Improving Low-Income Solar Access through Data, Funding, and Benefits Allocation
Sector: Solar • Location: Lakewood, Colorado, United States of America
Source: Department of Energy (DOE)
Solar photovoltaics (PV) can be used to reduce the energy burden of low-income customers, but to date, these customers have not adopted solar at the same rate as other income groups. This project will create a data platform capability, funding pathways, and benefit allocation frameworks to expand solar access for low- and medium-income (LMI) households. First, it will create a solar data access pl
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Participants
Sponsoring Agency | Obfuscated Data |
Company | Obfuscated Data |
Status
Original status | closed |
Taiyo status | Obfuscated Data |
Taiyo last update | 00-00-0000 |
Available timestamps | 00-00-0000 |
Available timestamp type | Obfuscated Data |
Contact
Contact name | Obfuscated Data |
Phone | 0000000000 |
ObfuscatedData@email.com | |
Address | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Description
Description | Solar photovoltaics (PV) can be used to reduce the energy burden of low-income customers, but to date, these customers have not adopted solar at the same rate as other income groups. This project will create a data platform capability, funding pathways, and benefit allocation frameworks to expand solar access for low- and medium-income (LMI) households. First, it will create a solar data access platform within EERE’s SLOPE tool to enable users to assess and compare solar access and LMI adoption options. Second, it will examine the feasibility and barriers to using weatherization and LIHEAP funds for rooftop and community solar in combination with cost-effective energy efficiency measures. Third, it will define and pilot benefit allocation frameworks from utility-scale PV. These three activities will enable local analysis of LMI solar adoption, and study and test mechanisms for delivering cost savings from utility-scale PV directly to LMI consumers. |
Original sub-sector | Obfuscated |
Original Currency | USD |
Original budget | 000000000000000 |
Procurement method | Obfuscated Data |
Budget | 000000000000000 |
Location
Region | Obfuscated |
Country | Obfuscated |
State | Obfuscated Data |
County | Obfuscated |
Location | Obfuscated Data, Obfuscated data, obfuscated data, Obfuscated data |
Source
Source reliability | High |
Data quality score | 100% |
Source | Obfuscated Data |
URL | obfuscated_data,obfuscateddata.com |
More Details
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Article Published Date | Obfuscated Data |
