Parameter identification of the photovoltaic cell model with a hybrid Jaya-NM algorithm

Research output: Journal Publications and Reviews (RGC: 21, 22, 62)21_Publication in refereed journal

12 Scopus Citations
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Author(s)

Detail(s)

Original languageEnglish
Pages (from-to)200-203
Journal / PublicationOptik
Volume171
Online published9 Jun 2018
Publication statusPublished - Oct 2018

Abstract

This paper proposes a hybrid computational intelligence algorithm for identifying parameters of the photovoltaic (PV) cell model. In the proposed algorithm, Jaya algorithm is applied to perform the global search while Nelder–Mead (NM) algorithm is employed to conduct the local search. The integration of Jaya and NM algorithms provide the ability to find the global optimum solution in a multidimensional optimization problem. To validate the effectiveness of the proposed Jaya-NM algorithm, current and voltage data from a commercial PV cell are utilized and the single diode model parameter are identified. The results show that the proposed algorithm outperforms recently published identification methods.

Research Area(s)

  • Computational intelligence, Jaya algorithm, Parameter identification, Photovoltaic cell