Artificial bee swarm optimization algorithm for parameters identification of solar cell models

被引:348
作者
Askarzadeh, Alireza [1 ]
Rezazadeh, Alireza [1 ]
机构
[1] Shahid Beheshti Univ, GC, Fac Elect & Comp Engn, Tehran, Iran
关键词
Mathematical modeling; Parameter identification; Artificial bee swarm optimization; PHOTOVOLTAIC MODULES; EXTRACTION;
D O I
10.1016/j.apenergy.2012.09.052
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
An accurate mathematical model is an extremely helpful tool for simulation, evaluation, control, and optimization of solar cell systems. Due to the non-linearity of the solar cell models and the inability of traditional optimization methods to accurately identify the unknown parameters, recently, metaheuristic algorithms have attracted significant attention. Artificial bee swarm optimization (ABSO) is a recently invented algorithm inspired by the intelligent behaviors of honey bees such as collection and processing of nectar. In this paper, we propose an ABSO-based parameter identification technique based on the single and double diode models for a 57 mm diameter commercial (R.T.C. France) silicon solar cell. The results obtained by ABSO algorithm are quite promising and outperform those found by the other studied methods. (c) 2012 Elsevier Ltd. All rights reserved.
引用
收藏
页码:943 / 949
页数:7
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