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Titre: | Identification of PV model parameters using experimental and nameplate data |
Auteur(s): | Atchi, Aymene Khaled, Rayane Kheldoun, Aissa (Supervisor) |
Mots-clés: | Photovoltaic systems PV model : Analysis |
Date de publication: | 2021 |
Résumé: | In the last few decades, the use of photovoltaic systems has enormously increased. Hence
tools to predict energy production are highly needed. This work presents two reliable methods
for identifying the optimal parameters of a PV generating unit. In the first method, the PV
system is simulated using single and double diode models. It is based on an opposition-based
differential evolution algorithm where the objective function is derived from the experimental
current-voltage data. In the second method, the parameters of the single diode model are
identified using only datasheets provided by manufacturers. It is based on a new meta-
heuristics method called Black Widow. These methods are found to be useful for designers
since they are simple, fast, and accurate. The analysis is performed on different PV
cells/modules and under different temperatures and irradiances. The final results are
compared with different existing methods. |
Description: | 58 p. |
URI/URL: | http://dlibrary.univ-boumerdes.dz:8080/handle/123456789/11813 |
Collection(s) : | Power
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