E3S Web Conf.
Volume 336, 2022The International Conference on Energy and Green Computing (ICEGC’2021)
|Number of page(s)||5|
|Published online||17 January 2022|
Machine learning for predictive maintenance of photovoltaic panels: cleaning process application
1 Mohammed V University in Rabat, Higher School of Technology in Sale, MEAT, Salé, Morocco
2 Mohammed V University in Rabat, Higher School of Technology in Sale, LASTIMI, Salé, Morocco
It is well known that the presence of dust on the surface of PV modules has a significant impact on their efficiency. Then, the consequent reduction in energy production has a non-negligible effect on the incomes. Although there is a growing need for accurate data showing where the solar arrays need maintenance in this rush for renewable energy. The purpose of this article is to introduce the research on existing photovoltaic panel maintenance solutions and introduce a new machine learning algorithm application to minimize the cleaning process of photovoltaic modules.
© The Authors, published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License 4.0, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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