Abstract
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.
Original language | English |
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Pages (from-to) | 1922-1925 |
Number of pages | 4 |
Journal | Measurement Science and Technology |
Volume | 12 |
Issue number | 11 |
DOIs | |
Publication status | Published - Nov 2001 |
Keywords
- Genetic algorithms
- Parameter extraction
- Photovoltaics
- Solar cell
ASJC Scopus subject areas
- Instrumentation
- Engineering (miscellaneous)
- Applied Mathematics