on the Nova Scotia Power (NSP) Electric Vehicle Integration project, including use case testing and the addition of a new telematics platform. It also mentions the planned installation of bidirectional chargers and the submission of an annual performance report to Natural Resources Canada (NRCAN).

oducts include press releases, news coverage, etc. Did you produce or contribute to any knowledge products this year? Yes (Do not include media products in this response) Product Type Description/Weblink Media product, Media https://www.yo...

AI summary The text lists knowledge products created or contributed to by the entity, including presentations and lunch-and-learn sessions, and references a REDACTED Load Forecast Report and a Smart Grid Semi-Annual Report, along with a Natural Resources Canada EVID Annual Performance Report.

9 Attachment 2 Page 181 of 205 CI C0010788 – Smart Grid Semi-Annual Report Attachment 13 Page 5 of 11 NATURAL RESOURCES CANADA EVID Annual Performance Report Product Type Description/Weblink Media product, Media https://www.youtube.com/wat...

AI summary The document outlines various media and knowledge products related to the Smart Grid Initiative Fund (SIF) and Smart Grid Nova Scotia (SGNS), including presentations, panel discussions, and events attended by representatives such as Peter Gregg and Shawn Connell. These activities highlight innovation, electrification, and technology in the energy sector.

or management) is composed of women: NSP began self-identification in 2021; data will be provided in subsequent reports What share of the organization is owned by First Nations, Inuit, and Métis peoples? Select the category that most close...

AI summary The text provides information on Nova Scotia Power's (NSP) self-identification efforts starting in 2021, related to the representation of women and Indigenous peoples in the organization. It also references a redacted 2023 Load Forecast Report and a Smart Grid Semi-Annual Report, indicating the presence of confidential information.

tion? Please indicate the number of four month positions. 2) Were any co-ops hired to work directly on the SIF-funded project? (2) No ↓ Continue down to the bottom of the Page and Click the button to be taken to the next section of the que...

AI summary The text includes a questionnaire related to the Smart Grid Initiative Fund (SIF), asking about hiring cooperatives and collaborations for the SIF-funded project. It also mentions a redacted section of a 2023 Load Forecast Report and a Smart Grid Semi-Annual Report attachment.

tions and specific end uses in scope. Date Filed: June 20, 2023 NSPI (Synapse) IR-12 Page 1 of 2 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information R...

AI summary The document discusses the historic trend in electric heating shares and efficiency, noting that slow growth in electric heating has been offset by increased efficiency. However, in the forecast period, electric heating shares are expected to outpace efficiency gains, leading to an increase in overall intensity.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 Request IR-13: 2 3 Commercial and Industrial Growth (Section 4.4, pp 52-53) 4 5 (a) Please provide the detailed ca...

AI summary NSPI responded to Synapse Energy Economics' request regarding the 2023 Load Forecast Report, providing detailed calculations for commercial and industrial demand growth, including heat pump installations and customer growth factors.

2023 Load Forecast Report Synapse IR-13 Attachment 1 Page 2 of 4 Mass Solution Annualized kWh per Solution Annualized kWh per Annualized kWh per Solution Nameplate Tonnage kWh/Ton Nameplate Tonnage kWh/Ton Solution Nameplate (Heating Only)...

AI summary The document presents energy consumption data for various heat pump solutions, including annualized kWh per solution and nameplate tonnage kWh per ton for heating and cooling. The data includes different types of heat pumps such as rooftop, centralized, mini-split, and water source systems, along with their respective energy efficiency metrics.

Heat Pump Water Heater (Air-Water) 976.65 976.65 - Calculator V5 - (October 26, 2018) Old vs. new space/water heating system Fossil Fuel Displacement or Brand New System Is there an existing space cooling system OR were t None Customer Rat...

AI summary The text provides a snippet of a calculator tool used for comparing old and new space/water heating systems, with specific details about a centralized heat pump system (Air-Air) under the R22 customer rate class. It includes assumptions about energy usage and peak demand, but much of the content is redacted as confidential.

Statistics estimated the price elasticities in 49 U.S. States (excluding Hawaii) and found 25 variation across states. The mean of the estimates was –0.16. 2 A 2006 study prepared for 1 Bohi, Douglas R., and Mary Beth Zimmerman, “An Update...

AI summary The text discusses studies on energy demand price elasticity across U.S. states, referencing multiple academic sources. It mentions a 2006 study by the National Energy Research Lab and refers to a 2023 Load Forecast Report (NSUARB M11108) and related information requests.

al Peak 29 Pricing column). Date Filed: June 20, 2023 NSPI (Synapse) IR-19 Page 1 of 1 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NO...

AI summary NSPI explains the impact of COVID-19 on commercial sector load forecasts, noting reduced energy use in 2021 and 2022. The forecast shows an increase through 2033 due to the shift of EV load to the commercial sector, despite factors like solar adoption and demand-side management reducing sales.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 Request IR-22: 2 3 General Service (Section 6.2). 4 5 (a) Please explain and quantify the specific reasons for the...

AI summary The 2023 Load Forecast Report (NSUARB M11108) outlines responses from NSPI to Synapse Energy Economics' information requests. Key factors affecting load changes include EV load, RTR participation, DSM programs, and increased efficiency. The report notes EV load added 11.4% to class load, while RTR reduced load by 2.7%. DSM program effects decreased slightly compared to the 2022 forecast.

Heat Heat Cool Cool Other Other Heat Heat Cool Cool Intensity Intensity Intensity Intensity Intensity Intensity Heat share Heat share Cool share Cool share efficiency efficiency efficiency efficiency 2023 2022 2023 2022 2023 2022 2023 2022...

AI summary The document presents a table with data on heat and cool intensity, heat and cool share, and efficiency metrics for the years 2013 to 2020. It includes comparative figures for 2023 and 2022, indicating trends over time.

30 Attachment 1 Page 3 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045

AI summary The document outlines a study on Nova Scotia Energy Efficiency and Demand Response potential from 2021 to 2045. It provides an overview of energy efficiency and demand response initiatives that could be implemented over the next two decades.

IR-30 Attachment 1 Page 4 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045

AI summary This document is the IR-30 Attachment 1 Page 4 of 355 from the Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045. It outlines the scope and context of an energy efficiency and demand response study covering the period from 2021 to 2045.

e IR-30 Attachment 1 Page 5 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045

AI summary The document introduces a study on Nova Scotia Energy Efficiency and Demand Response Potential for the period 2021-2045, focusing on analyzing energy efficiency and demand response opportunities.

sults Across Demand Response Scenarios ..........................113 11.6.2 Comparison of Potential Results Across Scenarios ....................................................114 11.7 Demand Response Snapback Effects .......................

AI summary The document outlines a study on energy efficiency and demand response potential in Nova Scotia for the period 2021-2045. It includes sections on demand response scenarios, snapback effects, and concludes with findings on energy efficiency and demand response strategies.

tachment 1 Page 6 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045

AI summary This document is the beginning of a study on Nova Scotia Energy Efficiency and Demand Response Potential for the period 2021-2045. It outlines the scope and objectives of the study, which focuses on analyzing the potential for energy efficiency and demand response initiatives in the region.

chment 1 Page 7 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045

AI summary The document outlines a study on Nova Scotia Energy Efficiency and Demand Response Potential for the period 2021-2045. It aims to assess opportunities for energy efficiency and demand response initiatives during this timeframe.

chment 1 Page 8 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045

AI summary The document is titled 'Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045,' indicating it focuses on analyzing the potential for energy efficiency and demand response initiatives in Nova Scotia over the next two decades.

Page iii ©2019 Navigant Consulting, Ltd. . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 9 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 E. EX...

AI summary EfficiencyOne commissioned Navigant Consulting to conduct energy efficiency and demand response potential studies for Nova Scotia from 2021 to 2045. The study focuses on residential and business, nonprofit, and institutional sectors, aiming to assess energy efficiency measures, operational activities, and user behavior changes to reduce energy consumption. Results will inform integrated resource planning and program design.

mic and market savings potential across Nova Scotia. These results 1 will be used to inform integrated resource planning (IRP), and energy efficiency and demand response program design in Nova Scotia. E.1 Estimation of Energy Efficiency Po...

AI summary The text discusses the estimation of energy efficiency potential in Nova Scotia using Navigant's DSMSim™ model. The model calculates technical, economic, and market savings potential, considering different types of efficiency measures and their impacts across various sectors and customer segments.

he calculation only to those measures that have passed the benefit-cost test chosen for measure screening, in this case the Total Resource Cost (TRC) test or the Program Administrator Cost (PAC) test. Market potential (also referred to as...

AI summary The text discusses the calculation of market potential for demand-side management (DSM) measures, considering factors like equipment turnover, incentive levels, and consumer adoption. It differentiates between gross and net potential savings and references appendices for detailed analysis.

at is that, by definition, technical potential calculation does not consider participation overlaps. Therefore, the technical potential estimates for each DR option should be considered independently. Navigant assessed cost-effectiveness o...

AI summary The document discusses the technical and economic potential of energy efficiency (EE) and demand response (DR) in Nova Scotia, noting that technical potential calculations do not account for participation overlaps. Navigant assessed DR options, calculating achievable potential by multiplying participation assumptions with technical estimates and considering customer opt-out during events.

Cumulative Savings as a Percent of Total Sales (%) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 7 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 16 of 355 Nova Scot...

AI summary The document presents cumulative savings as a percentage of total sales and discusses the technical and economic potential of energy efficiency and demand response in Nova Scotia over a 25-year period, showing flat savings potential of 2,100 to 2,200 MW (gross at generator) and market potential ranging from 375 MW to 600 MW (net at generator).

Load (%) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 10 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 19 of 355 Nova Scotia Energy Efficiency and Demand Response...

AI summary The document discusses the market winter peak demand savings potential from energy efficiency (EE) and demand response (DR) in Nova Scotia, estimating scenarios ranging from 15% to 24% over a 25-year period, as analyzed by Navigant Consulting.

apse IR-30 Attachment 1 Page 24 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 1. INTRODUCTION This section provides an overview of the potential study, including background and study goals, a discus...

AI summary This section introduces the Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045, outlining its goals, methodology, and collaboration with EfficiencyOne and stakeholders through the Demand Side Management Advisory Group (DSMAG). The study uses validated modeling tools and incorporates stakeholder feedback to ensure accuracy and relevance to current market conditions.

bal input assumptions and measure characterizations. We also carefully considered, and as appropriate, were responsive to stakeholders’ input, incorporating their feedback into the analysis approach. 1.1 Context and Study Goals Navigant wa...

AI summary Navigant was retained by EfficiencyOne to estimate the potential for electric energy efficiency and demand response in Nova Scotia from 2021 to 2045. The study involves analyzing current energy use patterns, characterizing potential efficiency measures, and estimating achievable energy savings. The findings will support integrated resource planning and program design.

Study for 2021-2045 potential results are presented for DR options, sub-options, customer class, and building type for cost- effective DR options. Section 12 – presents the Conclusion of the study. The report also includes the following el...

AI summary The document outlines a study on energy efficiency and demand response potential from 2021 to 2045, including appendices with modeling plans, baseline studies, and model inputs and outputs for residential and commercial sectors.

11,159 Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 24 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 33 of 355 Nova Scotia Energy Efficiency and Demand Response Po...

AI summary Navigant and EfficiencyOne characterized 183 energy efficiency measures across Nova Scotia’s residential and BNI sectors, prioritizing those with high impact, data availability, inclusion in EfficiencyOne’s DSM Plan, and cost-effectiveness. The measures included are currently available in the market and economically viable.

gies measure that would attempt to capture potential savings from technologies not currently ready for the market. All measures included are currently available in the market and economically viable. 3.2 Energy Efficiency Measure Character...

AI summary The document discusses the characterization of energy efficiency measures, focusing on defining key parameters for each of the 183 measures included in the study. It emphasizes that all measures are currently available and economically viable, and outlines the process of defining over 50 parameters for each measure.

o EE Definition: Describes the efficient technology set to replace the baseline technology. o Unit Basis: The normalizing unit for energy, demand, cost, and density estimates. ©2019 Navigant Consulting, Ltd. Page 25 . REDACTED (CONFIDENTIA...

AI summary The document discusses the definition of efficient technology and the unit basis for energy, demand, cost, and density estimates in the context of a load forecast report for Nova Scotia's energy efficiency and demand response potential study from 2021 to 2045.

fficient technology, using the following variables: o Base Costs: The cost of the base equipment, including both material and labor costs. This is zero for retrofit measures. o EE Costs: The cost of the energy-efficient equipment, includin...

AI summary The text outlines key variables used in the analysis of efficient technology, including base and EE costs, technology densities, saturation levels, applicability, and competition groups. These metrics help assess the feasibility and impact of replacing baseline technologies with energy-efficient alternatives.

avings by End Use (GWh, gross at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 33 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 42 of 355 Nova Scotia Ene...

AI summary The document presents data on energy efficiency and demand response potential in Nova Scotia, highlighting residential and BNI lighting as major contributors to winter peak demand savings. HVAC systems are identified as having the largest impact on demand reduction, accounting for over 75% of the potential savings through energy efficiency.

ynapse IR-30 Attachment 1 Page 43 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 4.4 Energy Efficiency Technical Potential Results by Measure Figure 4-7 and Figure 4-8 present the top forty measures...

AI summary The document presents technical energy efficiency potential results for residential and BNI measures in Nova Scotia for 2021, highlighting the top forty measures ranked by electricity savings potential. The analysis includes adjustments for competition groups and identifies wood boilers/furnaces as the most effective residential heating measure.

generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 36 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 45 of 355 Nova Scotia Energy Efficiency and Demand Respons...

AI summary The document presents the top forty energy efficiency measures ranked by their winter peak demand technical savings potential for residential and BNI sectors in 2021. HVAC-related measures like Wi-Fi Thermostats, Wood Furnaces, and Air Source heat pumps are highlighted as major contributors to demand reduction.

Figure 4-10. EE Technical Potential, 2021 Top 40 BNI Measures for Winter Peak Demand Savings (MW, gross at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 38 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load...

AI summary This section discusses the economic savings potential of energy efficiency measures in Nova Scotia, focusing on cost-effective opportunities across sectors and end-use categories. Navigant's approach to calculating economic potential is outlined, along with results from different aggregation levels and a scenario using a PAC of 1.0 as the screening measure.

ghest-impact measures. Additionally, Navigant developed an economic potential scenario using a PAC of 1.0 as the measure screen instead of a TRC of 1.0. Results for this scenario are shown by sector. 5.1 Approach to Estimating Economic Pot...

AI summary The text discusses the estimation of economic potential using the Total Resource Cost (TRC) test, which evaluates the cost-effectiveness of energy efficiency measures. Measures with a TRC ratio of 1.0 or higher are included in the economic potential, as they provide monetary benefits equal to or greater than their costs.

port Synapse IR-30 Attachment 1 Page 48 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 5.2 Energy Efficiency Economic Potential Results by Sector Figure 5-1 shows economic electricity savings potenti...

AI summary The document presents economic electricity savings potential and winter peak demand savings by sector for Nova Scotia's energy efficiency and demand response initiatives from 2021 to 2045. Residential and BNI sectors show similar growth in economic savings potential, and high avoided costs from the 2014 Integrated Resource Plan influence the screening of high-saving measures.

emand Savings by Sector (MW, gross at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 41 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 50 of 355 Nova Scoti...

AI summary The document compares the economic electricity potential in residential and BNI sectors using the program administrator cost (PAC) test screen and the total resource cost (TRC) test. Results show similar economic potential under both tests, with slightly more measures qualifying under the PAC test.

generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 42 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 51 of 355 Nova Scotia Energy Efficiency and Demand Respons...

