期刊
MEASUREMENT SCIENCE AND TECHNOLOGY
卷 12, 期 11, 页码 1922-1925出版社
IOP PUBLISHING LTD
DOI: 10.1088/0957-0233/12/11/322
关键词
genetic algorithms; parameter extraction; photovoltaics; solar cell
In this paper, a technique based on genetic algorithms is proposed for improving the accuracy of solar cell parameters extracted using conventional techniques. The approach is based on formulating the parameter extraction as a search and optimization problem. Current-voltage data used were generated by simulating a two-diode solar cell model of specified parameters. The genetic algorithm search range that simulates the error in the extracted parameters was varied from +/-5 to +/- 100% of the specified parameter values. Results obtained show that for a simulated error of +/-5% in the solar cell model values, the deviation of the extracted parameters varied from 0.1 to 1% of the specified values. Even with a simulated error of as high as +/- 100%, the resulting deviation only varied from 2 to 36%. The performance of this technique is also shown to surpass the quasi-Newton method, a calculus-based search and optimization algorithm.
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