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Veuillez utiliser cette adresse pour citer ce document : http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/11331

Titre: Choosing the adapted artificial intelligence method (ANN and ANFIS) based MPPT controller for thin layer PV array
Auteur(s): Bouchetob, Elaid
Nadji, Bouchra
Mots-clés: ANFIS
ANN
Artificial intelligence
DC-DC converter
MPPT
PV system
Date de publication: 2023
Editeur: Springer
Collection/Numéro: Lecture Notes in Networks and Systems/ Vol.591 LNNS (2023);pp. 322-331
Résumé: Because of the many advantages that artificial intelligence technologies provide in comparison to more conventional methods, a rising number of solar power plants are beginning to use them in their monitoring of the MPP. When there is a sudden change in solar temperature and irradiance, it is possible that the MPP will not be tracked as accurately. As a consequence of this, these methods could make up for the deficiencies of those that are more well-established (P&O, IC, etc.). Aside from that, there is a wide range of methods to AI, each of which has a particular advantage. By making some minor adjustments to the architecture, an artificial neural network (ANN) and an adaptive neuro-fuzzy inference system (ANFIS) were used to monitor the MPP of Thin Layer panel technology at the Oued Nechou installation in Ghardaia. Each connection channel now has six panels rather than the previous maximum of 12 panels, and the junction box has 210 channels rather than the prior maximum of 105 channels. In the last step, a DC-DC boost converter is used to increase the power output voltages produced by the module
URI/URL: DOI 10.1007/978-3-031-21216-1_35
https://link.springer.com/chapter/10.1007/978-3-031-21216-1_35
http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/11331
ISBN: 978-303121215-4
ISSN: 23673370
Collection(s) :Communications Internationales

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