ملخص
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.
اللغة الأصلية | English |
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الصفحات (من إلى) | 1922-1925 |
عدد الصفحات | 4 |
دورية | Measurement Science and Technology |
مستوى الصوت | 12 |
رقم الإصدار | 11 |
المعرِّفات الرقمية للأشياء | |
حالة النشر | Published - نوفمبر 2001 |
ASJC Scopus subject areas
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