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Low-Income Energy Affordability Data LEAD Tool 2018 Update
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low and moderate-income (LMI) communities t...
Ma, O. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy
Jul 01, 2020
57 Resources
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57 Resources
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Evaluation of Early Performance Results for Massachusetts Homes in the National Grid Pilot Deep Energy Retrofit Program
In 2009, National Grid started a DER pilot program that offered technical support and financial incentives to qualified Massachusetts homeowners who planned and successfully completed a retrofit that incorporated the performance requirements and goals of the National Grid DER meas...
Neuhauser, K. and Gates, C. Building Science Corporation
Apr 27, 2016
29 Resources
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29 Resources
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Energy Appliance Data 2009-2010
Datasets for residential appliances energy usage/efficiency. The Federal Trade Commission (FTC) collects manufacturer data about the energy use and efficiency of appliances. All of the data was submitted by manufacturers under the FTC's Appliance Labeling Rule (see "FTC Appliance ...
Trade Commission, F. National Renewable Energy Laboratory
Jul 29, 2014
19 Resources
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19 Resources
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Low-Income Energy Affordability Data LEAD Tool 2022 Update
The Low-Income Energy Affordability Data (LEAD) Tool was created by the Better Building's Clean Energy for Low Income Communities Accelerator (CELICA) to help state and local partners understand housing and energy characteristics for the low and moderate-income (LMI) communities t...
Ma, O. and Vimont, A. U.S. Department of Energy, Office of Energy Efficiency and Renewable Energy
Aug 01, 2024
63 Resources
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63 Resources
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Understanding the Evolution of Customer Motivations and Adoption Barriers in Residential Solar Markets: Survey Data
This research focused on accelerating solar photovoltaic (PV) diffusion by collecting new market data and developing predictive modeling frameworks to test and refine understandings of household level motivations for adopting solar.
Three different household-level surveys were...
Sigrin, . et al National Renewable Energy Laboratory
May 22, 2017
13 Resources
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13 Resources
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