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    Por favor, use este identificador para citar o enlazar este ítem:https://uvadoc.uva.es/handle/10324/65995

    Título
    Applications of Artificial Intelligence to photovoltaic systems: a review
    Autor
    Mateo Romero, Héctor FelipeAutoridad UVA Orcid
    González Rebollo, Miguel ÁngelAutoridad UVA
    Cardeñoso Payo, ValentínAutoridad UVA Orcid
    Alonso Gómez, VíctorAutoridad UVA Orcid
    Redondo Plaza, Alberto GregorioAutoridad UVA Orcid
    Moyo, Ranganai Tawanda
    Hernández Callejo, LuisAutoridad UVA Orcid
    Año del Documento
    2022
    Documento Fuente
    Applied Sciences, 2022, vol .12, 10056
    Résumé
    This article analyzes the relationship between artificial intelligence (AI) and photovoltaic (PV) systems. Solar energy is one of the most important renewable energies, and the investment of businesses and governments is increasing every year. AI is used to solve the most important problems found in PV systems, such as the tracking of the Max Power Point of the PV modules, the forecasting of the energy produced by the PV system, the estimation of the parameters of the equivalent model of PV modules or the detection of faults found in PV modules or cells. AI techniques perform better than classical approaches, even though they have some limitations such as the amount of data and the high computation times needed for performing the training. Research is still being conducted in order to solve these problems and find techniques with better performance. This article analyzes the most relevant scientific works that use artificial intelligence to deal with the key PV problems by searching terms related with artificial intelligence and photovoltaic systems in the most important academic research databases. The number of publications shows that this field is of great interest to researchers. The findings also show that these kinds of algorithms really have helped to solve these issues or to improve the previous solutions in terms of efficiency or accuracy.
    Revisión por pares
    SI
    DOI
    10.3390/app121910056
    Idioma
    eng
    URI
    https://uvadoc.uva.es/handle/10324/65995
    Tipo de versión
    info:eu-repo/semantics/publishedVersion
    Derechos
    openAccess
    Aparece en las colecciones
    • DEP32 - Artículos de revista [284]
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    Nombre:
    applsci-12-10056-v3 (3).pdf
    Tamaño:
    7.660Mo
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