AI summary The document discusses the economic winter peak demand potential in residential and BNI sectors using a PAC cost test screen of 1.0, showing that economic potential is close to that using a TRC screen. This suggests that cost effectiveness screening was not a major limiting factor for economic potential.

generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 43 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 52 of 355 Nova Scotia Energy Efficiency and Demand Respons...

AI summary The document discusses the economic electricity savings potential in Nova Scotia, comparing BNI and Residential sectors. It highlights similarities in economic savings opportunities despite differences in industrial processes and emphasizes the importance of HVAC equipment and lighting in BNI for energy efficiency.

Report Synapse IR-30 Attachment 1 Page 53 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Figure 5-6 shows the economic winter peak demand potential as a percentage of consumption. Very similar trends...

AI summary The document discusses the economic winter peak demand potential as a percentage of consumption across various sectors in Nova Scotia, highlighting trends in energy efficiency and demand response. It notes that the BNI sector's economic potential closely follows technical potential due to fuel switching in HVAC, while residential sector differences are attributed to line loss factors.

ort Synapse IR-30 Attachment 1 Page 54 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 5.3 Energy Efficiency Economic Potential Results by End Use Figure 5-7 shows the economic electricity potential,...

AI summary The document presents economic potential results for energy efficiency and demand response in Nova Scotia from 2021 to 2045. HVAC and lighting are highlighted as key areas with significant savings potential, particularly in residential and BNI sectors. Wi-Fi enabled plugs also show potential due to their current low penetration.

gross at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 48 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 57 of 355 Nova Scotia Energy Efficiency and Deman...

AI summary The document discusses the economic potential of energy efficiency and demand response measures in Nova Scotia for 2021, focusing on the top 40 BNI measures. It notes that most technical potential is economically achievable, passing the TRC test of 1.0, with only a few large measures dropping out of the highest 20.

t technical potential is economically achievable, passes a TRC test of 1.0. Therefore, the measure mix of top 10 to 20 measures is largely the same as the technical potential results for both sectors. Figure 5-11. EE Economic Potential, 20...

AI summary The document presents economic potential for energy efficiency (EE) measures in residential and BNI sectors, highlighting that the top 10 to 20 measures align with technical potential results. Figures show savings in winter peak demand, sourced from Navigant analysis.

y efficiency investment is different for residential and BNI customers. 10 The model uses this information to simulate how customers in each sector will accept measures with differing payback periods. Since the payback time of a technology...

AI summary The document discusses how efficiency investment differs between residential and BNI customers, and how the model simulates technology adoption based on payback periods. It explains that equilibrium market share is recalculated annually due to changing technology and energy costs, and outlines two approaches for calculating equilibrium market share. Behavioral measures are modeled differently due to their low cost and reliance on marketing efforts.

Report Synapse IR-30 Attachment 1 Page 63 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 6.5 Energy Efficiency Incentive Strategy Per EfficiencyOne’s guidance, and as discussed with the DSM Advisory...

AI summary The study outlines an energy efficiency incentive strategy based on targeted payback and assumes 85% re-participation by program participants after the useful life of energy-efficient measures. This approach ensures that incentive costs are applied only during initial conversions and not for replacements of already efficient equipment, impacting cumulative savings calculations.

ogram participants that revert to the baseline after the effective useful life of the measure, this savings is removed from the cumulative potential to reflect the in-situ condition at each time-step. Behaviour measures, such as home energ...

AI summary The text discusses how energy efficiency savings from measures are calculated, noting that savings from measures reverting to baseline after their useful life are removed. Behaviour measures, such as home energy reports, are an exception, with incentives for re-adoption added to program spending. The section also introduces the topic of model calibration for energy efficiency forecasts.

ipient of model results with a level of comfort that simulated results are reasonable. For this study, Navigant took a number of steps to ensure that forecast model results were reasonable, including: • Identifying the subset of potential...

AI summary Navigant Consulting ensured the reasonableness of forecast model results by calibrating them against historic program achievements, using data from 2017 and conducting detailed backcasting for key lighting measures in ENS programs.

Report Synapse IR-30 Attachment 1 Page 64 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 the calibration process. It is important to note that although the team calibrated to historical results for t...

AI summary The report discusses the calibration process of a model used to estimate energy efficiency and demand-side management potential in Nova Scotia. It highlights that while the model was calibrated using historical data from specific measures, the total market potential may differ from past program achievements due to the inclusion or exclusion of certain measures.

orically not been included in programs, but may exclude certain historical measures as well. This discrepancy can cause calibrated base year potential to be lower or higher than historic program data. To obtain close agreement with Efficie...

AI summary The text discusses the calibration process used to align forecasted savings with historical data, involving adjustments to incentive levels and diffusion parameters. It also describes a backcasting exercise using the DSMSimTM model to simulate adoption of energy efficiency measures based on historical data.

ristic of “normal” market conditions. Figure 6-2. EE Backcast Results for Residential Screw-in LED (Gross kWh/year at Meter Backcast Comparison EfficiencyOne’s Historical Navigant Simulated Achievements Backcast Source: Navigant Analysis ©...

AI summary The document compares historical achievements and simulated backcast results for energy efficiency programs, specifically focusing on residential LED screw-in bulbs and BNI LED troffers. The analysis shows a close fit between historical data and simulations, with minor differences possibly influenced by non-economic factors.

EfficiencyOne’s Historical Navigant Simulated Achievements Backcast Source: Navigant Analysis ©2019 Navigant Consulting, Ltd. Page 58 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 6...

AI summary The document compares historical energy efficiency achievements with simulated backcast results for BNI Linear Replacement Lamps in Nova Scotia. It notes that the historical savings align well with the simulated trajectory, suggesting that these measures are past the inflection point and will experience slower growth due to market saturation.

ting Effect – 200% of reference scenario at the sector and end use level • Mid Scenario o Targeted Payback – Half of reference scenario at the sector and end use level o Marketing Effect – 150% of reference scenario at the sector and end u...

AI summary This section presents market potential results for energy efficiency and demand response in Nova Scotia, calculated using the TRC benefit-cost test with a threshold of 0.7. Results are shown by sector, end use category, and highest-impact measures, with varying levels of aggregation.

ings, by Scenario (GWh, net at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 61 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 70 of 355 Nova Scotia Energ...

AI summary The document discusses energy efficiency (EE) market potential in Nova Scotia from 2021 to 2045, showing increasing potential under different scenarios. Under the TRC ratio of 0.7, the base scenario market potential rises from 1.1% in 2021 to 22.3% in 2045. The low, mid, and maximum achievable scenarios reach 19.0%, 27.7%, and 30.8%, respectively.

Report Synapse IR-30 Attachment 1 Page 71 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Figure 8-3 show incremental annual electricity savings as a percent of sales for each scenario. The base scena...

AI summary The report presents the incremental annual electricity savings as a percent of sales for different energy efficiency scenarios in Nova Scotia from 2021 to 2045. The base scenario shows a decline in savings over time, attributed to technology saturation in sectors like BNI lighting. The residential and BNI sectors show significant saturation, while the commercial sector maintains consistent potential. These trends may cause the scenarios to diverge after the 25-year study period.

ity Savings by Scenario, as a Percent of Sales (%) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 63 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 72 of 355 Nova Sco...

AI summary The document presents cumulative winter peak demand savings by scenario, showing market potential increasing steadily through 2045, reaching 470 MW in the base scenario. By 2045, this represents 22% of the economic potential and 19% of the load.

Response Potential Study for 2021-2045 Figure 8-5 shows the cumulative winter peak demand potential by scenario as a percent of load. The base scenario cumulates to 1.0% in 2021 and 19.0% in 2045. Figure 8-5. EE Market Potential, Cumulativ...

AI summary The document discusses the potential for energy efficiency (EE) and demand response in Nova Scotia from 2021 to 2045, showing cumulative winter peak demand savings by scenario as a percentage of load. The base scenario shows a cumulative savings of 1.0% in 2021 and 19.0% in 2045, while incremental savings peak at 1.2% in 2028 before declining due to technology saturation and increasing costs.

t Report Synapse IR-30 Attachment 1 Page 75 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 8.2 Energy Efficiency Potential Results by Sector Figure 8-7 shows the magnitude of cumulative electricity m...

AI summary The document presents energy efficiency potential results for the residential and BNI sectors in Nova Scotia, showing cumulative electricity savings by scenario. The residential sector's base case reaches 1,415 GWh by 2045, while the BNI sector's base case reaches 1,275 GWh. These results represent percentages of economic potential in each sector.

umulative Electricity Savings (GWh, net at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 68 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 77 of 355 Nova...

AI summary The document presents cumulative winter peak demand savings potential for the residential and BNI sectors in Nova Scotia by 2045, showing different scenarios and their respective percentages of economic potential. The base case for residential reaches 285 MW, while for BNI it reaches 185 MW.

BNI sector. The base case reaches 185 MW in 2045. This represents 30% of economic potential in that year. In 2045, The low, mid and maximum achievable scenarios reach 130, 230 and 285 MW respectively. Figure 8-10. EE BNI Market Potential,...

AI summary The document discusses energy efficiency potential in Nova Scotia, focusing on the BNI sector and residential HVAC. It outlines market potential scenarios and highlights technologies like LED lighting and whole home retrofits that contribute to electricity savings.

Report Synapse IR-30 Attachment 1 Page 80 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Figure 8-12 shows the winter peak demand market savings potential, net at generator, across end uses. The domi...

AI summary The document discusses energy efficiency and demand response potential in Nova Scotia from 2021 to 2045. Key end uses include BNI lighting and residential HVAC, with LED troffers and whole home retrofits leading savings. Residential single-family market rate is the dominant customer segment for electricity savings.

Segment (MW, net at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 74 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 83 of 355 Nova Scotia Energy Efficienc...

AI summary The document presents energy efficiency potential results by measure for 2021, highlighting that residential screw-in LED bulbs and custom energy efficiency lead in electricity savings. The top ten measures account for over 50% of achievable savings in the residential sector, with a more gradual decline in savings potential in the BNI sector.

port Synapse IR-30 Attachment 1 Page 84 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Figure 8-16. EE Market Potential, 2021 Top 40 BNI Measures for Electricity Savings (GWh, net at generator) Sourc...

AI summary The document discusses the energy efficiency (EE) market potential in Nova Scotia for 2021, highlighting the top 40 Business and Non-Industrial (BNI) and residential measures for electricity savings. Residential whole home measures show the highest demand-saving potential, while BNI measures have a more evenly distributed potential.

Demand Savings (MW, net at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 77 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 86 of 355 Nova Scotia Energy Ef...

AI summary The document discusses the cost-effectiveness of energy efficiency (EE) measures in Nova Scotia, highlighting benefit-cost test ratios for the EE Base Case Market Potential. It notes that these ratios are generally greater than 1.0 across sectors and analysis years, except for the Rate Impact Measure (RIM) test, which shows lower ratios in certain years and sectors.

ct Measure (RIM) test, which has benefit-cost tests less than 1.0 for certain years and sectors. Figure 8-19. EE Base Case Market Potential, Benefit-Cost Test Ratios for the Portfolio and by Sector Total Program Impact Year Cost Test Measu...

AI summary The text references the Rate Impact Measure (RIM) test, which includes benefit-cost tests with ratios less than 1.0 for certain years and sectors. It also mentions Figure 8-19, which displays EE Base Case Market Potential and benefit-cost test ratios for the portfolio and by sector.

2045 3.03 4.25 4.27 0.76 ©2019 Navigant Consulting, Ltd. Page 79 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 88 of 355 Nova Scotia Energy Efficiency and Demand Response Potential...

AI summary Figure 8-20 shows the net benefits for the achievable base case in Nova Scotia's energy efficiency and demand response potential study, by sector and for the portfolio under each benefit-cost test. Net benefits are positive in all cases except the RIM test.

2040 $171.85 $195.66 $329.25 -$29.78 2045 $144.20 $163.29 $309.15 -$35.90 Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 80 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1...

AI summary The document presents a 25-year investment forecast for energy efficiency and demand response programs in Nova Scotia, showing annual investment levels ranging from $40 million to $65 million. Administrative costs are estimated at approximately 50% of total spending and remain constant across scenarios.

stant between achievable scenarios. Investment details for each scenario are provided in Appendix F. Figure 8-21. EE Base Case Investment, by Investment Type for the Portfolio (nominal million $) Variable Program Fixed Program Year Incenti...

AI summary The text discusses investment details for energy efficiency scenarios, with a focus on variable and fixed program administrative costs, and references Appendix F for further information.

2037 $38.36 $8.42 $8.60 $55.38 2038 $37.92 $8.26 $8.47 $54.65 2039 $37.79 $8.12 $8.33 $54.24 2040 $37.69 $7.95 $8.16 $53.80 2041 $36.10 $7.67 $7.87 $51.64 2042 $35.76 $7.51 $7.71 $50.98 2043 $35.28 $7.34 $7.54 $50.16 2044 $34.84 $7.18 $7.3...

AI summary The document presents a load forecast report analyzing energy efficiency and demand response potential in Nova Scotia from 2021 to 2045, with detailed financial figures and projections for various years.

t Report Synapse IR-30 Attachment 1 Page 90 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 8.7 Non-Programmatic Savings For this study, Navigant defines non-programmatic savings as reductions in savi...

AI summary The report discusses non-programmatic savings, defined as reductions in savings potential due to codes and standards and freeridership. It highlights that non-programmatic savings contribute 11% of total savings in 2021 and peak at 17% in 2025. The study also includes hourly loadshape disaggregation for base case achievable potential savings, developed at the request of the DSMAG stakeholder group.

has multiple non-linear components, the effects of varying a parameter is often asymmetrical. For each sensitivity, all other variables were held constant, allowing individual effects to be observed. Residential achievable potential sensit...

AI summary The analysis examines the sensitivity of residential energy efficiency potential to various parameters, including the net-to-gross ratio, marketing effects, and incentive changes. It highlights the asymmetrical impact of these factors and their influence on customer adoption, savings, and program effectiveness.

manifests in greater sensitivity than other model inputs, however, any reductions in net-to-gross ratio (as a result of an increase in freeridership) would be captured in the non-programmatic savings. By contrast, the avoided costs and dis...

AI summary The analysis highlights the sensitivity of achievable energy efficiency potential to various factors such as net-to-gross ratios, carbon prices, avoided costs, and incremental costs. It emphasizes that changes in these factors significantly impact the Total Resource Cost (TRC) and the benefit-cost ratio, particularly when considering the influence of carbon pricing and administrative costs.

Response Potential Study for 2021-2045 Figure 9-1. EE Residential 2045 Cumulative Achievable Potential Sensitivity (GWh, net at generator) Source: Navigant analysis ©2019 Navigant Consulting, Ltd. Page 84 . REDACTED (CONFIDENTIAL INFORMATI...

AI summary The document discusses the sensitivity analysis of energy efficiency (EE) residential and BNI (Business and Non-Industrial) achievable potential up to 2045. It highlights how changes in marketing, incentives, awareness, and other factors influence the cumulative potential, particularly in areas with steep payback curves and significant diminishing returns.

er classes. Step 4: Develop Key Assumptions for •Develop assumptions for participation, unit load reduction, and itemized Potential and Costs cost for each DR option. Step 5: Estimate Potential and Costs, •Present potential estimates, annu...

AI summary The document outlines a six-step process for assessing demand response (DR) potential, including developing assumptions, estimating potential and costs, and conducting scenario analysis. It emphasizes market characterization, segmentation, and the use of data from NS Power’s rate schedules and energy efficiency studies.

ponse Potential Study for 2021-2045 Figure 10-6. Customer Count Forecast by Building Type Source: Navigant 10.2.2 Peak Period Definition and Peak Demand Projections A key element of market characterization for the DR potential study is to...

