Parameters extraction of photovoltaic module for long-term prediction using Artifical Bee Colony optimization
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hdl:2117/77771
Tipus de documentText en actes de congrés
Data publicació2015
EditorInstitute of Electrical and Electronics Engineers (IEEE)
Condicions d'accésAccés restringit per política de l'editorial
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Reconeixement-NoComercial-SenseObraDerivada 3.0 Espanya
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.
CitacióGaroudja, E., Kara, K., Chouder, A., Silvestre, S. Parameters extraction of photovoltaic module for long-term prediction using Artifical Bee Colony optimization. A: International Conference on Control, Engineering & Information Technology. "3rd International Conference on Control, Engineering & Information Technology (CEIT 2015): 25-27 May 2015: Tlemcen, Algeria". Tlecmen: Institute of Electrical and Electronics Engineers (IEEE), 2015, p. 1-6.
Versió de l'editorhttp://ieeexplore.ieee.org/stamp/stamp.jsp?tp=&arnumber=7232993
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PID3585187.pdf | 316,7Kb | Accés restringit |