| Autor: |
Xiaojing Xu, Charles Sims, Chien-fei Chen, J. Scott Holladay, Gerald Jones, Tim Roberson |
| Jazyk: |
angličtina |
| Rok vydání: |
2024 |
| Předmět: |
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| Zdroj: |
Energies, Vol 17, Iss 18, p 4538 (2024) |
| Druh dokumentu: |
article |
| ISSN: |
1996-1073 |
| DOI: |
10.3390/en17184538 |
| Popis: |
Rooftop solar adoption has increased considerably in recent years thanks to a combination of lower panel costs and generous incentive programs. This paper estimates the increase in residential rooftop solar adoption associated with three types of solar incentive programs and isolates the effect of these programs in both high and low-income census tracts. We utilize a dataset of census tract-level rooftop solar adoption compiled using a machine learning-based image classification tool that identifies solar photovoltaic panels from satellite images. This allows us to study areas of the country that have lower solar adoption rates and incomes than areas previously studied. We find evidence that programs designed specifically to encourage adoption in low-income areas are associated with a smaller gap between low- and high-income solar adoption. However, property-tax benefits and net metering, which are more prevalent across the U.S., are associated with an increase in the gap between low- and high-income solar adoption. |
| Databáze: |
Directory of Open Access Journals |
| Externí odkaz: |
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