AI summary The document outlines the methodology for developing peak demand projections for the DR potential study, including defining the peak period, calculating coincident peak demand factors, obtaining end use shares, and calibrating results to align with demand distribution. It also includes steps for forecasting energy sales after DSM and developing separate peak demand projections for EVs.

ers since these segments tend to be ineligible for DR programs. ©2019 Navigant Consulting, Ltd. Page 91 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 100 of 355 Nova Scotia Energy E...

AI summary The document provides baseline peak demand forecasts by customer class and building type for Nova Scotia, with residential and small commercial segments dominating. It also introduces a section on battery adoption projections.

Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 10.2.3 Battery Adoption Projections Due to a lack of information on battery adoption projections in Nova Scotia, Navigant developed high- level battery adoptio...

AI summary The document discusses battery adoption projections in Nova Scotia, using assumptions from Navigant Research and industry expertise. It estimates battery size, costs, and savings based on NS Power tariffs, and includes a non-economic adoption adder for residential customers. Projections follow a Bass-diffusion curve with a 10-year ramp rate.

0.2 Grand Total 7.9 85.2 91.2 Source: Navigant analysis 10.2.4 Electric Vehicle Projections The forecasts produced for this report are derived from Navigant’s Vehicle Adoption Simulation Tool (VASTTM). VASTTM integrates a provincial-level...

AI summary The document discusses electric vehicle (EV) projections using Navigant's Vehicle Adoption Simulation Tool (VASTTM), which models PEV adoption based on factors like cost, range, and customer behavior. Due to limited data on battery projections in Nova Scotia, Navigant used a simplified payback analysis approach for battery adoption.

re 10-13 presents the forecasted load impacts from PEVs. Figure 10-13. Demand Impacts from PEVs Source: Navigant analysis, NSPI 2019 Load Forecast 21 The decision to use EV forecasts using Navigant’s VAST model was based on discussions wit...

AI summary The document discusses the characterization of demand response (DR) options to curtail winter peak demand, including load curtailment, load shifting to behind-the-meter batteries, EV charging control, critical peak pricing, and behavioral demand response. These DR options are based on industry-standard programs.

Electric Furnace 22 Residential Control of electric loads by a thermostat Heat Pump 23 DCL Direct Load Control Small Commercial and/or load control switch. HVAC 24 Small Industrial Hot Water Firm capacity reduction commitment. HVAC Large C...

AI summary The text outlines various methods for managing and controlling electric loads, including direct load control, battery control, and EV charging control, across different customer classes such as residential, commercial, and industrial.

s dispatching to the grid. Charging modulation to reduce EV EV Charging Control EV EV demand during peak periods A rate schedule with significantly higher Critical Peak Pricing peak prices to discourage consumption All classes Total Facili...

AI summary The text outlines methods to manage electric vehicle (EV) demand during peak periods, including EV charging control and critical peak pricing (CPP), as well as behavioral demand response (BDR) strategies to encourage peak shaving. It also references a study on energy efficiency and demand response potential in Nova Scotia from 2021 to 2045.

ia Energy Efficiency and Demand Response Potential Study for 2021-2045 Figure 10-15. Summary of DR Sub-Options DR Option DR Sub-Option End Use DLC-Thermostat-Electric Furnace Electric Furnace DLC-Thermostat-Heat Pump Heat Pump DCL Direct L...

AI summary The document outlines various demand response (DR) sub-options, including direct load control and BNI curtailment, across different end uses such as electric furnaces, heat pumps, HVAC, lighting, and water heating. These options are part of a broader energy efficiency and demand response potential study for the period 2021-2045.

BNI Curtailment- Water Heating Control Water Heating BNI Curtailment- Industrial Total Facility BTM Battery Control BTM Battery Control Batteries EV Charging Control EV Charging Control EV CPP with enabling technology Critical Peak Pricing...

AI summary The document outlines various demand response (DR) and energy efficiency strategies, including direct load control (DLC) for residential and small BNI customers, BNI curtailment for large BNI customers, BTM battery control for all customer classes, and EV charging control during peak demand periods. These strategies aim to reduce demand and manage load during peak times.

customer incentives, O&M, etc. Global Parameters Program Lifetime, Discount Rate, Inflation Rate, Line Losses, Avoided Costs 27 Source: Navigant 26 The DR analysis assumed “default with opt-out” type of offer under the High Scenario and th...

AI summary The document discusses the calculation of demand response (DR) program potentials, including technical and market potentials, based on assumptions such as 'default with opt-out' and 'opt-in' offer types. It references avoided costs from the 2014 Integrated Resource Plan and Transmission and Distribution (T&D) costs provided by NS Power in 2018.

rticipant marketing and recruitment costs, annual program administration costs, O&M costs, and customer incentives. 10.4.1 Demand Response Base Case Assumptions 10.4.1.1 Participation and Hierarchy Participation assumptions are based on re...

AI summary The text discusses assumptions related to demand response (DR) participation, including the use of industry-standard S-shaped ramp curves over a 5-year period, and references participation assumptions by customer class and DR option. It also mentions the use of secondary sources such as FERC's DR program survey and detailed documentation in an Excel spreadsheet.

fficiency and Demand Response Potential Study for 2021-2045 Figure 10-19. Summary of Changes in Programmatic Assumptions Across Scenarios % change in % change in % change in marketing Scenario Applicable Customer Class incentives over part...

AI summary The document presents a summary of changes in programmatic assumptions across different scenarios for energy efficiency and demand response potential from 2021 to 2045, showing variations in incentives, marketing costs, and participation rates for different customer classes.

vigant analysis Page 104 ©2019 Navigant Consulting, Ltd. . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 113 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study f...

AI summary The document discusses the achievable demand response (DR) potential in Nova Scotia, estimating that DR potential will increase to 93 MW by 2027 and stabilize at 92 MW by 2045. This potential represents over 6% of Nova Scotia Power’s peak demand in 2027 and over 7% by 2045, as energy efficiency measures reduce overall peak demand.

0.73 EV Charging Control 3.05 11.08 0.28 0.26 Source: Navigant analysis 11.3.2 Demand Response Levelized Costs & Supply Curves Figure 11-5 shows the levelized costs and the corresponding 2045 achievable potential for all DR options. The le...

AI summary The document discusses the levelized costs and achievable potential for various demand response (DR) options in Nova Scotia through 2045. Critical Peak Pricing (CPP) is identified as the least costly option, while EV charging control is significantly more expensive due to high technology enablement costs.

gy Efficiency and Demand Response Potential Study for 2021-2045 Figure 11-5. DR Base Achievable Scenario Levelized Costs vs. 2045 Potential (MW at generator) Cumulative Achievable Cost-Effective Levelized Costs Cost-Effective DR Option Pot...

AI summary This section discusses the achievable potential results for cost-effective demand response (DR) options, including various DR strategies such as Critical Peak Pricing (CPP), Demand Load Control (DLC), and Behavioural DR, along with their corresponding levelized costs and potential contributions by 2045.

s under the base case scenario. 11.4.1 Achievable Potential by DR Option for Cost-Effective DR Options Figure 11-6 shows the MW breakdown of the DR achievable potential by cost-effective DR option. Figure 11-6. DR Achievable Potential by D...

AI summary The document discusses the achievable potential of demand response (DR) options under a base case scenario, showing that the potential increases to about 81 MW by 2026 and then declines to 72 MW by 2035. DLC accounts for nearly half of the potential, followed by CPP and BNI Curtailment.

consistent once the program is fully ramped by 2026. Figure 11-11. DR Annual Program Costs by DR Option for Cost-Effective DR Options ($) Source: Navigant Analysis Page 112 ©2019 Navigant Consulting, Ltd. . REDACTED (CONFIDENTIAL INFORMATI...

AI summary The document discusses demand response (DR) scenario analysis results, including adjustments to participation levels, incentive amounts, marketing spending, and equipment saturation. These adjustments impact DR achievable potential and peak demand forecasts, which are tied to different demand reduction scenarios from an energy efficiency potential study.

Behavioural DR 5.52 5.78 0.96 Base BTM Battery Control 19.17 22.91 0.84 High CPP 177.98 36.08 4.93 High Behavioural DR 8.13 8.17 1.00 High DLC 39.46 43.56 0.91 High BNI Curtailment 9.47 10.21 0.93 High BTM Battery Control 5.53 9.54 0.58 Hi...

AI summary The document presents data on the performance of various demand response (DR) programs, including behavioural DR, BTM battery control, CPP, DLC, BNI curtailment, and EV charging control, under different scenarios (high and low) with associated cost metrics.

illion in 2022 to $12.0 million in 2045 for the high scenario • $2.4 million in 2021 to $12.1 million in 2045 for the low scenario 11.6.2 Comparison of Potential Results Across Scenarios Figure 11-14 and Figure 11-15 show a comparison of t...

AI summary The document compares achievable demand response (DR) potential across different scenarios, showing that the high scenario has 18% more potential than the base scenario, while the low scenario has 24% less. These potentials are expressed as percentages of NSP’s peak demand in 2045.

s conducted by Navigant to draw on insights related to snapback. ©2018 Navigant Consulting, Inc. Page 117 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 126 of 355 Nova Scotia Energy...

AI summary The study provides updated information on Nova Scotia's customer base and the potential for energy and demand reductions through energy efficiency and demand response programs. It highlights the remaining potential but notes unique challenges in realizing it over the next 25 years.

response programs and initiatives. While much energy efficiency (and demand response) potential remains, there are unique challenges in Nova Scotia in realizing this potential over the next 25 years.

AI summary The text highlights the remaining potential for energy efficiency and demand response programs in Nova Scotia, while noting unique challenges in realizing this potential over the next 25 years.

12.1 Energy Efficiency • Near-term Electricity Savings: The majority of near-term savings are from the Res HVAC, Res Lighting, and BNI Lighting end uses. Residential screw-in LED Bulb ranks as the highest electricity- saving market potenti...

AI summary The text discusses energy efficiency in Nova Scotia, highlighting near-term electricity and winter peak demand savings from residential and BNI lighting and HVAC measures. It notes the success of EfficiencyOne in implementing energy efficiency programs and challenges posed by market saturation, tightening codes, and low net-to-gross ratios, particularly for lighting.

cal and economic potential are attributed to HVAC fuel switching measures that completely remove the end-use load from a home. Although still a significant portion of potential, achievable results indicate that efficient electrification te...

AI summary The text discusses the potential of HVAC fuel switching and efficient electrification technologies like heat pumps for reducing energy use, but notes market barriers to adoption. It also highlights the dominance of Critical Peak Pricing (CPP) and Direct Load Control (DLC) in achieving demand response savings over a 25-year period, with the remaining savings coming from BNI curtailment.

DLC sub-options. The remaining savings are estimated from BNI curtailment. ©2018 Navigant Consulting, Inc. Page 118 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 127 of 355 Nova Sco...

AI summary The document discusses demand response (DR) options in Nova Scotia that can provide significant demand savings over a 25-year period. It emphasizes the need for collaboration between NS Power and EfficiencyOne to realize these savings. The text also outlines a modelling plan for an energy efficiency and demand response study.

between Navigant and EfficiencyOne, and to inform stakeholders regarding the methodology, activities, deliverables, and timelines related to the EE and DR studies being conducted. i . Date Filed: August 14, 2019 Page 2 of 40 REDACTED (CONF...

AI summary Navigant, on behalf of EfficiencyOne, will use two Analytica-based models to assess energy efficiency (EE) and demand response (DR) potential in Nova Scotia. The models will be presented in Excel for review by EfficiencyOne, regulatory intervenors, and the Nova Scotia Utility and Review Board (UARB).

ecast Report Synapse IR-30 Attachment 1 Page 131 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A • Ability to handle avoided costs, retail rates, and load shape profiles at multiple levels...

AI summary The text outlines key features of a modeling tool used for energy efficiency and demand response studies. It highlights capabilities such as handling avoided costs, load shape profiles, and evaluating cost-effectiveness at various intervals. The model also supports recurring incentives, administrative costs, and switching between net and gross savings.

analysis • All summary results and intermediate calculations are immediately available in tabular or graphical form and can be exported to Excel As a starting point, the analysis will incorporate data from the 2020-2022 DSM Plan recently s...

AI summary The analysis incorporates data from the 2020-2022 DSM Plan and the 2018 Potential Study Update. It evaluates approximately 350 energy efficiency measures across residential and BNI sectors, targeting a TRC test threshold of 1.0 for economic potential and 0.7 TRC for achievable potential. Updates to the DSM Plan will be made if new information or measures are added.

s added compared to the recent measure set developed. 2 . Date Filed: August 14, 2019 Page 4 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 132 of 355 Nova Scotia Energy Efficien...

AI summary The document outlines the use of Navigant’s DRSim™ and DSMSimTM models to analyze demand response and energy efficiency potential in Nova Scotia. It mentions the inclusion of programs such as direct load control, peak time rebates, and behind-the-meter batteries in the analysis.

nt, Navigant will develop a set of energy sales forecasts for electric consumption and electric peak demand, disaggregated by sector (e.g., residential and BNI), and end use. The reference forecasts will span the 25-year study period, from...

AI summary Navigant will develop energy sales forecasts for electric consumption and peak demand, disaggregated by sector and end use, to serve as a reference for calculating DSM savings potential over a 25-year period from 2021 to 2045.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 137 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary The document is a page from the 2023 Load Forecast Report, specifically Attachment 1 of Synapse IR-30, which includes the Nova Scotia Energy Efficiency and Demand Response Potential Study for the period 2021-2045. This appendix provides supporting information for the study.

trends to be applied to each customer segment. EUI trends are intended to reflect natural changes in electricity consumption as a result of two factors: (1) natural conservation and (2) natural growth. • Natural conservation is a well-esta...

AI summary The text discusses the concept of natural conservation and natural growth in electricity consumption, particularly within the context of DSM programs. It outlines how EUI trends reflect changes in consumption due to these factors and highlights the importance of defining natural conservation, including the impact of future building codes and appliance standards on conservation potential.

ergy and capacity costs • Consumer price forecast • Retail rates • Line loss factors 2.1.2 Step 3: Define, Characterize and Screen Efficiency Measures The next step in the potential estimation process is to define and characterize energy e...

AI summary This section discusses the process of defining and characterizing energy efficiency measures (EEMs) as part of a study on Nova Scotia's energy efficiency and demand response potential from 2021 to 2045. The focus is on actions that increase efficiency or reduce demand through equipment, control strategies, or behavior changes.

chment 1 Page 139 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A 2.1.2.1 Define Efficiency Measures Navigant’s process for defining potential EEMs includes developing a comprehensive list...

AI summary Navigant's process for defining and characterizing energy efficiency measures (EEMs) includes compiling a comprehensive list from residential, BNI, and peak load reduction categories. They will use existing ENS DSM programs, the ENS TRM, and emerging technologies, while leveraging prior analyses to expedite the process. A final list of recommended measures will be presented for review.

rs for review and discussion, and highlight any which were not included in the 2018 ENS Potential Study Update or the 2020-2022 ENS DSM Plan. 2.1.2.2 Characterize Efficiency Measures After Navigant and E1 have reached agreement on a final...

AI summary The document outlines the process for reviewing and characterizing energy efficiency measures, including identifying energy and demand savings, associated costs, and avoided costs from fuel-switching measures. The process involves combining market characteristics with measure-specific data to ensure accurate cost-effectiveness testing.

ics (energy/demand reduction, water, costs, market maturity, etc.). 10 . Date Filed: August 14, 2019 Page 12 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 140 of 355 Nova Scotia...

AI summary The document outlines the process for leveraging prior measure characterization analyses and updating them as necessary for the energy efficiency and demand response potential study. It emphasizes estimating energy savings, costs, and applicability for each measure, with defined units and supporting documentation.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 141 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A There are three general types of energy efficiency and renewable energy resourc...

