N-7NSPI (Synapse) RIR-1 to RIR-46 - Redacted
30 passages
and lightning. Aggregated power of controlled equipment, which is calculated by the BMS based on equipment nameplates and trends and not measured directly, is available for each customer site in ESP. Table 6 summarizes all events that have...
AI summary The document discusses the calculation of aggregated power reduction for controlled equipment using Building Management System (BMS) data, and the methodology used to estimate average event savings for demand response events. It notes that the approach uses ESP-sourced power trend data instead of utility metering due to the small load reduction being lost in the noise.
1 Request IR-16: 2 3 Demand Side Management (Section 4.6, pp 54-56). 4 5 (a) Please provide the source data for the DSM values used in this forecast. 6 (b) Please provide the DSM values used in the latest IRP. 7 (c) Please provide the DSM...
AI summary The request seeks source data for DSM values used in the forecast, including the latest IRP and E1 potential study. The response indicates that DSM values for 2023-2025 are based on EOne’s Settlement Plan and values beyond 2025 are based on the EOne Potential Study. A table is referenced with energy and demand values for various years.
http://en.wikipedia.org/wiki/System_dynamics for a high-level overview. ©2019 Navigant Consulting, Ltd. Page 1 . REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 10 of 355 Nova Scotia En...
AI summary Navigant conducted a bottom-up analysis to estimate demand response (DR) potential and costs in Nova Scotia, using data from EfficiencyOne and secondary sources. The analysis involved five steps and provided input data for Navigant’s Demand-Response Simulator (DRSim™) model to calculate total DR potential across the province.
hment 1 Page 23 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 E. 2.2.2 Scenario Analysis For the low and high cases, Navigant adjusted assumed participation levels, incentive amounts, marketing spen...
AI summary The document discusses scenario analysis for demand response (DR) and energy efficiency programs in Nova Scotia from 2021 to 2045. It outlines how different participation levels and assumptions affect DR achievable potential, program costs, and cost-effectiveness under low, base, and high scenarios.
odelling Scenarios’ Assumptions WebEx Presentation held May 28, 2019 • 2019 Potential Study Technical Conference held July 16, 2019 • Three formal stakeholder review and comment periods: o On March 22, 2019, EfficiencyOne shared draft Pote...
AI summary The document outlines stakeholder engagement activities related to a study on energy efficiency potential in Nova Scotia, including review periods and feedback opportunities with the DSMAG. It also highlights caveats and limitations of the study, particularly regarding program design and measure characterization.
brium market share, behavioural measures, investment and incentive strategy, re-participation, and model calibration. Section 7 – discusses the Reference Forecast Approach and scenario configuration. Section 8 – presents the Energy Efficie...
AI summary The document outlines various sections of a study on energy efficiency and demand response potential in Nova Scotia from 2021 to 2045. Sections cover market share, forecasting approaches, energy efficiency measures, demand response methodologies, and results of cost-effectiveness analyses.
t Report Synapse IR-30 Attachment 1 Page 28 of 355 Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045 2. GLOBAL DATA Navigant aggregated multiple data sources to simulate many elements of the market conditions...
AI summary The document outlines the data sources used by Navigant to model energy efficiency and demand response potential in Nova Scotia from 2021 to 2045. Key data includes energy forecasts, residential and industrial building stock, and historical consumption data from various sources like Nova Scotia Power and EfficiencyOne.
site visits (see Appendix B) • ENS program evaluation reports • NS Power end use intensity-based forecasts (Load Forecast Models) • Previous Nova Scotia DSM potential studies Where Nova Scotia-specific information was not available, Naviga...
AI summary Navigant used various data sources, including NS Power's load forecast models and previous DSM studies, to estimate energy consumption. They segmented customer sectors based on consumption, demand, and end-use allocations, working with EfficiencyOne and the DSM Advisory Group. The DSMSim™ model was used to represent efficiency measures at the segment level, incorporating fuel choices and equipment efficiency.
ted winter peak demand by customer class and segment over the potential analysis period. The baseline projections aimed to define and forecast customer data for the study period, similar to the market 16 These business types were sourced f...
AI summary The document discusses the methodology for projecting customer counts and winter peak demand by customer class and building type, using 2018 as the base year. It outlines the selection of customer classes and building types for analysis and the use of data from the DnB dataset provided by EfficiencyOne.
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.
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.
Customers without dispatchable batteries and 4 Behavioural DR not enrolled in DLC or CPP Source: Navigant 10.4.1.2 Unit Impact Assumptions The unit impacts specify the amount of load that could be reduced during a DR event once customers a...
AI summary The text discusses unit impact assumptions for demand response (DR) programs, specifying how load reductions are estimated based on customer participation. Residential DLC impacts for space heating are defined in kW per device, while other impacts are defined as a percentage of enrolled load. The model inputs data from Appendix C are used for these assumptions, with examples given for BNI Curtailment and different control types.
e Total Resource Cost (TRC) test. Navigant also calculated the cost-effectiveness results based on the Program Administrator Cost (PAC) test. 11.3.1 Benefit-Cost Assessment by Demand Response Option Figure 11-4 shows the TRC benefits, cost...
AI summary The document presents a benefit-cost assessment of various demand response (DR) options using the Total Resource Cost (TRC) and Program Administrator Cost (PAC) tests. It shows that most DR options are cost-effective, except for Behavioral DR, BTM Battery Control, and EV Charging control. The TRC and PAC tests yield different benefit-cost ratios due to differences in how incentives are treated.
ential Study for 2021-2045 11.5 Demand Response Investment Levels Figure 11-11 summarizes the annual program investment for cost-effective DR options in the base case. Results indicate the following: • The program investment for DLC increa...
