AUTHORS: Haithem Chaieb, Anis Sakly

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ABSTRACT: Optimization can be defined as an effort of generating solutions to a problem under constrained circumstances utilizing the existing resources with the finest way. Literature proposes many variants of optimization methods inspired from nature such as evolutionary algorithms and swarms intelligence algorithms. Swarm intelligence is considered as a powerful method suitable for optimization problems. For instance, Bat algorithm has been inspired by bats behavior during their flight and hunting. Particle Swarm Optimization algorithm has been inspired by social behavior of fish schooling or bird flocking In this work, an attempt is made to validate experimentally and analyses the performance of Bat and PSO algorithm. A standard test has been carried to evaluate the ability to track the global maximum point of the photovoltaic panel under a step change in irradiance Furthermore under partial shading conditions. The main equations that govern the behavior of each algorithm are also explained. Furthermore, this paper outlines how far BA algorithm outperforms PSO with respect to the tracking capability, transient behavior, and convergence criteria as results of his excellent features. It is envisaged that the BA algorithm can be suitably used as an MPPT technique, particularly for large PV array under various weather condition.

KEYWORDS: MPPT; swarm intelligence; Bat algorithm; partially shading condition; PSO.

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