AI summary The document outlines three types of energy efficiency and renewable energy resource potential: technical, economic, and achievable. Technical potential refers to what can be saved using available technologies, economic potential considers cost-effectiveness, and achievable potential accounts for market constraints and program impacts. Navigant will estimate these potentials in sequence.

le potential. Figure 9 illustrates the key inputs and the layers of the potential modelling approach. Figure 9. Approach to Market Potential Analysis The analysis for technical and economic potential is modeled on the measure level only. T...

AI summary The text describes a method for analyzing market potential in energy efficiency and demand response, focusing on technical and economic potential at the measure level, and considering the cost of incentives and program delivery.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 142 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary This document is part of a 2023 Load Forecast Report and includes an appendix from a study on Nova Scotia's energy efficiency and demand response potential for the period 2021-2045.

direct install and rebate programs, for example) and the program delivery or administrative cost (upstream versus downstream). The achievable potential analysis will be addressed and reported at the sector level (residential and BNI) by en...

AI summary The text discusses the analysis of achievable potential for energy efficiency programs, including baseline market conditions, technology portfolios, customer behavior modeling, and the state of the Nova Scotia electricity system. The analysis will be conducted at the residential and BNI sectors, considering up to five scenarios due to budget and timeline constraints.

system peak demand o Number and type of customers o Sector-level energy and demand requirements o Net energy and system-peak demand savings, at the generator, of energy efficiency measures (after free-ridership, spillover, and interactive...

AI summary The text discusses the development of technical potential for energy efficiency measures, defining it as the energy savings achievable by replacing existing measures with efficient ones wherever technically feasible. It highlights different ways of characterizing savings, such as fixed amounts for condensing water heaters and percentages for automated building controls.

ated building controls are typically characterised as a percentage of customer 13 . Date Filed: August 14, 2019 Page 15 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 143 of 355...

AI summary The document discusses energy efficiency and demand response potential in Nova Scotia for the period 2021-2045, referencing a load forecast report and an appendix from a study.

ynapse IR-30 Attachment 1 Page 143 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary This document is part of a study on the potential for energy efficiency and demand response in Nova Scotia from 2021 to 2045. It is an appendix to a larger report and contains detailed information relevant to the analysis of energy efficiency and demand response initiatives.

segment consumption or per square foot; and, lastly, measures such as industrial ventilation heat recovery are well-suited for estimating energy savings as a percentage of end use consumption. The DSMSimTM model can appropriately handle sa...

AI summary The text discusses methods for estimating energy savings through energy efficiency (EE) measures, including the use of the DSMSimTM model. It outlines technical potential calculations based on measure replacement types and highlights the distinction between savings from new construction and retrofit measures. The study considers all possible EE measures without economic feasibility constraints.

homes, customer-segment consumption/sales, etc.). 14 . Date Filed: August 14, 2019 Page 16 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 144 of 355 Nova Scotia Energy Efficiency...

AI summary The document discusses the technical suitability and total technical potential (TTP) for energy efficiency and demand response in Nova Scotia from 2020 to 2029, based on the Annual Incremental Technical Potential (AITP) for each year.

Retrofit (RET) and Replace-On-Burnout (ROB) Measures RET measures, commonly referred to as advancement or early-retirement measures, are replacements of existing equipment before the equipment fails. RET measures can also be efficient proc...

AI summary The text explains the difference between Retrofit (RET) and Replace-On-Burnout (ROB) measures in energy efficiency programs. RET measures involve replacing equipment before failure, while ROB measures replace failed equipment. The text also discusses how technical potential is calculated differently for RET and ROB measures compared to new measures.

homes, customer-segment consumption/sales, etc.). 15 . Date Filed: August 14, 2019 Page 17 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 145 of 355 Nova Scotia Energy Efficiency...

AI summary The document references a 2023 Load Forecast Report and an Energy Efficiency and Demand Response Potential Study for the period 2021-2045, indicating analysis related to energy consumption and demand response strategies in Nova Scotia.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 145 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary The document is a page from the 2023 Load Forecast Report by Synapse, specifically Attachment 1 of the Nova Scotia Energy Efficiency and Demand Response Potential Study covering the period 2021-2045. This appendix likely contains detailed data or analysis related to energy efficiency and demand response potential in Nova Scotia.

across measures (e.g., at the end use, customer segment, sector, service territory or total level). If a competition group is composed of more than one measure that passes the TRC test, then 17 . Date Filed: August 14, 2019 Page 19 of 40 R...

AI summary The text discusses the evaluation of energy efficiency and demand response potential in Nova Scotia for the period 2021-2045, referencing a 2023 Load Forecast Report and an appendix from a study. It mentions the use of TRC (Total Resource Cost) tests for competition groups composed of multiple measures.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 147 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A the economic measure that provides the greatest savings potential is included i...

AI summary The document outlines the process for calculating economic potential using the DSMSimTM model, which screens DSM measures based on a TRC threshold of 1.0. It emphasizes avoiding double-counting and ensures accurate representation of economic potential by using technical potential results as input.

Figure 11. Navigant’s Economic Potential Model Data Flow 18 . Date Filed: August 14, 2019 Page 20 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 148 of 355 Nova Scotia Energy Eff...

AI summary The document discusses the development of achievable potential in the context of energy efficiency and demand response initiatives in Nova Scotia, focusing on modeling and forecasting for the period 2021-2045.

ment 1 Page 148 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A 2.1.3.3 Develop Achievable Potential

AI summary This section discusses the development of achievable potential in the context of energy efficiency and demand response initiatives in Nova Scotia, focusing on strategies to realize the identified energy efficiency and demand response potential for the period 2021-2045.

This section presents the approach to calculating achievable potential, which is fundamentally more complex than the calculation of technical or economic potential. The potential study will estimate the annual and cumulative achievable pot...

AI summary This section outlines the approach to calculating achievable energy and peak demand savings potential through energy efficiency (EE), involving up to five scenarios with varying incentives. The process includes simulating market adoption of energy-efficient measures and determining equilibrium market share, considering stakeholder feedback and sector-level analysis.

). For energy- efficient technologies, a key differentiating factor between the base technology and the efficient technology is the energy and cost savings associated with the efficient technology. Of course, that additional efficiency oft...

AI summary The text discusses the factors influencing the adoption of energy-efficient technologies, focusing on the balance between initial costs and long-term energy savings. It mentions the use of payback time to estimate market share and the development of payback acceptance curves based on consumer surveys.

diffusion model 10, 11 to simulate the S-shaped approach to equilibrium that is commonly observed for technology adoption. Figure 13 provides a stock/flow diagram illustrating the 9 Each of these approaches can be better understood by visi...

AI summary The text discusses the use of a diffusion model to simulate the S-shaped approach to equilibrium in technology adoption, referencing academic sources and a simulation tool. It is part of a load forecast report and energy efficiency study for Nova Scotia covering the period 2021-2045.

management models, therefore, must rely on other techniques to provide both the developer and the recipient of model results with a level of comfort that simulated results are reasonable. 23 . Date Filed: August 14, 2019 Page 25 of 40 REDA...

AI summary The text discusses the importance of management models in providing confidence in simulated results, referencing a 2023 Load Forecast Report and an Energy Efficiency and Demand Response Potential Study for 2021-2045. It highlights the need for techniques that ensure the reasonableness of model outcomes for both developers and recipients.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 153 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary The document refers to a 2023 Load Forecast Report and an Energy Efficiency and Demand Response Potential Study for the period 2021-2045. It includes an appendix, likely containing detailed data or analysis related to energy efficiency and demand response initiatives in Nova Scotia.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 154 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary The document is a page from the 2023 Load Forecast Report and an appendix of the Nova Scotia Energy Efficiency and Demand Response Potential Study covering the period 2021-2045. It is part of a larger analysis related to energy efficiency and demand response in Nova Scotia.

7. BNI: HVAC, electric water heating, lighting, industrial (for each segment) processes, electric vehicles, batteries Level 1: Sector Navigant will segment customers between the residential and business, non-profit and institutional (BNI)...

AI summary The document outlines the segmentation of customers for demand response (DR) and energy efficiency (EE) analysis, including residential, business, non-profit, institutional (BNI), and industrial sectors. It details how different customer segments are grouped and analyzed, with special attention to low-income and First Nation customers.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 163 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix A

AI summary The document is a page from the 2023 Load Forecast Report, specifically Appendix A of the Nova Scotia Energy Efficiency and Demand Response Potential Study covering the period 2021-2045.

idential Sector and BNI Sector Baseline Study Prepared for: Efficiency One 230 Brownlow Avenue, Suite 300 Dartmouth, NS B3B 0G5 Submitted by: Navigant Consulting, Ltd. First Canadian Place 100 King Street West Suite 4950 P.O. Box 64 Toront...

AI summary This document is a baseline study for the Nova Scotia residential and BNI sectors, prepared by Navigant Consulting for Efficiency One. It focuses on energy efficiency and demand response potential, with a submission date of June 19, 2019, and a filing date of August 14, 2019.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 175 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix B 2. SUMMARY OF FINDINGS – RESIDENTIAL SECTOR This section presents detailed find...

AI summary The document provides a summary of findings from a residential sector survey conducted in Nova Scotia, highlighting regional distribution of survey responses, with the majority coming from the Halifax region. It is part of a broader study assessing energy efficiency and demand response potential from 2021 to 2045.

sources used to heat homes in Nova Scotia. ©2019 Navigant Consulting, Ltd. Page 5 . Date Filed: August 14, 2019 Page 9 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 177 of 355 N...

AI summary This text discusses the primary heating source fuel types used in Nova Scotia residences, with electricity being the most common (33%), followed by oil (31%), heat pumps (16%), and other sources such as wood/pellets/chips, natural gas, and propane.

and then heat pump (16%), wood/pellets/chips (9%), natural gas (4%), propane (2%). Figure 4. Residential Sector – Primary Heating Source Fuel Type 2.4 Residential – Clothes Dryers The vast majority of respondents have a clothes dryer in th...

AI summary The document discusses residential heating sources and appliance usage in Nova Scotia, highlighting the prevalence of heat pumps, wood/pellets/chips, natural gas, and propane. It also provides data on the age and types of clothes dryers and washing machines in residential homes.

of the time. The survey found the 65% of clothes washers were five years old or older. Figure 6. Residential Sector – Washing Machines 2.6 Residential – Refrigerators and Freezers Virtually all respondents have a fridge in their home with...

AI summary The text discusses the age and usage patterns of household appliances in the residential sector, including washing machines, refrigerators, freezers, and power bars, with a focus on energy efficiency and the potential for demand response initiatives.

circuitry is designed to monitor and control power to each electrical outlet in the strip to improve energy efficiency and prevent household electronics from wasting power. Figure 8. Residential Sector – Power Bars ©2019 Navigant Consultin...

AI summary The document discusses residential energy efficiency in Nova Scotia, focusing on power bars and water heaters. It highlights the prevalence of water heaters in homes, the types of water heaters used, and the absence of advanced models like heat pump or smart water heaters. The data comes from a survey and is part of a broader energy efficiency and demand response potential study.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 183 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix B 2.10 Residential – Mini-Split Heat Pumps As reported in Figure 12, one-quarter...

AI summary The document discusses residential energy efficiency in Nova Scotia, focusing on the adoption of mini-split heat pumps and thermostats. One-quarter of respondents have at least one mini-split heat pump, and the average household has five thermostats, none of which are smart or programmable.

Figure 13. Residential Sector – Thermostats ©2019 Navigant Consulting, Ltd. Page 13 . Date Filed: August 14, 2019 Page 17 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 185 of 35...

AI summary The text discusses findings from a study on residential energy efficiency and demand response potential in Nova Scotia. It highlights the average number of lightbulbs in homes and the prevalence of LED bulbs, noting that no bulbs are smart bulbs connected to the internet.

2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 186 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix B 2.13 Residential – Dimmers and Sensors As seen in Figure 15, nearly one-half of...

AI summary The document discusses residential energy efficiency in Nova Scotia, highlighting that nearly half of respondents have manual light dimmers and a smaller number have outdoor motion sensors. It also outlines that a majority of respondents would pursue energy efficiency projects with a $75 cost and $35 or more annual savings, or a 2-year payback period.

Figure 16. Residential Sector – Cost Savings (Lower Cost Project) ©2019 Navigant Consulting, Ltd. Page 16 . Date Filed: August 14, 2019 Page 20 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attac...

AI summary The text discusses residential sector cost savings based on survey responses, highlighting that a majority of respondents would pursue energy efficiency projects with annual savings of $550 or more, or a two-year payback period. It also mentions residential demographics and participation from all three regional municipalities.

Figure 20. Residential Sector – Household Income Type ©2019 Navigant Consulting, Ltd. Page 18 . Date Filed: August 14, 2019 Page 22 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page...

AI summary The document provides a summary of survey responses from the BNI sector in Nova Scotia, highlighting the regional distribution of responses, with the majority coming from the Halifax region. This data is part of a broader study on energy efficiency and demand response potential from 2021 to 2045.

Figure 31. BNI Sector – LED Lighting ©2019 Navigant Consulting, Ltd. Page 25 . Date Filed: August 14, 2019 Page 29 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 197 of 355 Nova...

AI summary The document discusses findings from the BNI Sector regarding LED lighting and lighting controls. It highlights the average number of occupancy sensors and the lack of automatic light fixtures. Additionally, it presents data on cost savings, showing that a majority of BNI respondents would pursue a $7,500 project with a $5,000 annual savings or a 1.5-year payback period.

Figure 33. BNI Sector – Cost Savings (Lower Cost Project) ©2019 Navigant Consulting, Ltd. Page 26 . Date Filed: August 14, 2019 Page 30 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1...

AI summary The text discusses cost savings for the BNI sector based on survey responses, indicating that businesses would pursue projects with annual savings of $65,000 or more, or a 1.5-year payback period. It also mentions online survey findings for residential and BNI sectors in a study on energy efficiency and demand response potential.

did not know the age of their home. Household Income 29% of respondents indicated they are low income (low income cut-offs based on Statistics Canada measures). 71% of respondents are not low income. Utility Bill Payment 89% of residents s...

AI summary The survey found that 29% of respondents are low income, and 89% pay their own electricity bills. The majority of respondents are located in the Halifax Regional Municipality and Elsewhere in Mainland Nova Scotia. The data is part of a residential lighting study in the 2023 Load Forecast Report.

achment 1 Page 200 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 Appendix B 4.1.2 Residential Lighting A summary of the distribution of all lighting types for both interior and exterior lamps is sho...

AI summary This section discusses the distribution of residential lighting types in Nova Scotia, noting that 80% of light bulbs are general service bulbs and 13% are specialty bulbs. The survey collected data on various lighting types, including LED and smart lighting, as well as information on dimming and motion detectors.

o have a smart water heater. A summary of shower heads and faucets is shown in Figure 39. Figure 39. Residential Water Conservation Profile Measure / Characteristic Online Survey Findings Shower Heads 92% of residential homes have one or t...

AI summary The text summarizes findings from a survey on residential water conservation measures, including the prevalence of shower heads and faucets in homes, with a focus on low-flow shower heads and faucet aerators. It references a 2023 Load Forecast Report and an Energy Efficiency and Demand Response Potential Study for 2021-2045.

for 2021-2045 Appendix B 4.2.3 Controlling Energy Usage Figure 43 lists findings for controlling energy usage in BNI facilities.. Figure 43. BNI Controls Profile Measure / Characteristic Online Survey Findings Power Bars 94% of respondents...

AI summary The document presents findings from an online survey regarding energy usage controls in BNI facilities. It highlights the prevalence of power bars, computer servers, and the limited adoption of energy-efficient technologies such as smart power bars, variable frequency drives, and electrically commutated motors.

equipment, or appliances had an ECM installed. ©2019 Navigant Consulting, Ltd. Page 34 . Date Filed: August 14, 2019 Page 38 of 42 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 206 of...

