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Título:	Parameters extraction of photovoltaic module for long-term prediction using Artifical Bee Colony optimization
Autor/a:	Garoudja, Elyes; Kara, Kamel; Chouder, Aissa; Silvestre Bergés, Santiago
Otros autores:	Universitat Politècnica de Catalunya. Departament d'Enginyeria Electrònica; Universitat Politècnica de Catalunya. MNT - Grup de Recerca en Micro i Nanotecnologies
Abstract:	In this paper, a heuristic optimization approach based on Artificial Bee Colony (ABC) algorithm is applied to the extraction of the five electrical parameters of a photovoltaic (PV) module. The proposed approach has several interesting features such as no prior knowledge of the physical system and its convergence is not dependent on the initial conditions. The extracted parameters have been tested against several static IV characteristics of different PV modules from different manufacturers. In order to assess the effectiveness of the extracted parameters, a dynamic model based maximum power point has been used and compared to real measurements data of a grid connected system located in the Centre de Developpement des Energies Renouvelables (CDER) in Algiers. In addition, comparison of the proposed ABC algorithm with some wellknown heuristic algorithms such as, Particle Swarm Optimization (PSO) and Differential Evolution (DE), has given better results in terms of local minimum avoidance and accuracy.
Abstract:	Peer Reviewed
Materia(s):	-Àrees temàtiques de la UPC::Energies::Energia solar fotovoltaica -Àrees temàtiques de la UPC::Energies::Energia solar fotovoltaica::Cèl·lules solars -Solar cells -Photovoltaic power generation -Photovoltaic module -Artificial bee colony -Parameters extraction -Maximum power point -ABC -PSO -DE -Cèl·lules solars -Energia solar fotovoltaica
Derechos:	http://creativecommons.org/licenses/by-nc-nd/3.0/es/
Tipo de documento:	Artículo - Versión publicada Objeto de conferencia
Editor:	Institute of Electrical and Electronics Engineers (IEEE)
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