A Review in Application of Particle Swarm Optimization in Photovoltaic System

Abstract

   Solar energy is abundantly available and environmentally beneficial, which has led to a rise in the acceptance of solar energy for the generation of power. The availability of solar power varies despite the fact that it appears to be a desirable source of energy due to a variety of reasons, including changes in temperature, shadow, and irradiance. Therefore, in recent years, research has focused on how to get the most power possible from solar photovoltaic (PV) systems utilizing the Maximum Power Point Tracking (MPPT) method. Without using excessive amounts of arithmetic, bioinspired algorithms shown good qualities for handling non-linear, non-differentiable, and stochastic optimization problems. This work evaluates a variety of applications using the Particle Swarm Optimization (PSO) method, a global metaheuristic optimization technique. The results of literature review highlighted the most important features of this algorithm and the most important fields of its application in the photovoltaic system especially the MPPT optimization of control system. Metaheuristics have established themselves as effective methods for handling challenging optimization issues throughout the past three decades.