AI summary The document provides appendices containing online survey instruments used to gather data on energy-related characteristics of residential and non-residential buildings in Nova Scotia as part of an energy efficiency and demand response potential study.

o not have a particular equipment type, please enter ‘0’ in the quantity box. Section A: Background/Ownership To begin… 1. Do you reside in… CODE ONE ONLY 1 Cape Breton Island 2 Halifax Regional Municipality (HRM) 3 Elsewhere on Mainland N...

AI summary The text contains a survey form related to a residential energy efficiency and demand response study in Nova Scotia, including questions about residence location, postal code, and gender. It is part of a 2019 study and includes a redacted confidential section.

e specify: ) 98 Don’t know /Not sure Please note that in the remaining questions, home refers to your primary place of residence in Nova Scotia. © Narrative Research, 2019 2 . Date Filed: August 14, 2019 Page 2 of 15 REDACTED (CONFIDENTIAL...

AI summary This section of the survey asks respondents about the number and age of electric clothes dryers in their homes, specifically focusing on heat pump dryers and their age categories. The survey is part of a larger study on energy efficiency and demand response potential in Nova Scotia.

ank wrap, that is, have 8 insulation overtop of the metal exterior of the tank? © Narrative Research, 2019 6 . Date Filed: August 14, 2019 Page 6 of 15 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 At...

AI summary The text contains survey questions related to residential energy efficiency, specifically focusing on the number and age of hot water heaters and shower heads in homes. The questions are part of a 2019 survey on energy efficiency and demand response potential in Nova Scotia.

UMBER _ 98 Don’t know 22. How many shower heads do you have in your home? RECORD NUMBER _ 98 Don’t know 23. [POSE ONLY IF 1 OR MORE IN Q.22] Of this/these [INSERT NUMBER FROM Q.22] shower head(s), how many are low-flow, that is, they use l...

AI summary The text includes survey questions about household water fixtures, such as the number of shower heads and faucets, and whether they are low-flow. These questions are part of a residential survey conducted in 2019 as part of a load forecast and energy efficiency study in Nova Scotia.

e, that is, you can set schedules to 8 control the temperature? 28aa. [POSE ONLY IF 1 OR MORE IN Q 28B] Of this/these [INSERT NUMBER FROM Q.28B] programmable thermostat(s), how many are RECORD Don’t know NUMBER a) smart thermostats you ca...

AI summary The text includes survey questions about programmable thermostats and home energy efficiency, focusing on customer participation and technology usage. It is part of a larger study on energy efficiency and demand response potential in Nova Scotia.

8 DISPLAY IMAGE Section H: Willingness/Awareness RANDOMIZE ORDER OF 32-35 & 33-34 32. Before today, how familiar were you with: ROTATE LIST; RANDOMLY POSE ONLY ONE OF THESE ITEMS 0 - Completely 1 2 3 4 5 6 7 8 9 10 – Unfamiliar Completely...

AI summary The text presents survey questions related to consumer awareness and willingness to participate in energy efficiency programs, specifically focusing on heat pump technologies and the financial considerations of energy efficiency projects.

generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[INSERT RANDOM AMOUNT FROM TABLE BELOW] per year? © Narrative Research, 2019 10 . Date Filed: August 14, 2019 Page 10...

AI summary The text discusses a hypothetical energy efficiency project where the cost to a customer after utility rebates is $1,000, and the annual savings are determined by a random amount from a table. It references a 2019 residential survey and a 2023 load forecast report.

1 2 8 i) $1,300 1 2 8 33. Before today, how familiar were you with: ROTATE LIST; RANDOMLY POSE ONLY ONE OF THESE ITEMS 0- 1 2 3 4 5 6 7 8 9 10 – Completely Completely Unfamiliar Familiar a. Networked/Connected – Indoor LED lights (i....

AI summary The text asks respondents about their familiarity with various energy efficiency technologies and whether they would pursue an energy efficiency project with a specific cost and annual savings, assuming no impact on comfort.

ou generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[INSERT RANDOM AMOUNT FROM TABLE BELOW] per year? © Narrative Research, 2019 11 . Date Filed: August 14, 2019 Page 11...

AI summary The text discusses a hypothetical scenario where a customer is asked if they would generally pursue an energy efficiency project with a specific cost and annual savings. It appears to be part of a survey or study related to residential energy efficiency in Nova Scotia.

within a First Nations Community? 1 Yes 2 No 3 Prefer not to say 98 Don’t know/Not sure 39. What is the main source of energy used to heat your principal place of residence? RANDOMIZE PRESENTATION, KEEPING “OTHER” AND “DON’T KNOW” LAST – C...

AI summary The document includes survey questions related to energy use in residential heating, specifically asking about the main source of heating and additional heating types. The questions are part of a larger residential energy survey conducted in 2019.

know/Not sure That concludes the survey. Thank you for your assistance and input. It is greatly appreciated! © Narrative Research, 2019 15 . Date Filed: August 14, 2019 Page 15 of 15 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Fo...

AI summary This text is from a survey conducted by Efficiency Nova Scotia to understand energy usage in Nova Scotia. The survey aims to improve energy-related programs and is anonymous. Respondents are asked to provide information about their business and equipment.

ervers on a single rack, but we want to know the number of individual servers. RECORD NUMBER _ 98 Don’t know/Not sure © Narrative Research, 2019 2 . Date Filed: August 14, 2019 Page 2 of 16 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023...

AI summary The text contains survey questions related to server usage and hot water heaters in a commercial setting, with responses indicating uncertainty or lack of knowledge. It is part of a larger energy efficiency and demand response study for Nova Scotia.

Q8 TOTAL MINUS Q9A TOTAL] hot water heaters, how many are heat pump water heaters? RECORD NUMBER: 98 Don’t know/Not sure © Narrative Research, 2019 3 . Date Filed: August 14, 2019 Page 3 of 16 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 20...

AI summary The text includes a survey question about the number of heat pump water heaters in a building, part of a larger study on energy efficiency and demand response potential in Nova Scotia. It also references a confidential report and a load forecast study.

Not Yes No Don’t know Applicable a) Have open coolers, that is, coolers 1 2 8 9 that do not have covers or doors? b) Have strategic energy management or organized management approach? This is the process of 1 2 8 9 monitoring, cont...

AI summary The text presents a series of questions regarding the presence of specific energy management features in facilities, including open coolers, strategic energy management approaches, door heater controls, packaged terminal heat pumps, and variable frequency drives in heating, cooling, and ventilation systems.

and ventilation systems, VFD automatically controls the speed of any fans or pumps. 13. Approximately, how many motors does your business’ HVAC, refrigeration equipment or appliances have? RECORD NUMBER: 98 Don’t know/Not sure 14. [POSE IF...

AI summary The text contains survey questions about HVAC, refrigeration, and lighting systems in a business setting, including the number of motors and types of lighting used. It is part of a 2019 commercial survey related to energy efficiency and demand response potential in Nova Scotia.

al service lights (i.e. have a base sized like a normal light bulb _ _ 8 and screw into regular light sockets) © Narrative Research, 2019 6 . Date Filed: August 14, 2019 Page 6 of 16 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load F...

AI summary The text discusses a survey item from the 2019 E1 Commercial Survey, asking respondents to report the number of smart LED light bulbs connected to the internet among those previously reported in question 15. This relates to energy efficiency and demand response potential.

highlight outdoor objects and features). f) General service lights (i.e. have a base sized like a normal light bulb _ 8 and screw into regular light sockets) g) Parking garage lights _ 8 17. Approximately, how many occupancy sensors does...

AI summary The text includes survey questions related to lighting fixtures and occupancy sensors in commercial buildings, focusing on energy efficiency measures such as daylighting controls and occupancy sensors. The questions are part of a 2019 survey on energy efficiency and demand response potential in Nova Scotia.

otential Study for 2021-2045 Appendix B-2 2019 E1 Commercial Survey – Final e. Packaged Terminal heat pump (A PTHP provides heating and cooling room by room often for applications such as hotels, motels, apartment buildings, offices, among...

AI summary The text outlines potential energy efficiency projects, including heat pumps and motor upgrades, and poses a hypothetical question about pursuing a project with a $100,000 cost after rebates and annual savings varying based on random selection.

enerally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[INSERT RANDOM AMOUNT FROM TABLE BELOW] per year? © Narrative Research, 2019 9 . Date Filed: August 14, 2019 Page 9...

AI summary The text discusses the cost-benefit analysis of energy efficiency projects, focusing on the point at which a project becomes financially viable after utility rebates. It references a 2019 commercial survey and an energy efficiency and demand response potential study for Nova Scotia.

LED bulbs) j. General service light (have a base sized like a normal light bulb and screw into regular light sockets) 22. Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business,...

AI summary This text presents a scenario asking respondents whether they would pursue an energy efficiency project with a $7,500 cost after rebates, depending on the annual savings. It includes options for savings ranging from $500 to $9,500 and asks respondents to indicate their decision with 'Yes,' 'No,' or 'Don’t know.'

2 Head office or other department pays 3 No, landlord pays 98 Don’t know/Not sure 99 Other (Please specify: _) 26a. [POSE IF CODES 1 OR 2 IN Q.26] Please select the electric utility provider that provides electricity at your business’ Nova...

AI summary The text includes survey response options related to electricity provider selection and rate codes for businesses in Nova Scotia, along with a reference to a redacted 2019 commercial survey and a load forecast report attachment.

3 Large commercial 4 Small Commercial 5 Industrial 6 Institutional 98 Don’t know/Not sure 30. What is the main source of energy used to heat your business’ Nova Scotia location where you work? RANDOMIZE PRESENTATION, KEEPING “OTHER” AND “D...

AI summary The text presents survey questions related to energy usage in commercial and industrial settings in Nova Scotia, focusing on heating sources and additional heating systems. The survey includes response options and instructions for data collection.

collects heat from tubes in the ground outside of your building) 7 Other (Please Specify: ) 98 Don’t Know/Not Sure © Narrative Research, 2019 15 . Date Filed: August 14, 2019 Page 15 of 16 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 L...

AI summary The text includes a survey response option related to heat collection systems and references a 2019 commercial survey as part of a load forecast report and energy efficiency study. It also contains a redacted section and a page reference from a legal document.

1.7 28.1 24.2 26.8 25.8 32.3 32.1 31.4 28.6 Responses of 'Don't know' or above 85 were excluded from calculation of the mean. 20 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 20 of 54 REDACTED (CONFIDENTIAL INFORMATION...

AI summary The document contains statistical data and references to a 2023 Load Forecast Report and a Nova Scotia Energy Efficiency and Demand Response Potential Study. It includes a narrative research section filed on August 14, 2019, and mentions a redacted confidential attachment from Synapse IR-30.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 32_2: Before today, how familiar were you with: ENERGY STAR Mini Split Heat Pumps

AI summary The text references a survey question about familiarity with ENERGY STAR Mini Split Heat Pumps, part of a 2019 electricity usage survey conducted by NAVIGANT.

2019 Electricity Usage Surveys - Residential TABLE 32_2: Before today, how familiar were you with: ENERGY STAR Mini Split Heat Pumps

AI summary The text references a 2019 electricity usage survey focusing on residential energy use and includes a table asking respondents about their familiarity with ENERGY STAR Mini Split Heat Pumps prior to a specific date.

REGION GENDER AGE LOW INCOME HOME HEATING TYPE(S) INEXPENSIVE UPGRADES EXPENSIVE UPGRADES AGE OF HOME OVERALL % Other HRM Cape Breton Male Female 18-34 35-54 55+ Yes No Own Rent Oil Electricity Heat pump Familiar (7-10) Unfamiliar (0-6) Fa...

AI summary The text presents a table with demographic and housing-related data, including gender, age, low-income status, home ownership, heating types, and familiarity with energy upgrades. It includes percentages and counts across various categories, such as age groups, regions, and heating sources.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 35A: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed and M...

AI summary The text discusses a hypothetical energy efficiency project with no impact on home comfort but may cause inconvenience and cost $1,000 after rebates, saving $100 annually. It references a survey conducted by Navigant in 2019 on residential electricity usage.

example might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[100] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and $100 annual savings would be pursued, highlighting considerations around cost-benefit analysis in energy efficiency initiatives.

192 243 248 111 162 220 129 334 336 157 206 289 145 233 260 123 370 96 84 62 80 This table excludes those who responded 'Don't know' to any of Q35a-i. TABLE 35B: Suppose an energy efficiency project has NO impact on the QUALITY of lighting...

AI summary This table excludes respondents who answered 'Don't know' to any of Q35a-i. It presents a scenario where an energy efficiency project has no impact on home comfort but may cause inconvenience and cost $1,000 after rebates, saving $250 annually.

example might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[250] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and annual savings of $250 would be pursued, highlighting considerations around cost and savings.

192 243 248 111 162 220 129 334 336 157 206 289 145 233 260 123 370 96 84 62 80 This table excludes those who responded 'Don't know' to any of Q35a-i. 30 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 30 of 54 REDACTED (...

AI summary The document includes a table with numerical data and notes that it excludes respondents who answered 'Don't know' to any of Q35a-i. It also references a 2023 Load Forecast Report, an attachment from Synapse IR-30, and an Energy Efficiency and Demand Response Potential Study for 2021-2045, including Appendix B-3.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 35C: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed and M...

AI summary This section of the document presents a hypothetical scenario about an energy efficiency project that may cause inconvenience but does not affect the quality of lighting, heating, and cooling. It asks respondents whether they would pursue such a project if the cost after rebates is $1,000 and the annual savings are $400.

example might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[400] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and $400 annual savings would be pursued, highlighting considerations around cost and savings.

192 243 248 111 162 220 129 334 336 157 206 289 145 233 260 123 370 96 84 62 80 This table excludes those who responded 'Don't know' to any of Q35a-i. TABLE 35D: Suppose an energy efficiency project has NO impact on the QUALITY of lighting...

AI summary This table and question explore customer willingness to pursue energy efficiency projects with a $1,000 cost after rebates, assuming annual savings of $550 and potential inconvenience. It excludes respondents who answered 'Don't know' to related questions.

example might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[550] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and annual savings of $550 would be pursued. The focus is on the cost-benefit analysis of such projects.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 35E: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed and M...

AI summary This text presents a hypothetical scenario from a 2019 residential electricity usage survey, asking respondents if they would pursue an energy efficiency project with a $1,000 cost after rebates and annual savings of $700, assuming no impact on comfort and some inconvenience.

example might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[700] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and $700 annual savings would be pursued, highlighting considerations around cost and savings.

192 243 248 111 162 220 129 334 336 157 206 289 145 233 260 123 370 96 84 62 80 This table excludes those who responded 'Don't know' to any of Q35a-i. TABLE 35F: Suppose an energy efficiency project has NO impact on the QUALITY of lighting...

AI summary This table and question explore consumer willingness to pursue energy efficiency projects with a $1,000 cost after rebates and annual savings of $850, assuming no impact on home comfort but potential inconvenience.

example might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[850] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and annual savings of $850 would be pursued, highlighting considerations around cost-benefit analysis in energy efficiency initiatives.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 35G: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed and M...

AI summary This text presents a hypothetical scenario from a 2019 residential electricity usage survey, asking respondents if they would pursue an energy efficiency project costing $1,000 after rebates, which saves $1,000 annually, assuming no impact on home comfort and potential inconvenience.

xample might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[1000] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and annual savings of $1,000 would be pursued.

192 243 248 111 162 220 129 334 336 157 206 289 145 233 260 123 370 96 84 62 80 This table excludes those who responded 'Don't know' to any of Q35a-i. TABLE 35H: Suppose an energy efficiency project has NO impact on the QUALITY of lighting...

