Parameter identification and sensitivity analysis of solar cell models with cat swarm optimization algorithm

被引：241
作者：
Guo, Lei [1 ,2 ]
Meng, Zhuo [1 ]
Sun, Yize [1 ]
Wang, Libiao [1 ]
机构：
[1] Donghua Univ, Coll Mech Engn, 2999 North Rd, Shanghai 201620, Peoples R China
[2] Fujian Agr & Forestry Univ, Coll Mech & Elect Engn, 15 Shangxiadian Rd, Fuzhou 350002, Peoples R China
来源：
ENERGY CONVERSION AND MANAGEMENT | 2016年 / 108卷
关键词：
Parameter identification; Solar cell models; Cat swarm optimization; Heuristic algorithm; Optimization; Sensitivity analysis; IMPROVED DIFFERENTIAL EVOLUTION; DIODE MODEL; PERFORMANCE; DEGRADATION; EXTRACTION; BEHAVIOR; SYSTEMS; ENERGY;
D O I：
10.1016/j.enconman.2015.11.041
中图分类号：
O414.1 [热力学];
学科分类号：
摘要：
Solar cell model is used in various studies of photovoltaic system. Different methods have been developed to determine model parameters. In this paper, an optimization technique based on cat swarm optimization (CSO) algorithm is proposed to estimate the unknown parameters of single and double diode models. To investigate the effectiveness of proposed approach, comparative studies with other techniques are presented. The evaluation for the quality of identified parameters is also given. Results demonstrate the high performance of developed approach, high accuracy of estimated parameters, and calculated I-V curve is in good agreement with experimental I-V data. In addition, the sensitivity of performance to control parameter of CSO is also investigated. Results show the proposed CSO algorithm can be an effective tool to solve the optimization problem of parameter identification of solar cell models. (C) 2015 Elsevier Ltd. All rights reserved.
引用
收藏
页码：520 / 528
页数：9
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