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Parameter identification of solar cells and fuel cell using improved social spider algorithm

Hadi Kashefi (Department of Industrial Engineering, Yazd University, Yazd, Iran)
Ahmad Sadegheih (Department of Industrial Engineering, Yazd University, Yazd, Iran)
Ali Mostafaeipour (Department of Industrial Engineering, Yazd University, Yazd, Iran)
Mohammad Mohammadpour Omran (Iran University of Science and Technology, Tehran, Iran)

COMPEL - The international journal for computation and mathematics in electrical and electronic engineering

ISSN: 0332-1649

Article publication date: 30 June 2020

Issue publication date: 7 July 2021

277

Abstract

Purpose

To design, control and evaluate photovoltaic (PV) systems, an accurate model is required. Accuracy of PV models depends on model parameters. This study aims to use a new algorithm called improved social spider algorithm (ISSA) to detect model parameters.

Design/methodology/approach

To improve performance of social spider algorithm (SSA), an elimination period is added. In addition, at the beginning of each period, a certain number of the worst solutions are replaced by new solutions in the search space. This allows the particles to find new paths to get the best solution.

Findings

In this paper, ISSA is used to estimate parameters of single-diode and double-diode models. In addition, effect of irradiation and temperature on I–V curves of PV modules is studied. For this purpose, two different modules called multi-crystalline (KC200GT) module and polycrystalline (SW255) are used. It should be noted that to challenge the performance of the proposed algorithm, it has been used to identify the parameters of a type of widely used module of fuel cell called proton exchange membrane fuel cell. Finally, comparing and analyzing of ISSA results with other similar methods shows the superiority of the presented method.

Originality/value

Changes in the spider’s movement process in the SSA toward the desired response have improved the algorithm’s performance. Higher accuracy and convergence rate, skipping local minimums, global search ability and search in a limited space can be mentioned as some advantages of this modified method compared to classic SSA.

Keywords

Citation

Kashefi, H., Sadegheih, A., Mostafaeipour, A. and Mohammadpour Omran, M. (2021), "Parameter identification of solar cells and fuel cell using improved social spider algorithm", COMPEL - The international journal for computation and mathematics in electrical and electronic engineering, Vol. 40 No. 2, pp. 142-172. https://doi.org/10.1108/COMPEL-12-2019-0495

Publisher

:

Emerald Publishing Limited

Copyright © 2020, Emerald Publishing Limited

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