Applications of Artificial Intelligence to Photovoltaic Systems: A Review
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...
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| Format: | Article |
| Language: | English |
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MDPI AG
2022-10-01
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| Series: | Applied Sciences |
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| Online Access: | https://www.mdpi.com/2076-3417/12/19/10056 |
| _version_ | 1797480488102789120 |
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| author | Héctor Felipe Mateo Romero Miguel Ángel González Rebollo Valentín Cardeñoso-Payo Victor Alonso Gómez Alberto Redondo Plaza Ranganai Tawanda Moyo Luis Hernández-Callejo |
| author_facet | Héctor Felipe Mateo Romero Miguel Ángel González Rebollo Valentín Cardeñoso-Payo Victor Alonso Gómez Alberto Redondo Plaza Ranganai Tawanda Moyo Luis Hernández-Callejo |
| author_sort | Héctor Felipe Mateo Romero |
| collection | DOAJ |
| description | 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. |
| first_indexed | 2024-03-09T22:00:45Z |
| format | Article |
| id | doaj.art-8d7cb7a9cab64fbfa9f4ea4ee4dbdb7a |
| institution | Directory Open Access Journal |
| issn | 2076-3417 |
| language | English |
| last_indexed | 2024-03-09T22:00:45Z |
| publishDate | 2022-10-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Applied Sciences |
| spelling | doaj.art-8d7cb7a9cab64fbfa9f4ea4ee4dbdb7a2023-11-23T19:50:20ZengMDPI AGApplied Sciences2076-34172022-10-0112191005610.3390/app121910056Applications of Artificial Intelligence to Photovoltaic Systems: A ReviewHéctor Felipe Mateo Romero0Miguel Ángel González Rebollo1Valentín Cardeñoso-Payo2Victor Alonso Gómez3Alberto Redondo Plaza4Ranganai Tawanda Moyo5Luis Hernández-Callejo6Departamento Fisica de la Materia Condensada, Universidad de Valladolid, 47011 Valladolid, SpainDepartamento Fisica de la Materia Condensada, Universidad de Valladolid, 47011 Valladolid, SpainDepartamento Informatica, Universidad de Valladolid, 47011 Valladolid, SpainDepartamento de Física, Universidad de Valladolid, 47002 Valladolid, SpainDepartamento Ingeniería Agrícola y Forestal, Universidad de Valladolid, 47002 Valladolid, SpainDepartment of Mechanical Engineering, Durban University of Technology, P.O. Box 1334, Durban 4000, South AfricaDepartamento Ingeniería Agrícola y Forestal, Universidad de Valladolid, 47002 Valladolid, SpainThis 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.https://www.mdpi.com/2076-3417/12/19/10056PVartificial intelligenceMPPTforecastingparameter estimationfaults detection |
| spellingShingle | Héctor Felipe Mateo Romero Miguel Ángel González Rebollo Valentín Cardeñoso-Payo Victor Alonso Gómez Alberto Redondo Plaza Ranganai Tawanda Moyo Luis Hernández-Callejo Applications of Artificial Intelligence to Photovoltaic Systems: A Review Applied Sciences PV artificial intelligence MPPT forecasting parameter estimation faults detection |
| title | Applications of Artificial Intelligence to Photovoltaic Systems: A Review |
| title_full | Applications of Artificial Intelligence to Photovoltaic Systems: A Review |
| title_fullStr | Applications of Artificial Intelligence to Photovoltaic Systems: A Review |
| title_full_unstemmed | Applications of Artificial Intelligence to Photovoltaic Systems: A Review |
| title_short | Applications of Artificial Intelligence to Photovoltaic Systems: A Review |
| title_sort | applications of artificial intelligence to photovoltaic systems a review |
| topic | PV artificial intelligence MPPT forecasting parameter estimation faults detection |
| url | https://www.mdpi.com/2076-3417/12/19/10056 |
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