E-22024 DSM Programs Evaluation Reports
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Where: - › _ℎ = The control group's average daily consumption over the given post-program year - › _ℎ = The treatment group's average daily consumption over the given post-program year - › _ℎ = The control group's average daily consumption...
AI summary The document discusses adjustments made to the cumulative savings approach for calculating annual electrical savings, taking into account varying numbers of participating households with AMI data. Table 84 presents the 2024 electrical savings values established using this method.
Background After inconclusive results in 2023, a billing analysis was again conducted for Green Heat as part of the 2024 DSM evaluation to obtain measured electrical energy savings generated through the installation of mini-split heat pump...
AI summary A 2024 billing analysis for Green Heat evaluated energy savings from mini-split heat pumps (MSHPs) and wood/pellet stoves, updating prior results and using AMI data for improved accuracy. MSHPs are the primary measure, with stove installations analyzed for the first time via billing rather than modeling.
Methodology The billing analysis consisted of calculating the change in electrical energy consumption by comparing levels before and after participation in Green Heat for a group of recent participants (treatment group). To account for var...
AI summary The methodology uses a difference-in-differences approach to measure Green Heat program savings by comparing treatment and control groups, normalizing energy data for weather, and calculating unitary savings for MSHPs and wood/pellet stoves. This isolates program impacts from external factors like the pandemic.
AMI Data Preparation AMI data for treatment group and control group participants were obtained from two sources: - › Nova Scotia Power (NS Power) for the period between the moment AMI data became available (2020) and November 2023 - › Effi...
AI summary AMI data for treatment and control groups were sourced from NS Power (2020–2023) and EfficiencyOne (2024), aggregated monthly. A 5% exclusion rate applied to remove inconsistent data (nil consumption, extreme peaks, or abnormal patterns), ensuring sufficient control group representation for analysis.
Background After inconclusive results in 2023, a billing analysis was again conducted for HEA as part of the 2024 DSM evaluation to obtain measured electrical energy savings generated through the installation of energy efficiency upgrades....
AI summary The 2024 DSM evaluation shifted from using overestimation ratios (ORs) based on space heating data to adjustment ratios (ARs) derived from AMI data for whole-home consumption. This change addresses challenges posed by increased heat pump adoption and simplifies calculations by directly applying ARs to modelled savings estimates.
Methodology To assess the electrical energy savings obtained from HEA energy efficiency upgrades, the billing analysis consisted of calculating the change in electrical energy consumption before (pre) and after (post) participation in HEA...
AI summary The methodology assesses electrical energy savings from HEA upgrades by comparing treatment and control groups, normalizing AMI data against HOT2000 modelled savings, and calculating adjustment ratios (ARs) to isolate program-specific impacts from external factors like the pandemic.
Selection of the Treatment and Control Groups The initial treatment group included 1,803 HEA participants who were selected based on the following criteria: - › Be 100% electrically heated according to HOT2000 (meaning that the primary hea...
AI summary The treatment group of 1,803 HEA participants was selected based on heating type, assessment dates, and AMI data availability. The control group of 1,227 past HEA participants was chosen to match the treatment group, ensuring similar characteristics per UMP guidelines. AMI data was incomplete due to missing NS Power account numbers, affecting the number of participants analyzed.
AMI Data Preparation AMI data for treatment group and control group participants were obtained from two sources: - › NS Power for the period between the moment AMI data became available (2020) and November 2023 - › EfficiencyOne for the ye...
AI summary AMI data for treatment and control groups were sourced from NS Power (2020–2023) and EfficiencyOne (2024). Data was aggregated monthly, with the Evaluator excluding 5% of samples due to inconsistencies like nil consumption, extreme peaks, or abnormal variations to ensure analytical accuracy.
Metering Data Analysis To establish the available DR capacity generated from Mysa thermostats, the Evaluator analyzed the available participant whole-house consumption meter data and established a unitary available DR capacity value per pa...
AI summary The Evaluator used whole-house meter data to calculate DR capacity from Mysa thermostats, converting it to per-thermostat values and updating the 2024-2025 DSM MA. Other products like EVs and batteries were excluded due to insufficient data, while Sinopé thermostats were included based on similar control strategies. No DR capacity was claimed for EVs due to low participation.
Metering Data Analysis Results Using the methodology presented above, the Evaluator established the DR capacity made available at each event hour of the 2023-2024 heating season. As mentioned in the introduction, available DR capacity is m...
AI summary The analysis of metering data from the 2023-2024 heating season indicates that some DR events resulted in negative DR capacity due to incorrect preheating implementation. This occurred during the events instead of before, leading to higher load than expected. The methodology used is based on heating degree days to represent heating load accurately.
3.2.3 Interactive Effects In a home, interactive effects occur when the implementation of energy efficiency products has an impact on the energy consumption of other elements such as heating and cooling. For the Eco Shift Pilot pathway, al...
AI summary Interactive effects occur when energy efficiency measures impact other home systems like heating/cooling. The Eco Shift Pilot evaluates these effects using whole-house metering data (AMI) over device-level data, capturing interactions with uncontrolled systems (e.g., heat pumps) and offsetting thermostat load reductions.
5.1 BNI DR Description In 2023, E1 officially launched the BNI DR program component. Since the fall of 2020, E1 implemented several pilot initiatives focused on reducing demand during the Nova Scotia peak period. One of them was the DR Agg...
AI summary In 2023, E1 launched the BNI DR program, building on pilot initiatives since 2020. The DR Aggregator Pilot, led by Parsons Inc., allows E1 to hire aggregators who manage groups of BNI customers to reduce load during peak periods through remote control or direct participant action, such as adjusting heating, cooling, and lighting systems.
APPENDIX II Residential DR: Detailed Metering Data Analysis Methodology This appendix summarizes the methodology used by the Evaluator to establish the available DR capacity as part of the 2024 evaluation of Residential DR. For the Eco Shi...
AI summary The appendix outlines the methodology for evaluating residential demand response (DR) capacity using Mysa thermostats. The Evaluator used whole-house consumption data from advanced metering infrastructure (AMI) to compare expected and actual hourly loads during events, calculating a unitary available DR capacity per thermostat.
This appendix summarizes all the recommendations made by the Evaluator as part of the 2024 evaluation of BNI DR. Section Recommendations Executive Summary 2024 BNI DR Recommendation 1: Update the BNI DR Baseline Considerations document to...
AI summary This appendix outlines two key recommendations from the 2024 evaluation of the BNI DR program. The first recommendation focuses on updating the BNI DR Baseline Considerations document to address issues related to building operating hours, lookback windows, and event exclusions due to missing AMI data. The second recommendation suggests continuing to use project reviews to evaluate available DR capacities in future evaluations.
Summary [Table](#page-51-1) 176 presents a summary of the values used to calculate advanced rooftop unit (RTU) control savings. The detailed methodology follows.
AI summary Table 176 summarizes the values used to calculate advanced rooftop unit (RTU) control savings, with a detailed methodology provided afterward.