AI summary The table presents survey data on willingness to pursue energy efficiency projects with a $1,000 cost after rebates, assuming annual savings of $1,150 and potential inconvenience. Respondents who answered 'Don't know' are excluded.

xample might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[1150] per year?

AI summary The text presents a hypothetical scenario asking if an energy efficiency project with a $1,000 cost after rebates and annual savings of $1,150 would be pursued, highlighting considerations around cost-benefit analysis in energy efficiency initiatives.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 35I: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed and M...

AI summary The text presents a hypothetical scenario from a 2019 electricity usage survey asking residential customers about their willingness to pursue an energy efficiency project with a $1,000 cost after rebates and annual savings of $1,300, potentially involving inconvenience.

xample might be installing new [ITEM SEEN IN Q32]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $1,000 if the project saved $[1300] per year?

AI summary The text presents a hypothetical scenario asking whether an energy efficiency project with a $1,000 cost after rebates and $1,300 annual savings would be pursued, highlighting considerations around cost-benefit analysis for such projects.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 34A: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed. An e...

AI summary This text presents a hypothetical scenario from a 2019 electricity usage survey, asking respondents if they would pursue an energy efficiency project with a $75 cost after rebates and annual savings of $15.

68 202 244 258 118 164 222 122 342 346 158 215 294 149 243 261 133 371 102 90 59 80 This table excludes those who responded 'Don't know' to any of Q34a-i. TABLE 34B: Suppose an energy efficiency project has NO impact on the QUALITY of ligh...

AI summary This text presents a table and a question regarding energy efficiency projects, asking respondents if they would pursue a project with a $75 cost after rebates that saves $25 annually, assuming no impact on the quality of lighting, heating, and cooling.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[25] per year?

AI summary The text discusses energy efficiency projects and asks whether one would pursue a project with a cost of $75 after rebates if it saves $25 annually, highlighting the cost-benefit analysis of such initiatives.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 34C: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed. An e...

AI summary This text presents a hypothetical scenario from a 2019 electricity usage survey, asking residential participants about their willingness to pursue an energy efficiency project with a $75 cost after rebates and annual savings of $35.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[35] per year?

AI summary The text discusses energy efficiency project cost-benefit analysis, asking if a project with a $75 cost after rebates and $35 annual savings would be pursued. It references an example from ITEM SEEN IN Q33.

68 202 244 258 118 164 222 122 342 346 158 215 294 149 243 261 133 371 102 90 59 80 This table excludes those who responded 'Don't know' to any of Q34a-i. TABLE 34D: Suppose an energy efficiency project has NO impact on the QUALITY of ligh...

AI summary This table presents data from respondents who answered a question about pursuing an energy efficiency project with a $75 cost after rebates and annual savings of $45. It excludes individuals who responded 'Don't know' to any of Q34a-i.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[45] per year?

AI summary The text discusses the consideration of energy efficiency projects, specifically whether to pursue a project with a cost of $75 after rebates and annual savings of $45. It references an example from [ITEM SEEN IN Q33].

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 34E: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed. An e...

AI summary This excerpt from Appendix B-3 of a Nova Scotia regulatory proceeding discusses a hypothetical energy efficiency project with no impact on home comfort but reduced energy consumption. It asks respondents if they would pursue such a project if the cost after rebates was $75 and the annual savings were $55.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[55] per year?

AI summary The text discusses energy efficiency projects and the cost-benefit analysis of such projects, specifically asking if an energy efficiency project with a cost of $75 (after rebates) and annual savings of $55 would be pursued.

68 202 244 258 118 164 222 122 342 346 158 215 294 149 243 261 133 371 102 90 59 80 This table excludes those who responded 'Don't know' to any of Q34a-i. TABLE 34F: Suppose an energy efficiency project has NO impact on the QUALITY of ligh...

AI summary The text presents a table and a question about energy efficiency projects, specifically asking respondents if they would pursue a project with a $75 cost after rebates that saves $65 annually, assuming no impact on home comfort.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[65] per year?

AI summary The text discusses energy efficiency projects, specifically whether to pursue a project with a cost of $75 after rebates and annual savings of $65. It references an example seen in Q33.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 34G: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed. An e...

AI summary This excerpt from a 2019 electricity usage survey asks residential customers about their willingness to pursue an energy efficiency project with a $75 annual savings after rebates, assuming no impact on the quality of lighting, heating, and cooling.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[75] per year?

AI summary The text discusses energy efficiency projects, specifically asking if a project costing $75 after rebates, which saves $75 annually, would be pursued. It references an item seen in Q33.

68 202 244 258 118 164 222 122 342 346 158 215 294 149 243 261 133 371 102 90 59 80 This table excludes those who responded 'Don't know' to any of Q34a-i. TABLE 34H: Suppose an energy efficiency project has NO impact on the QUALITY of ligh...

AI summary This text presents a table and a question related to energy efficiency projects, asking respondents whether they would pursue a project with a $75 cost after rebates that saves $85 annually, assuming no impact on home comfort.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[85] per year?

AI summary The text discusses the consideration of energy efficiency projects, specifically whether to pursue a project with a cost of $75 after utility rebates that saves $85 per year. It includes a placeholder reference to an item seen in Q33.

Appendix B-3 NAVIGANT 2019 Electricity Usage Surveys - Residential TABLE 34I: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your home, but changes the amount of energy consumed. An e...

AI summary This excerpt from Appendix B-3 discusses a hypothetical energy efficiency project that does not affect the quality of home comfort but reduces energy consumption. It asks respondents whether they would pursue such a project if it cost $75 after rebates and saved $95 annually.

nergy consumed. An example might be [ITEM SEEN IN Q33]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $75 if the project saved $[95] per year?

AI summary The text discusses energy efficiency projects and asks whether they would be pursued if the cost after rebates is $75 and the annual savings is $95. It references an example seen in Q33.

458 544 218 784 169 170 150 153 TABLE 39: What is the main source of energy used to heat your principal place of residence?

AI summary The text presents a table with numerical data and a question about the main source of energy used for heating a principal place of residence.

REGION GENDER AGE LOW INCOME HOME HEATING TYPE(S) INEXPENSIVE UPGRADES EXPENSIVE UPGRADES AGE OF HOME OVERALL % Other HRM Cape Breton Male Female 18-34 35-54 55+ Yes No Own Rent Oil Electricity Heat pump Familiar (7-10) Unfamiliar (0-6) Fa...

AI summary The text presents a table with demographic and energy usage data, including gender, age, income, home ownership, heating types, and the familiarity with energy upgrades across different regions in Nova Scotia.

REGION GENDER AGE LOW INCOME HOME HEATING TYPE(S) INEXPENSIVE UPGRADES EXPENSIVE UPGRADES AGE OF HOME OVERALL % Other HRM Cape Breton Male Female 18-34 35-54 55+ Yes No Own Rent Oil Electricity Heat pump Familiar (7-10) Unfamiliar (0-6) Fa...

AI summary The text presents a table with demographic and energy-related data, including gender, age, income, home ownership, heating types, and familiarity with energy upgrades. It reflects statistics across different regions in Nova Scotia.

6.8 5.3 1.4 5.7 13.7 2.9 6.5 13.1 5.0 7.6 7.4 Responses of greater than 100 were excluded from calculation of the mean. 4 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 4 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED)...

AI summary The text includes a table from a 2019 electricity usage survey focusing on business servers and their use of server virtualization and decommissioning. It also mentions a load forecast report and a study on energy efficiency and demand response potential in Nova Scotia.

175 105 21 49 101 70 51 49 38 44 59 34 60 100 44 8 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 8 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 303 of 355 N...

AI summary The text presents a table from a 2019 electricity usage survey for businesses in Nova Scotia, focusing on the use of variable frequency drives (VFDs) in heating, cooling, and ventilation systems. It is part of a larger study on energy efficiency and demand response potential.

2019 Electricity Usage Surveys - Business TABLE 11B: [IF Q10C 'Yes', OR CODED AS ZERO IF Q10C 'No'] How many of each does your business have? Door heater controls such as anti-sweat heaters (ASH)? These are electric resistance heaters that...

AI summary The text refers to a 2019 electricity usage survey for businesses, specifically asking about the number of door heater controls (anti-sweat heaters) in refrigerated cases, which are commonly found in grocery and convenience stores.

NAVIGANT 2019 Electricity Usage Surveys - Business TABLE 11D: [IF Q10E 'Yes', OR CODED AS ZERO IF Q10E 'No'] How many of each does your business have? Systems with variable frequency drive (VFD)? In your heating, cooling and ventilation sy...

AI summary The text references a 2019 electricity usage survey for businesses, specifically focusing on the number of systems with variable frequency drives (VFD) in heating, cooling, and ventilation systems. The survey item asks businesses to report how many such systems they have.

o'] How many of each does your business have? Systems with variable frequency drive (VFD)? In your heating, cooling and ventilation systems, VFD automatically controls the speed of any fans or pumps.

AI summary The text asks about the number of systems with variable frequency drives (VFD) in heating, cooling, and ventilation systems, explaining that VFD automatically controls the speed of fans or pumps.

89 19 44 87 64 44 43 34 39 52 32 50 89 41 MEAN 1.7 1.9 1.5 1.4 1.9 1.3 1.2 1.5 3.0 .9 1.5 3.5 1.7 2.2 2.2 Responses of greater than 10 were excluded from calculation of the mean. TABLE 14: [IF Q13 1 OR MORE] Of this/these motors, how many...

AI summary The text presents a table with numerical data and a question about the use of EC Motors in HVAC, refrigeration equipment, or appliances. The table includes mean values and excludes responses over 10 from the calculation. The question asks for the number of such motors using EC Motors, which are electronically commutated motors that vary speed using electronic controls.

2019 Electricity Usage Surveys - Business TABLE 15B/16B (Responses shown as a proportion of the total number of specific items, and not of the number of respondents): Pole mounted area lights which is exterior lighting generally used to pr...

AI summary The text presents data from 2019 Electricity Usage Surveys for businesses, specifically focusing on pole-mounted area lights. The data includes the number of non-LED and LED bulbs, presented as a proportion of the total number of bulbs.

s (LED + non-LED)] Q15C_1. Number of Non-LED Bulbs Q15C_2. Number of LED Bulbs Q16C. [IF Q15C_LED 1 OR MORE] Of these LED light bulbs, how many are connected to the internet (i.e., smart lightbulbs)? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents survey data on the number of LED and non-LED bulbs, the proportion of LED bulbs connected to the internet (smart bulbs), and demographic information about businesses in Nova Scotia, including region, ownership, employee count, square footage, and heating types.

38 27 4 7 25 12 13 8 15 9 15 11 11 32 11 14 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 14 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 309 of 355 Nova Sc...

AI summary The text provides data from a 2019 electricity usage survey for businesses in Nova Scotia, focusing on the proportion of downlight luminaires (spotlights set in ceilings) in use, with responses shown as a percentage of total bulbs (LED and non-LED).

s, and not of the number of respondents): Downlight luminaire which is a small spotlight set in a ceiling and directed downwards [Proportions are shown as a percentage of total bulbs (LED + non-LED)] Q15D_1. Number of Non-LED Bulbs Q15D_2....

AI summary The text presents survey data on the adoption of LED bulbs and internet-connected smart bulbs across different regions and business premises in Nova Scotia. It includes statistics on the proportion of LED bulbs, internet-connected bulbs, and sample sizes by region, business type, and heating type.

s (LED + non-LED)] Q15E_1. Number of Non-LED Bulbs Q15E_2. Number of LED Bulbs Q16E. [IF Q15E_LED 1 OR MORE] Of these LED light bulbs, how many are connected to the internet (i.e., smart lightbulbs)? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text contains survey questions and data on the number of LED and non-LED bulbs, as well as the proportion of LED bulbs connected to the internet, across various regions and business premises in Nova Scotia. It also includes data on heating types and square footage.

59 33 7 19 37 18 14 19 16 12 20 14 19 40 19 15 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 15 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 310 of 355 Nova...

AI summary The text presents data from the 2019 Electricity Usage Surveys - Business, focusing on general service lights and their proportion in total bulbs (LED + non-LED). It includes a table reference from the 2023 Load Forecast Report and a study on Nova Scotia Energy Efficiency and Demand Response Potential for 2021-2045.

r of respondents): General service lights (i.e. have a base sized like a normal light bulb and screw into regular light sockets) [Proportions are shown as a percentage of total bulbs (LED + non-LED)] Q15F_1. Number of Non-LED Bulbs Q15F_2....

AI summary The text presents data on the adoption of LED bulbs and smart lightbulbs in Nova Scotia, including proportions by region, business premises type, employment size, square footage, and heating type. The data is based on survey responses, with larger sample sizes excluded for analysis.

th: IT load optimization strategy (Server refresh and virtualization) (A way of reducing the number of physical computer servers by running multiple, independent operating systems on a single server)

AI summary The text discusses an IT load optimization strategy involving server refresh and virtualization, which aims to reduce the number of physical servers by running multiple operating systems on a single server.

1.7 1.0 .0 1.2 2.0 1.7 .9 2.3 1.6 1.8 3.3 This question was randomly posed to approximately one in seven respondents. 18 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 18 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED)...

AI summary The text includes a table from a 2019 electricity usage survey focusing on business respondents' familiarity with heat pump water heaters. It also references a load forecast report and a study on energy efficiency and demand response potential in Nova Scotia.

2.0 1.7 2.5 1.0 2.3 2.7 2.5 3.2 .6 2.8 2.8 This question was randomly posed to approximately one in seven respondents. 21 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 21 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED...

AI summary The text includes a table from a 2019 electricity usage survey asking respondents about their familiarity with Packaged Terminal Heat Pumps (PTHP), which are used for room-by-room heating and cooling in various building types.

2.9 4.6 3.9 2.0 3.8 3.3 4.3 4.0 3.8 3.9 4.7 This question was randomly posed to approximately one in seven respondents. 22 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 22 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVE...

AI summary The text includes a table from a 2019 electricity usage survey focusing on business respondents' familiarity with EC motors for refrigeration applications. The table is part of a larger study on energy efficiency and demand response potential in Nova Scotia.

.4 1.5 3.5 1.8 4.0 1.3 2.7 3.2 2.5 2.5 2.9 This question was randomly posed to approximately one in seven respondents. 23 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 23 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED...

AI summary The text includes a table from a survey regarding familiarity with the Strategic Energy Management Program, which aims to help organizations improve energy performance. It is part of a 2019 electricity usage survey for businesses, included in a load forecast report and energy efficiency study.

re you with: Strategic energy management program (This involves processes that empower an organization to implement energy management actions and consistently achieve energy performance improvements)

AI summary The text introduces the Strategic Energy Management Program, which empowers organizations to implement energy management actions and achieve consistent energy performance improvements.

NAVIGANT 2019 Electricity Usage Surveys - Business TABLE 23A: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in...

AI summary The text discusses a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause inconvenience. It asks whether a business would pursue such a project if the cost after rebates is $100,000 and annual savings are $5,000.

alling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[5,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question about pursuing energy efficiency projects with a $100,000 cost after rebates and annual savings of $5,000, along with a table showing responses by region and business premises characteristics.

162 99 19 44 97 63 47 44 38 43 57 32 53 96 41 TABLE 23B: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in some...

AI summary The text presents a hypothetical scenario involving an energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause inconvenience. It asks whether a project costing $100,000 after rebates, saving $20,000 annually, would be pursued.

lling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[20,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents survey data on energy efficiency project adoption, showing that 30% of respondents would pursue a project costing $100,000 after rebates if it saved $20,000 annually. The data is categorized by region, business premises, employment size, square footage, and heating type.

NAVIGANT 2019 Electricity Usage Surveys - Business TABLE 23C: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in...