AI summary The document outlines the investment trends for various demand response (DR) programs from 2021 to 2045. Key points include steady DLC investment increasing until 2024, followed by a drop and subsequent spikes due to program lifecycle costs. CPP investment is high initially but stabilizes after 2028. BNI curtailment costs are tied to aggregator payments, while behavioral program investments remain low and consistent after 2026.
lso varied by case as these were tied to the different demand reduction scenario impacts from the energy efficiency potential study. 11.6.1 Comparison of Cost Results Across Demand Response Scenarios Figure 11-12 shows the cost-effectivene...
AI summary The text compares the cost-effectiveness of various demand response (DR) options across three scenarios. Under the high scenario, DLC and BNI Curtailment are not cost-effective due to fixed costs and the opt-out nature of CPP, which captures more customers. Only CPP and BDR are cost-effective in the high scenario, while the base and low scenarios show similar cost-effective DR options.
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.
P.O. Box 64 Toronto, ON M5X 1B1 Canada 416.777.2440 navigant.com Reference No.: 207668 May 09, 2019 ©2019 Navigant Consulting, Ltd.. . Date Filed: August 14, 2019 Page 1 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast...
AI summary This document outlines the methodology for two studies on energy efficiency and demand response potential in Nova Scotia for 2021-2045. The studies aim to quantify electricity and demand savings and associated costs, by sector and end use, to inform Nova Scotia Power’s next Integrated Resource Plan.
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.
chnical, economic and achievable potential for 2021-2045 (25 years) 3 . Date Filed: August 14, 2019 Page 5 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 133 of 355 Nova Scotia E...
AI summary This section outlines the process for developing baseline energy use, end use saturation, and sales forecasts as part of a study on energy efficiency and demand response potential in Nova Scotia from 2021 to 2045. It emphasizes the importance of market characterization as a foundational step in the study.
Load Forecast 1. Energy forecast Nova Scotia Power forecasts 2. Demand forecast Customer Accounts Forecast Nova Scotia Power forecasts Customer Demographics Nova Scotia customer surveys and other primary and secondary sources Measure-level...
AI summary Nova Scotia Power provides forecasts for energy and demand, customer accounts, and demographics, using surveys, program evaluations, and statistical data. Incentive level assumptions are based on past program experience and future plans. Navigant will develop energy sales forecasts for electric consumption and peak demand, disaggregated by sector and end use.
regated electricity consumption (at each level) is reasonable and well aligned with expectations. Figure 4. Illustrative Breakdown of Energy Sales Forecast Based on Navigant’s experience conducting energy efficiency potential studies, we c...
AI summary The text discusses the importance of aggregating electricity consumption data by customer segments and end uses in energy efficiency potential studies. It highlights that proper segmentation and alignment with data availability are crucial to avoid unnecessary complexity and ensure valuable insights for program managers and DSM planners.
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.
or 2021-2045 Appendix A Figure 10. Navigant’s Technical Potential Model Data Flow 2.1.3.2 Develop Economic Potential
AI summary This section outlines the development of economic potential as part of a technical potential model, referencing data flow and analysis processes relevant to energy efficiency and demand-side management planning.
echnologies are replaced each year, which affects how quickly technologies can 22 . Date Filed: August 14, 2019 Page 24 of 40 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 152 of 355...
AI summary The document discusses a model used to predict the replacement of technologies over time, incorporating the diffusion of technology familiarity. It references the DSMSimTM model and highlights the challenges of calibrating predictive models without future data.
The purpose of this task is to develop a set of assumptions that will ultimately drive the activity of modelling DR potential. We refer to this process as developing the DR program design parameters. The two key parameters that are needed...
AI summary This task involves developing assumptions to model demand response (DR) potential, focusing on participation rates, unit impact, and other parameters. It also includes evaluating market characteristics, previous studies, and industry best practices to formulate a representative DR portfolio.
program development process. We review information presented in well- established secondary sources, such as the FERC National DR Program Survey database 17, and publicly filed program evaluation reports and market assessment studies from...
AI summary The document discusses the program development process, referencing secondary sources like the FERC National DR Program Survey and publicly filed program evaluations to assess participation and impact assumptions in demand response (DR) programs. It also mentions the use of peak demand projections and unit impacts at the end use level to develop potential estimates.
of kW reduction per participant or in savings by DR program and by market terms of percentage of enrolled load) segment for Nova Scotia. • Customer attrition, event participation • Annual program costs and levelized assumptions costs by pr...
AI summary The text discusses the analysis of demand response (DR) potential in Nova Scotia, emphasizing the need for achievable potential estimates. It highlights the importance of considering factors like customer participation, cost components, and incentive levels to determine realistic DR outcomes.
646 244 392 517 252 424 466 210 680 163 160 147 141 This table excludes responses of 'Don't know'. 7 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 7 of 54 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast R...
AI summary The text includes a table with numerical data and references to a 2023 Load Forecast Report and a Nova Scotia Energy Efficiency and Demand Response Potential Study for 2021-2045. It also mentions an attachment from Synapse and a study by Navigant, indicating a regulatory analysis context.
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. 45 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 45 of 54 REDACT...
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' from Appendix B-3. It also includes a redacted section and a reference to a Synapse IR-30 attachment.
14 25 18 8 12 18 2 18 125 2 17 70 10 13 10 42 Narrative Research . NAV002-1000 Date Filed: August 14, 2019 Page 42 of 51 REDACTED (CONFIDENTIAL INFORMATION REMOVED) 2023 Load Forecast Report Synapse IR-30 Attachment 1 Page 337 of 355 Nova...
AI summary The text includes a redacted section from a 2023 Load Forecast Report and an appendix from a 2021-2045 Nova Scotia Energy Efficiency and Demand Response Potential Study. It references a 2019 Electricity Usage Survey for businesses, focusing on square footage of company properties.