Parameter identification of the photovoltaic cell model with a hybrid Jaya-NM algorithm

被引:27
|
作者
Luo, Xiong [1 ,2 ,3 ]
Cao, Longpeng [1 ,2 ,3 ]
Wang, Long [1 ,2 ,3 ]
Zhao, Zihan [4 ]
Huang, Chao [5 ]
机构
[1] USTB, Sch Comp & Commun Engn, Beijing 100083, Peoples R China
[2] Guangdong Prov Key Lab New & Renewable Energy Res, Guangzhou 510640, Guangdong, Peoples R China
[3] Beijing Key Lab Knowledge Engn Mat Sci, Beijing 100083, Peoples R China
[4] China Univ Min & Technol, Sch Geosci & Surveying Engn, Beijing, Peoples R China
[5] City Univ Hong Kong, Dept Syst Engn & Engn Management, 83 Tat Chee Ave, Kowloon, Hong Kong, Peoples R China
来源
OPTIK | 2018年 / 171卷
关键词
Photovoltaic cell; Parameter identification; Jaya algorithm; Computational intelligence; I-V CHARACTERISTICS; SOLAR-CELLS; OPTIMIZATION; EXTRACTION; DIODE;
D O I
10.1016/j.ijleo.2018.06.047
中图分类号
O43 [光学];
学科分类号
070207 ; 0803 ;
摘要
This paper proposes a hybrid computational intelligence algorithm for identifying parameters of the photovoltaic (PV) cell model. In the proposed algorithm, Jaya algorithm is applied to perform the global search while Nelder Mead (NM) algorithm is employed to conduct the local search. The integration of Jaya and NM algorithms provide the ability to find the global optimum solution in a multidimensional optimization problem. To validate the effectiveness of the proposed Jaya-NM algorithm, current and voltage data from a commercial PV cell are utilized and the single diode model parameter are identified. The results show that the proposed algorithm outperforms recently published identification methods.
引用
收藏
页码:200 / 203
页数:4
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