AI summary The text discusses a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause some inconvenience. It asks whether a business would pursue such a project if the cost after rebates is $100,000 and it saves $35,000 annually.

162 99 19 44 97 63 47 44 38 43 57 32 53 96 41 TABLE 23D: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in some...

AI summary The text presents a hypothetical scenario regarding an energy efficiency project with no impact on lighting, heating, and cooling quality but may cause inconvenience. It asks whether a project costing $100,000 after rebates, saving $50,000 annually, would be pursued.

lling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[50,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question about pursuing an energy efficiency project with a $100,000 cost after rebates and annual savings of $50,000. It also includes a table with regional and business premises data, including heating types and employee counts.

NAVIGANT 2019 Electricity Usage Surveys - Business TABLE 23E: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in...

AI summary This text discusses a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause inconvenience. It asks whether a business would pursue such a project if the cost after rebates is $100,000 and it saves $65,000 annually.

lling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[65,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question regarding the pursuit of energy efficiency projects with a cost of $100,000 after utility rebates and potential annual savings of $65,000. It also includes a table with regional and business premises data, including heating types and employee counts.

162 99 19 44 97 63 47 44 38 43 57 32 53 96 41 TABLE 23F: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in some...

AI summary The text discusses a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause inconvenience. It asks if a project costing $100,000 after rebates, which saves $80,000 annually, would be pursued.

NAVIGANT 2019 Electricity Usage Surveys - Business TABLE 23G: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in...

AI summary The text discusses a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause inconvenience. It asks whether a business would pursue such a project if the cost after rebates is $100,000 and the annual savings are $95,000.

lling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[95,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question regarding the pursuit of an energy efficiency project with a cost of $100,000 after rebates and annual savings of $95,000, along with a table showing responses by region, business premises, and heating type.

162 99 19 44 97 63 47 44 38 43 57 32 53 96 41 TABLE 23H: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in some...

AI summary The text presents a scenario involving an energy efficiency project with no impact on the quality of lighting, heating, and cooling but may cause inconvenience. It asks whether the respondent would pursue the project if the cost after rebates is $100,000 and it saves $110,000 annually.

ling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[110,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question regarding energy efficiency project investment and includes a table with regional and business premises data, showing the percentage of respondents who would pursue a project with specific cost and savings parameters.

NAVIGANT 2019 Electricity Usage Surveys - Business TABLE 23I: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed and MAY result in...

AI summary The text discusses a hypothetical energy efficiency project with no impact on lighting, heating, and cooling but may cause inconvenience. It asks whether a business would pursue a project costing $100,000 after rebates if it saves $125,000 annually.

ling or implementing a(n) [ITEM SEEN IN Q20]. Would you generally pursue an energy efficiency project where the cost to you after utility rebates is $100,000 if the project saved $[125,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a question regarding the pursuit of an energy efficiency project with a cost of $100,000 after rebates and annual savings of $125,000. It also includes a table with data on regional and business premises characteristics, as well as a question about familiarity with networked/connected lighting systems.

2.5 4.6 4.0 1.6 4.0 4.0 4.1 2.4 3.3 3.5 3.0 This question was randomly posed to approximately one in ten respondents. 37 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 37 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED)...

AI summary The text includes a table from a 2019 electricity usage survey focusing on business respondents' familiarity with general service light bulbs. It also references a load forecast report and a study on energy efficiency and demand response potential in Nova Scotia.

2.5 4.6 4.0 1.6 4.0 4.0 4.1 2.4 3.3 3.5 3.0 This question was randomly posed to approximately one in ten respondents. 38 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 38 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED)...

AI summary The text discusses a survey question related to energy efficiency projects and their impact on energy consumption in businesses. It references a study on Nova Scotia's energy efficiency and demand response potential and includes a table from a 2019 electricity usage survey.

ject has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be installing or implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy e...

AI summary The text discusses energy efficiency projects and their cost-benefit analysis for businesses, asking whether a project costing $7,500 after rebates with annual savings of $500 would be pursued. It also includes a table with regional and business premises data, such as employment size, square footage, and heating types.

164 97 20 47 98 63 48 43 39 41 55 35 52 98 42 TABLE 22B: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be i...

AI summary The text presents a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but changes energy consumption. It asks whether a business would pursue such a project if the cost after rebates is $7,500 and the annual savings are $2,000.

r implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy efficiency project where the cost to your business after utility rebates is $7,500 if the project saved $[2,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question regarding the likelihood of pursuing an energy efficiency project with a cost of $7,500 after rebates and annual savings of $2,000. It also includes a table with data on responses by region, business premises type, number of employees, square footage, and heating type.

164 97 20 47 98 63 48 43 39 41 55 35 52 98 42 39 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 39 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 334 of 355 No...

AI summary The text discusses a 2019 electricity usage survey for businesses in Nova Scotia, focusing on energy efficiency projects that do not affect the quality of lighting, heating, and cooling but reduce energy consumption. An example is mentioned, though not fully specified.

ject has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be installing or implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy e...

AI summary The text discusses energy efficiency projects and their cost-benefit analysis, asking respondents if they would pursue a project costing $7,500 after rebates that saves $3,500 annually. It also includes a table with data on business premises, heating types, and responses to the energy efficiency question.

164 97 20 47 98 63 48 43 39 41 55 35 52 98 42 TABLE 22D: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be i...

AI summary The text presents a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but changes energy consumption. It asks whether a business would pursue such a project if the cost after rebates is $7,500 and the annual savings are $5,000.

r implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy efficiency project where the cost to your business after utility rebates is $7,500 if the project saved $[5,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text asks whether a business would pursue an energy efficiency project with a $7,500 cost after rebates, saving $5,000 annually. It also includes a table with data on business premises, employees, square footage, and heating types across different regions in Nova Scotia.

164 97 20 47 98 63 48 43 39 41 55 35 52 98 42 40 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 40 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 335 of 355 No...

AI summary The text discusses a 2019 electricity usage survey for businesses in Nova Scotia, focusing on energy efficiency projects that do not affect the quality of lighting, heating, and cooling but reduce energy consumption. An example of such a project is mentioned, though the specific item is redacted.

ject has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be installing or implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy e...

AI summary The text discusses the impact of energy efficiency projects on a business, asking whether a project with a $7,500 cost after rebates and $6,500 annual savings would be pursued. It also includes a table with data on business premises, heating types, and responses to the energy efficiency question.

164 97 20 47 98 63 48 43 39 41 55 35 52 98 42 TABLE 22F: Suppose an energy efficiency project has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be i...

AI summary The text presents a hypothetical energy efficiency project with no impact on the quality of lighting, heating, and cooling but changes energy consumption. It asks whether a business would pursue such a project if the cost after rebates is $7,500 and the annual savings are $8,000.

r implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy efficiency project where the cost to your business after utility rebates is $7,500 if the project saved $[8,000] per year? REGION BUSINESS PREMISES FT EMPLOYEES S...

AI summary The text presents a survey question about the likelihood of pursuing an energy efficiency project with a cost of $7,500 after rebates and annual savings of $8,000. It includes a table with regional and business data, showing varying percentages of 'Yes' and 'No' responses across different categories.

164 97 20 47 98 63 48 43 39 41 55 35 52 98 42 41 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 41 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 336 of 355 No...

AI summary This text references a table from a 2019 electricity usage survey for businesses, discussing an energy efficiency project that changes energy consumption without affecting the quality of lighting, heating, and cooling. It mentions an example item seen in Q21 of the survey.

ject has NO impact on the QUALITY of lighting, heating, and cooling in your business, but changes the amount of energy consumed. An example might be installing or implementing a(n) [ITEM SEEN IN Q21]. Would you generally pursue an energy e...

AI summary The text discusses energy efficiency projects, asking respondents if they would pursue a project costing $7,500 after rebates that saves $9,500 annually. It also includes a table with regional and business premises data, including heating types and employee counts.

13 0 0 6 8 27 20 23 Institutional 18 13 0 29 14 20 0 38 10 50 24 8 27 15 15 SAMPLE SIZE (#) 40 24 2 14 28 10 6 16 10 2 17 12 15 20 13 TABLE 30: What is the main source of energy used to heat your business’ Nova Scotia location where you wo...

AI summary The text presents a table with numerical data and a question asking about the main source of energy used to heat a business location in Nova Scotia. The table includes sample sizes and various categories, but the question highlights a focus on energy usage for heating.

e., a heat 8 8 10 7 10 6 16 4 0 11 12 4 4 8 15 pump system that has an indoor unit placed on a wall, that typically only heats a small area of the building) 6 8 0 4 8 3 3 8 0 0 12 4 7 6 11 49 Narrative Research . NAV002-1000 Date Filed: Au...

AI summary The text includes a table with numerical data and mentions a 2023 Load Forecast Report and a Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045, with a reference to an appendix and a redacted section.

Heating Indices (kWh / HH) Cooling Indices (kWh / HH) Year ResIndices.EFurn ResIndices.HPHeat ResIndices.SecHt ResIndices.FurnFan AContrib2Sales.HeatUse ResIndices.CAC ResIndices.HPCool ResIndices.GHPCool ResIndices.RAC AContrib2Sales.Cool...

AI summary The text presents data on heating and cooling indices (kWh per heating/cooling degree) across multiple years, showing trends in energy use for various heating and cooling technologies, including electric furnaces, heat pumps, and air conditioners.

Customer count and housing New housing usage NSPI and other Programs Before future DSM Year SAE model Historical Increment Cumlative New Cumulative Forecasted New New Structural Forecast RTR Electric End-Use Solar PV Total Total SAE + Regr...

AI summary The document presents data on customer count, housing usage, and energy consumption from 2013 to 2015, including metrics such as SAE model, historical customer counts, and electric end-use. It also includes information on programs and adjustments related to demand-side management.

333 (290) 29.3 5,366.2 2031 10,208.5 488,654.0 950.8 13,871.8 2,492.9 29,574.5 532,100.3 16000 4860 1.037016 379.2 5,390.6 (14.0) 433 (348) 70.9 5,461.5 2032 10,297.5 488,654.0 845.1 14,716.9 2,313.3 31,887.8 535,258.8 16000 4860 1.040964...

AI summary The document presents data on residential load forecasts, including customer numbers, EVs, solar installations, and demand-side management (DSM) impacts from 2023 to 2033. It highlights changes in these metrics over the decade, with notable increases in customer numbers and solar installations, and decreases in residential sales due to DSM efforts.

(485) (14) 5,657 (297) 5,360 (698) (402) Change to 4.7% 7.8% 13.6% -9.2% -0.3% 16.5% -5.6% 11.0% Residential Average Use - Regression (includes coefficients) Xheat Xcool Xother EESavings Binaries ARMA Covid Total Average Use 2023 4,353 343...

AI summary The text presents statistical data and regression analysis related to residential energy use in Nova Scotia, including changes in average use, heat and cooling inputs, and coefficients affecting energy consumption from 2023 to 2033.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 is outlined in Appendix B, Forecast Model Details in the Load Forecast report. The inputs 2 to XHeat, XCool, and X...

AI summary The 2023 Load Forecast Report (NSUARB M11108) outlines the methodology and data inputs used by NSPI in their responses to Synapse Energy Economics information requests. The report includes attachments detailing model components, heat pump growth, and assumptions for PV, EV, and DSM forecasts.

of 9 Year 22-Sep Covid ARMA XHeatNew XCoolNew XOtherNew Feb 18 New May 20 New Jun 20 New Oct 22 22-Sep Covid ARMA new Total (kWh)

AI summary The text presents a table with dates, energy-related terms, and values in kilowatt-hours, indicating data collection or reporting related to energy usage, possibly during the pandemic.

Year Month ResEndUse.ResOther NResEndUse.SmlGenOther NResEndUse.GenOther Sales.SmlInd Sales.MedInd Sales.Unm mVars.OthrUse mVars.Days mVars.Other_AvgMW 2027 5 210,673.6 15,949.0 145,782.3 22,382.9 38,498.7 6,516.9 439,803.3 31.0 591.1 2027...

AI summary The document presents a table of energy usage and sales data across multiple months and years, including residential and non-residential end-use energy consumption, sales by industry size, and various operational metrics. This data could be relevant for regulatory analysis and decision-making.

† Monthly HDD † Monthly CDD † Economics REDACTED (CONFIDENTIAL INFORMATION REMOVED) M11108 2023 Load Forecast Synapse IR-43 Attachment 2 has been filed electronically. REDACTED (CONFIDENTIAL INFORMATION REMOVED) REDACTED 2023 Load Forecast...

AI summary The document outlines the 2023 load forecast report, including demand-side management (DSM) projections, solar PV impact, electric vehicle (EV) forecasts, and various scenarios for energy demand. It also references responses from NSPI to Synapse Energy Economics' information requests.

2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information Requests NON-CONFIDENTIAL 1 Request IR-44: 2 3 Nova Scotia Power Electrification Support Overview by E3 4 5 (a) Please provide the full report...

AI summary NSPI provided responses to Synapse Energy Economics' information requests regarding the 2023 Load Forecast Report. The report, titled 'Nova Scotia Power Electrification Support Load Forecast Inputs – Overview,' was included as Appendix E in the 2022 Load Forecast Report. E3 contributed data on EV load shape and space heating.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-44 Attachment 1 Page 2 of 8 About E3 Engineering, Economics, 90+ full-time consultants 30 years of deep expertise Mathematics, Public Policy… San Francisco Ne...

AI summary The document highlights the importance of electrification in achieving Net-Zero goals in Nova Scotia, with Synapse Energy Economics providing support for integrated resource planning and electrification strategy reports, including work with Nova Scotia Power.

2023 Load Forecast Report Synapse IR-44 Attachment 1 Page 3 of 8 Electrification is key to achieving Net-Zero in Nova Scotia  In decarbonization Decarbonization Pillars in Nova Scotia modeling in Nova Scotia, consistent with the Demand Si...

AI summary The document discusses the importance of electrification in Nova Scotia's decarbonization strategy, emphasizing the need for parallel efforts in power sector GHG reductions and energy efficiency. It highlights the role of electrification in achieving Net-Zero goals and references a report by E3 Nova Scotia Power.

REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-44 Attachment 1 Page 7 of 8 LDV Charging Profiles  Charging profiles represent population-level charging scaled down to one vehicle  In unmanaged charging,...

AI summary The document discusses LDV charging profiles, explaining the difference between unmanaged and managed charging. Unmanaged charging occurs immediately upon arrival, while managed charging shifts timing to reduce costs and flatten peak loads. E3's input assumes 70% of managed charging is coordinated by an aggregator. The second section introduces heating equipment stock rollover, though details are redacted.

1 Request IR-45: 2 3 General Forecast Report Improvements – The Board Decision of October 31, 2022 notes that 4 NS Power agreed to the following changes in the 2023 forecast report (p 4): 5 6 In its Reply, NS Power addressed the concerns r...

AI summary NS Power has agreed to improve its 2023 forecast report by incorporating multi-hour temperature and windspeed analysis, multi-station weather data, and electrification impacts. It will also refine DR estimates, evaluate heat pump impacts, and update EV adoption rates, among other changes.

Please refer to Section 10 at page 78. Date Filed: June 20, 2023 NSPI (Synapse) IR-45 Page 2 of 4 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report (NSUARB M11108) NSPI Responses to Synapse Energy Economics Information...

AI summary The document outlines recommendations and updates related to the 2023 Load Forecast Report, including refining electrification impact analysis, incorporating commercial and industrial electrification impacts post-2027, evaluating heat pump impacts, and updating EV adoption rates. Some items are deferred for future study.

rs causing increases are growth in new customers and electric vehicles (EV). Offsetting these increases are rooftop solar and DSM. We will discuss several of these items in more detail in this report. Table 1. Net system requirement compon...

