Use an artificial intelligence method (Machine Learning) for analysis of the performance of photovoltaic systems

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Hichem Hafdaoui
El Amin Kouadri Boudjelthia
Salim Bouchakour
Nasreddine Belhaouas


The performance of a photovoltaic system depends on several parameters such as temperature, clouds, and the season, which makes the study of PV performance from monitoring databases very complex given the size of the information and the complexity of the phenomena involved. This article applies an artificial intelligence (AI) method based on machine learning (ML). For more efficient analysis, the Support Vector Machine (SVM) is used to simplify and optimize the processing of these data for the study of the performance of PV systems. More precisely, we group a multi-class data variable according to the needs of the analysis using SVMs. In this article, we present all the stages of data processing based on the application of artificial intelligence (AI). We present as an example the results obtained in the study of the performance of a 150W monocrystalline photovoltaic (PV) module after one year of monitoring.

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How to Cite
H. . Hafdaoui, E. A. . Kouadri Boudjelthia, S. . Bouchakour, and N. . Belhaouas, “Use an artificial intelligence method (Machine Learning) for analysis of the performance of photovoltaic systems”, J. Ren. Energies, vol. 25, no. 2, pp. 199 -, Dec. 2022.


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