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A Set of Smart Swarm-Based Optimization Algorithms Applied for Determining Solar Photovoltaic Cell’s Parameters

  • Selma Tchoketch KebirEmail author
  • Mohamed Salah Ait Cheikh
  • Mourad Haddadi
Conference paper
Part of the Lecture Notes in Networks and Systems book series (LNNS, volume 62)

Abstract

This paper presents the study and the use of two smart swarm-based optimization methods for determining the electrical unknown parameters of solar photovoltaic cells. These two methods are the well-known Particle Swarm Optimization (PSO) and a recent smart swarm-based method named, Whale Optimization Algorithm (WOA). This last one is inspired by the hunting behaviour of humpback whales in nature. The best parameters determination values are essential for the accuracy of the solar photovoltaic characteristics. The non-linear parameters determination problem is formulated mathematically as a multi-parameters or as a multi-objective optimization problem. The two swarm-based optimization methods are first described, explaining every step, and then validated using solar photovoltaic manufacturers’ data sheets information. The performance of each approach is evaluated in terms of chosen criteria. The results show that the WOA method outperforms the PSO.

Keywords

Optimization Swarm-based intelligence Nature-inspired PSO algorithm WOA algorithm Photovoltaic cells 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Selma Tchoketch Kebir
    • 1
    Email author
  • Mohamed Salah Ait Cheikh
    • 1
  • Mourad Haddadi
    • 1
  1. 1.Electronic DepartmentEcole Nationale Polytechnique, ENPAlgiersAlgeria

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