Parameters extraction of solar cells - A comparative examination of three methods

J. Appelbaum*, A. Peled

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

117 Scopus citations

Abstract

This paper deals with the extraction of the parameters of the single-diode solar cell model from experimental I-V characteristics of Si and Multi-junction solar cells. The extraction is carried out by three different optimization methods in an attempt to judge which method surpasses the others in terms of data-to-model fitting. The first and the second methods are a variation of the Newton-Raphson method and the Levenberg-Marquardt algorithm, respectively. Both methods are based on the gradient descent approach. The third method is a global-search method based on a Genetic-Algorithm. The extraction of the parameters was done in two stages. On the first stage, empirical I-V characteristics of solar cells that contained measurement errors were used, whereas on the second stage the parameters were re-extracted using a smooth synthetic I-V data. In the absence of true measured parameter values of the cells, it was left to rate the performance of the three optimization methods by the extraction error alone. Although no definitive conclusions could be drawn from the results of the noisy data, results of the smooth data are far more pronounced in terms of the extraction error, and tend to favor the Newton-Raphson method.

Original languageEnglish
Pages (from-to)164-173
Number of pages10
JournalSolar Energy Materials and Solar Cells
Volume122
DOIs
StatePublished - Mar 2014

Keywords

  • Genetic Algorithm
  • Lambert-W function
  • Levenberg-Marquardt
  • Newton-Raphson
  • Parameters extraction
  • Si and MJ solar cells

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