AI summary The text discusses factors increasing system requirements (new customers, EVs) and offsetting factors (solar, DSM). Table 1 details net system requirements for 2023 and 2033, including residential, commercial, industrial, and losses, sourced from NSPI's forecast report.

incorporates these trends into the forecasts. This change represents an acknowledgement of climate reality and is a definite step forward. This data should be analyzed and updated on a regular basis. NSPI previously investigated the use of...

AI summary The document discusses incorporating climate trends into load forecasts, noting a 11% residential load increase (2023-2033) with DSM programs, driven by new customers and EV adoption. A regression-based SAE model includes factors like heating, cooling, and DSM savings. Additional weather data had minimal impact on forecasts.

as a result of COVID, and several binary terms to account for variances in consumption associated with specific months (i.e., time-fixed effects). 8 8 Load Forecast Report, Appendix B, pp. 1-8. Synapse Energy Economics, Inc. Evidence Regar...

AI summary The text details Synapse Energy Economics' analysis of Nova Scotia Power’s 2023 load forecast, breaking down variables like XHeat, XCool, and XOther. It explains factors influencing residential energy use, including heating/cooling degree days, appliance efficiency, and income, with projected changes of +7.4%, +60.1%, and -1.3% respectively.

ion projection in this year’s load forecast. 14 In the near term, NSPI 11 Response to Board IR-3(c). 12 Load Forecast Report, p. 33. 13 Response to Synapse IR-7(b). 14 Response to Board IR-5. Synapse Energy Economics, Inc. Evidence Regardi...

AI summary NSPI's 2023 load forecast assumes 21,000 annual heat pump installations, with 68% for non-electric heating customers. This leads to increased XHeat (26.8%) and XCool (30.9%) loads, driven by heat pump adoption. Baseboard heat decreases by 447 GWh, while total heat pump load increases by 666 GWh. The forecast reverses the 2022 SAE projection of XHeat decline, showing a 7.4% increase from 2023–2033.

Regarding Nova Scotia Power’s 2023 Load Forecast 11 evaluated more closely in future years using AMI data. NSPI indicated that “work is ongoing to further reduce the differences in the models.” 22 Replacing fossil heating increases the ele...

AI summary The 2023 load forecast highlights that heat pump adoption increases electrical loads more than savings from retiring resistance heating, due to high assumed resistance heating intensity. The analysis recommends NSPI investigate heat pump impacts, validate assumptions, and monitor adoption trends using AMI data.

ipment, especially in light of the sensitivities that NSPI included testing this issue, and NSPI should also seek to validate any other assumptions about customer usage of secondary heating equipment. Water heaters For water heaters, the f...

AI summary NSPI's load forecast highlights a significant increase in electric water heater adoption (from 71% to 87% by 2033), driving energy and peak load growth. The report notes a 5% increase in XOther due to water heating usage and references completed demand response pilots with E1. NSPI emphasizes validating assumptions about secondary heating equipment usage and using pilot data for future forecasts.

levels. We ask NSPI to explore the potential for greater industrial savings. We ask NSPI to explore the impacts of real time rates. We ask NSPI to explore the impacts of increases in industrial RTR. 2.5. Commercial and Industrial Electrifi...

AI summary The document requests NSPI to explore industrial savings, real-time rates, and electrification impacts. It highlights forecasts for commercial/industrial electrification growth, municipal sector load trends, and modest DSM savings. Recommendations emphasize further investigation into post-2026 electrification prospects and DSM effectiveness.

120 152 -37 193 112 -141 2,392 152 2,581 mitigation) Source: Figure 58 of the 2022 Load Forecast Report. Recommendations and Considerations We ask NSPI to explain why the future System Peak values do not equal the Firm Peak less the interr...

AI summary The text discusses future system peak values and the impact of EVs and C&I electrification on peak load growth. It requests NSPI to explain discrepancies in peak values and investigate time-of-use rates and other measures to mitigate load increases. A significant increase in capacity requirements is noted, with a reference to the 2023 10-Year System Outlook.

a more complete evaluation of the options to control this growth in the next forecast. While Synapse requested the same detail in last 59 “2023 10-Year System Outlook NS Power,” June 30, 2023. Synapse Energy Economics, Inc. Evidence Regard...

AI summary The document discusses concerns about the accuracy of Nova Scotia Power's load forecast, particularly regarding the impact of electric vehicles and heat pumps on peak demand. It recommends further investigation into the performance of heat pumps, thermal storage, and induction cooking technologies, and urges NSPI to quantify electrification impacts in the commercial sector. The forecast is deemed plausible but requires refinement.

ive range than energy. However, the temperature at peak and the monthly HDD series are probably highly correlated. The economic and wind at peak components have very minimal impacts. • Figure D8 shows additional potential impacts. Especial...

AI summary The text discusses sensitivity analyses related to energy load forecasting, highlighting the impact of temperature, HDD, and policy options such as TOU/CPP. It also outlines NSPI's response to Synapse's recommendations and mentions the need for further clarifications and recommendations.

These load management strategies should be reflected in the next load forecast with greater detail, with all assumptions supported empirically to the maximum extent possible (page 14). 5. NSPI should include in its next load forecast more...

AI summary The document outlines several recommendations and questions regarding NSPI's load forecasting, including the need for more detailed and empirically supported assumptions, validation of proxy variables, and exploration of the impacts of EV load shifts, DSM programs, solar generation, RTR programs, and industrial electrification.

ctrification levels (page 21). 13. We ask NSPI to explore the potential for greater industrial savings (page 22). 14. We ask NSPI to explore the impacts of real time rates (page 23). 15. We ask NSPI to explore the impacts of increases in i...

AI summary The text outlines various requests for NSPI to explore and evaluate the impacts of industrial electrification, real-time rates, and technologies like heat pumps and thermal storage. It also recommends sensitivity analyses to mitigate peak load increases. The summary supports NSPI’s efforts to improve load forecast transparency and accuracy.

improve the transparency and accuracy of the load forecast. There is still more to do; but overall, NSPI’s Report is very well done and better explains the underlying factors driving the forecast. Synapse Energy Economics, Inc. Evidence Re...

AI summary Synapse Energy Economics, Inc. requests further clarifications and recommendations from NSPI regarding the 2023 load forecast, including the impact of heat pumps, electric vehicle batteries, and commercial electrification programs, as well as more detailed results from the SGNS project and clarification on DSM effects by sector.

ch of the commercial and industrial demand savings presented in Figure 36 are contained in the industrial forecast. We ask NSPI to clarify the DSM effects for each sector (p.15). • We’d like further explanation from NSPI about why the comm...

AI summary The text requests NSPI to clarify and improve its load forecasting, particularly regarding demand-side management effects, peak load growth from electric vehicles, time-of-use rates, and the impact of technologies like electric thermal storage, water heating, and induction cooking on energy and peak loads.

SUMMARY OF PROFESSIONAL EXPERIENCE 2023– Vice President, Grid Strategies, LLC. Provides research, technical assistance, Present and expert testimony on electric- and gas-utility planning, economics, and regulation. Reviews electric utility...

AI summary The text outlines professional experience in energy and regulatory sectors, including roles in grid strategies, regulatory policy, and advocacy. Key areas include utility planning, energy efficiency programs, renewable resource evaluation, and regulatory testimony. The individual has worked with organizations focused on clean energy, air quality, and transportation planning.

t Economy Summer Study on Energy Efficiency in Buildings, August 2010. “Monopsony Behavior in the Power Generation Market,” with Mike O’Boyle and Ron Lehr, Electricity Journal, August-September 2020. REPORTS “Policy Options: Responding to...

AI summary A list of studies and reports on energy efficiency, climate policy, and management practices, including academic papers and policy analyses from various institutions and government agencies, spanning topics like monopsony behavior in power markets and financial management in Florida school districts.

John D. Wilson  Grid Strategies, LLC Page 2 “Smoke in the Water: Air Pollution Hidden in the Water Vapor from Cooling Towers – Agencies Fail to Enforce Against Polluters,” Galveston Houston Association for Smog Prevention, February 2004....

AI summary The document lists publications by the Galveston Houston Association for Smog Prevention and the Southern Alliance for Clean Energy (SACE), focusing on air pollution, toxic emissions, renewable energy, and energy efficiency. Reports highlight underreporting of emissions, industry violations, and initiatives to advance renewable energy standards and energy efficiency programs in the Southeast.

John D. Wilson  Grid Strategies, LLC Page 3 “Analysis of Solar Capacity Equivalent Values for Duke Energy Carolinas and Duke Energy Progress Systems,” prepared for and filed by Southern Alliance for Clean Energy, Natural Resources Defense...

AI summary The text lists multiple reports authored or co-authored by the Southern Alliance for Clean Energy (SACE) on solar energy, energy efficiency, and decarbonization in the Southeastern U.S., including a 2021 review of Nova Scotia Power’s Integrated Resource Plan (IRP) for the Nova Scotia Utility and Review Board (NSUARB).

uncertainty of nuclear and economic impact modeling. 2013 Georgia PSC Docket No. 36498, direct testimony on behalf of Southern Alliance for Clean Energy. Adequacy of consideration of energy efficiency in Georgia Power’s 2013 integrated res...

AI summary Testimony from Southern Alliance for Clean Energy (SACE) in 2013-2014 regulatory proceedings focused on energy efficiency adequacy in integrated resource plans, renewable energy alternatives, and capacity credit calculations for solar power. Testimonies were provided in Georgia and South Carolina PSC dockets.

1 NS Power Response: 2 3 NS Power agrees with this recommendation. Heat pump data related to energy and peak effects is 4 aligned with the most recent studies available for Nova Scotia (Itron and E3). As more data is 5 gathered on the impa...

AI summary NS Power agrees to use heat pump data for load forecasting but notes data limitations. They mention developing class-level peak forecasts and addressing EV adoption with rate designs.

rvice in its Rebuttal Evidence. NS Power filed its Rebuttal Evidence on September 14 ,2023. Document: 308584 -2- 2023 Load Forecast NS Power uses two discrete elements for its forecast. The first is the Statistically Adjusted End- Use (SAE...

AI summary NS Power's 2023 Load Forecast uses SAE models and DSM adjustments, projecting near-term growth from customer and EV adoption, offset by DSM and solar. Long-term growth (0.7% annual NSR increase) is driven by electrification but mitigated by efficiency and demand response.

Document #:303618 Date Filed: May 25, 2023 Synapse (NSPI) Page 4 of 18 1 c. Please provide supporting evidence for the 40 percent saturation of customers providing 2 their heat via heat pumps in 2023 (p. 33). 3 d. Please provide the data s...

AI summary The document contains a series of requests for evidence, data sources, and calculations related to heat pump saturation forecasts, residential water heater efficiency, and model documentation (RESHAPE). It seeks clarification on assumptions, methodology, and impacts of electrification scenarios on peak load and energy consumption.

g. It appears that the Intensity in Figure 25 represents an average that is increasing because 26 the saturation is increasing. Please confirm if this is the driver. Please provide the intensity 27 per electric water heating household for...

AI summary The text contains two requests for clarification and data: (1) confirming if increasing saturation drives rising intensity in electric water heating household data (Figure 25) and requesting annual per-household intensity values, and (2) seeking source data and methodology for the 2023 EV sales forecast (Figure 26) and how federal targets influenced it.

e Company conducted any analysis on the long-term impact of the COVID- 23 19 pandemic, including analysis of whether the incremental sales attributable to the 24 increase in work-from-home load is apt to decline over time? Please explain....

AI summary The document contains regulatory requests addressing NSPI's load forecasts, including impacts of the pandemic on sales, assumptions about home size increases, and effects of critical peak pricing (CPP) and time-of-use (TOU) rates on EV charging behavior. Questions also seek clarity on building efficiency regulations and the status of CPP/TOU pilots.

e impacts of COVID on the 2021 and 2022 loads. 12 b. Please explain and quantify the ongoing effects of COVID in the commercial forecast. 13 c. Please explain why the current forecast (Figure 44) remains shows an increase through 14 2033 w...

AI summary The text outlines regulatory requests (IR-21 to IR-23) seeking explanations for forecast discrepancies in electricity demand, focusing on factors like COVID impacts, EV loads, space heating, DSM programs, and solar generation. Requests emphasize quantifying model changes, evaluating efficiency trends, and clarifying forecast assumptions for 2021–2033.

particularly the commercial lighting efficiency and intensity. 39 40 NS Power’s reply submission did not agree with a few of the intervenors’ requests. NS 41 Power does not consider the line loss determination model as a tool for load plan...

AI summary NS Power disagrees with intervenors' requests regarding line loss models, ELCC factors for LIIR, and commercial electrification analysis. It argues ELCC adjustments are unnecessary for LIIR but considers them for EV load shapes, and denies conducting cost-benefit analyses on commercial electrification programs.

Document: 303590 (P-194) Date Filed: 05/30/23 UARB Page 3 1 Request IR-5: 2 Page 33 of the Application lines 5 to 6 state: “The end-use model uses an estimated saturation of 3 40 percent of customers supplying their heat via heat pumps in...

AI summary The UARB requests explanations for increased heat pump saturation estimates (33% to 40%), effectiveness of heat pump water heaters, verification of EV adoption data, and bi-directional charger installations. Questions focus on forecast justification, program timelines, and EV data accuracy.

Document: 303590 (P-194) Date Filed: 05/30/23 UARB Page 5 1 Request IR-12: 2 Page 59 of the Application states in lines 5 to 7 “Building efficiency is expected to improve, 3 although based on calibration done in 2013, improvements are expe...

AI summary The text includes six requests (IR-12 to IR-16) questioning the Application's use of outdated building efficiency data, discrepancies in new customer load forecasts, EV energy allocation assumptions, economic downturn considerations, and the inclusion of a COVID variable in modeling. Requests seek clarification on methodology, data sources, and justification for projections.

on Requests to Nova Scotia Power Inc. (NS Power) In the Matter of Nova Scotia Power Incorporated’s 2023 Load Forecast Report – M11108 NON-CONFIDENTIAL 1 (d) Have any of the following heat pump performance characteristics changed in the 202...

AI summary The document contains requests to Nova Scotia Power Inc. (NSP) regarding changes in heat pump performance parameters in their 2023 Load Forecast compared to 2022, including COP curves, capacity curves, outdoor temperature cut-off points, and assumptions about low-temperature behavior. It also requests expanded data visualization (Figure 23) covering the full 2023-2033 forecast period.

electrification on energy and peak demand, and the effects of new technologies (specifically the results from the Smart Grid project, direct control of water heaters and Time Varying Pricing tariffs). The Consumer Advocate filed evidence p...

AI summary The Consumer Advocate submitted evidence by John Wilson of Resource Insight Inc., recommending NS Power adjust EV charging forecasts, update transformer sizing charts, revise load forecasts by removing inflated TVP benefits, clarify SAE model assumptions, and improve distribution planning for solar and electrification impacts.

he peak forecasting method; and • performing future sensitivity analysis based on actions to reduce projected peak increases using newly available technology. NS POWER REBUTTAL EVIDENCE In its rebuttal evidence, NS Power addressed the conc...

AI summary NS Power's rebuttal evidence addresses intervenors' concerns regarding peak forecasting methods, EV charging load modeling, and transformer sizing. The company confirmed reliance on current EV charging data, plans to use AMI meter data for distribution modeling, and acknowledged limitations in developing detailed end-use forecasts due to data gaps.

NS Power identified that real time pricing is available to industrial customers but only used by one. Other industrial rates are being developed for hydrogen production facilities, however, NS Power regards testing of rate design as outsid...

AI summary NS Power agrees to update load forecasts with data from IRP, Smart Grid NS, and TVP Pilot, while disagreeing on removing TVP savings due to peak demand alignment. They will assess EV, battery storage, and heat pump impacts but contest applying a fixed 0.6 kW EV load increase due to variable charging data.