Improved SPSO-based Parameter Identification of Solar PV cells I-V Model

被引:0
|
作者
Sun Yixin [1 ]
Peng Yunjian [1 ]
Deng Feiqi [1 ]
机构
[1] South China Univ Technol, Sch Automat Sci & Technol, Guangzhou 510640, Guangdong, Peoples R China
基金
中国国家自然科学基金;
关键词
solar PV cells; mathematics model; parameter identification; Simplified Particle Swarm Optimization(SPSO); TEMPERATURE;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The paper considers the parameter identification of PV cells' I-V model. Based on the nonlinear equation of PV cells I-V experimental model, which cannot be used directly to analyze the parameters' value with the output current and voltage, we present a quasi-linear differential equation of dV/dI to turn the parameters to differential coefficient of the dynamic relationship of I-V. Then an improved Simplified Particle Swarm Optimization (SPSO) algorithm is proposed to identify the unknown differential coefficient in the equation, by which the optimal parameters of PV cells can be calculated. Lastly, the results of PV cells' experiment verify the validity of the improved SPSO algorithm and shows that the identified parameters, which are affected by irradiance, can be used to get a more accurate PV cells I-V model to predict PV power generation.
引用
收藏
页码:1738 / 1742
页数:5
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