Original scientific paper
https://doi.org/10.30765/er.1714
A comprehensive study of diagnosis faults techniques occurring in photovoltaic generators
Selma Tchoketch Kebir
; Laboratoire de Dispositifs de Communications et de Conversion Photovoltaique, Electronic Departement, Ecole Nationale Polytechnique, Algiers 16000, Algeria / Unité de Développement des Equipements Solaires, UDES/Centre de Développement des Energies Renouvelables, CDER, Bou-Ismail, 42415, W. Tipaza, Algeria
Nawal Cheggaga
; Laboratory of Electrical Systems and Remote control, Electronic Departement, University Saad Dahleb of Blida, Po Box 270 Route de Soumaa, Blida 09000, Algeria
Mohamed Salah Ait Cheikh
; Laboratoire de Dispositifs de Communications et de Conversion Photovoltaique, Electronic Departement, Ecole Nationale Polytechnique, Algiers 16000, Algeria
Mourad Haddadi
; Laboratoire de Dispositifs de Communications et de Conversion Photovoltaique, Electronic Departement, Ecole Nationale Polytechnique, Algiers 16000, Algeria
Hachemi Rahmani
; Laboratoire de Dispositifs de Communications et de Conversion Photovoltaique, Electronic Departement, Ecole Nationale Polytechnique, Algiers 16000, Algeria / Unité de Développement des Equipements Solaires, UDES/Centre de Développement des Energies Renouvelables, CDER, Bou-Ismail, 42415, W. Tipaza, Algeria
Abstract
Recently, many focuses have been done in the field of renewable energies, especially in solar photovoltaic energy. Photovoltaic generator, considered as the heart of any photovoltaic installation, exhibits sometimes malfunctions which involve degradations on the overall photovoltaic plant. Therefore, diagnosis techniques are required to ensure failures detection. They avoid dangerous risks, prevent damages, allow protection, and extend their healthy life. For these purposes, many recent studies have given focuses on this field. This paper summarizes a large number of such interesting works. It presents a survey of photovoltaic generator degradations kinds, several types of faults, and their major diagnosis techniques. Comparative studies and some critical analyses are given. Other trending diagnosis solutions are also discussed. A proposed neural networks-based technique is developed to clarify the main process of diagnosis techniques, using artificial intelligence. This method shows good results for modelling and diagnosing the healthy and faulty (shaded) photovoltaic array.
Keywords
photovoltaic generator; degradations; faults detection; inspection; diagnosis; supervision
Hrčak ID:
258433
URI
Publication date:
20.12.2021.
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