Increasing the Accuracy of Hourly Multi-Output Solar Power Forecast with Physics-Informed Machine Learning

Machine Learning (ML)-based methods have been identified as capable of providing up to one day ahead Photovoltaic (PV) power forecasts. In this research, we introduce a generic physical model of a PV system into ML predictors to forecast from one to three days ahead. The only requirement is a basic...

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Detalles Bibliográficos
Autores principales: Pombo, Daniel Vázquez, Bindner, Henrik W., Spataru, Sergiu Viorel, Sørensen, Poul Ejnar, Bacher, Peder
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Article
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839153/
https://www.ncbi.nlm.nih.gov/pubmed/35161500
http://dx.doi.org/10.3390/s22030749

Internet

https://www.ncbi.nlm.nih.gov/pmc/articles/PMC8839153/
https://www.ncbi.nlm.nih.gov/pubmed/35161500
http://dx.doi.org/10.3390/s22030749

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