Cargando…
Machine learning reduces soft costs for residential solar photovoltaics
Further deployment of rooftop solar photovoltaics (PV) hinges on the reduction of soft (non-hardware) costs—now larger and more resistant to reductions than hardware costs. The largest portion of these soft costs is the expenses solar companies incur to acquire new customers. In this study, we demon...
Autores principales: | Dong, Changgui, Nemet, Gregory, Gao, Xue, Barbose, Galen, Sigrin, Benjamin, O’Shaughnessy, Eric |
---|---|
Formato: | Online Artículo Texto |
Lenguaje: | English |
Publicado: |
Nature Publishing Group UK
2023
|
Materias: | |
Acceso en línea: | https://www.ncbi.nlm.nih.gov/pmc/articles/PMC10156750/ https://www.ncbi.nlm.nih.gov/pubmed/37137971 http://dx.doi.org/10.1038/s41598-023-33014-4 |
Ejemplares similares
-
Income-targeted marketing as a supply-side barrier to low-income solar adoption
por: O'Shaughnessy, Eric, et al.
Publicado: (2021) -
Private vs. public value of U.S. residential battery storage operated for solar self-consumption
por: Forrester, Sydney, et al.
Publicado: (2022) -
Levelized cost-based learning analysis of utility-scale wind and solar in the United States
por: Bolinger, Mark, et al.
Publicado: (2022) -
Spatial Characteristics of the Diffusion of Residential Solar Photovoltaics in Urban Areas: A Case of Seoul, South Korea
por: Kim, Moon-Hyun, et al.
Publicado: (2021) -
Lifecycle cost and carbon implications of residential solar-plus-storage in California
por: Zheng, Jiajia, et al.
Publicado: (2021)