Solar cell parameter extraction using genetic algorithms

J. A. Jervase*, H. Bourdoucen, A. Al-Lawati

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

298 Citations (Scopus)


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 languageEnglish
Pages (from-to)1922-1925
Number of pages4
JournalMeasurement Science and Technology
Issue number11
Publication statusPublished - Nov 2001


  • Genetic algorithms
  • Parameter extraction
  • Photovoltaics
  • Solar cell

ASJC Scopus subject areas

  • Instrumentation
  • Engineering (miscellaneous)
  • Applied Mathematics


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