A modified particle swarm optimization algorithm to enhance MPPT in the PV array

Abstract

Due to the growing demand for electrical power, the researchers are trying to fulfill this demand by considering different ways of renewable energy resource as existing energy resources failed to do so. The solar energy from the sun is freely available, and by using photovoltaic (PV) cell power can be generated. However, it depends on rays fall on the PV cell, climatic condition. Thus, to enhance the efficiency of the photovoltaic (PV) systems, maximum power point tracking (MPPT) of the solar arrays is needed.The output of solar arrays mainly depends on solar irradiance and temperature. The mismatch phenomenon takes place due to partial shade, and it causes to the power output, which brings the incorrect operation of traditional MPP tracker. In this shaded condition, PV array exhibits multiple extreme points. In general, under this scenario, the MPPT approaches fail to judge the MPP, and it leads to low efficiency. The conventional approaches of PSO based algorithms can able to track the MPP under shading condition. However, the optimization process leads to issues in tracking speed. Thus, there a need for an efficient MPPT system which can track MPPT effectively in shaded condition? Hence, the proposed manuscript presents a modified Particle Swarm Optimization (PSO) algorithm is introduced to enhance the tracking speed as well as performance. The outcomes of the proposed system are compared with the traditional PSO system and are found that the tracking speed of MPP, accuracy, and efficiency is improved.

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Irradiance Sudden Change Grid Connected Fuzzy Self Tuning PID Controller Maximum Power Point Tracking Technique for Photovoltaic Power System

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