Solar cell parameter extraction using genetic algorithms

Research output: Contribution to journalArticle

176 Citations (Scopus)

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 languageEnglish
Pages (from-to)1922-1925
Number of pages4
JournalMeasurement Science and Technology
Volume12
Issue number11
DOIs
Publication statusPublished - Nov 2001

Fingerprint

Parameter extraction
Solar Cells
genetic algorithms
Solar cells
solar cells
Genetic algorithms
Genetic Algorithm
Newton-Raphson method
Diodes
Deviation
deviation
Newton methods
optimization
Quasi-Newton Method
Search Problems
calculus
Electric potential
Diode
Search Algorithm
Optimization Algorithm

Keywords

  • Genetic algorithms
  • Parameter extraction
  • Photovoltaics
  • Solar cell

ASJC Scopus subject areas

  • Polymers and Plastics
  • Ceramics and Composites
  • Materials Science (miscellaneous)

Cite this

Solar cell parameter extraction using genetic algorithms. / Jervase, J. A.; Bourdoucen, H.; Al-Lawati, A.

In: Measurement Science and Technology, Vol. 12, No. 11, 11.2001, p. 1922-1925.

Research output: Contribution to journalArticle

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