Applications of Artificial Intelligence to Photovoltaic Systems: A Review
Source abstract
Abstract
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.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Photovoltaic System Optimization Techniques · Solar Radiation and Photovoltaics · Energy Load and Power Forecasting
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Departamento Fisica de la Materia Condensada, Universidad de Valladolid, 47011 Valladolid, Spain
Departamento Informatica, Universidad de Valladolid, 47011 Valladolid, Spain
Departamento de Física, Universidad de Valladolid, 47002 Valladolid, Spain
Departamento Ingeniería Agrícola y Forestal, Universidad de Valladolid, 47002 Valladolid, Spain
Department of Mechanical Engineering, Durban University of Technology, P.O. Box 1334, Durban 4000, South Africa
Funding
Universidad the Valladolid · Cátedra CeI Caja Rural de Soria
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