Abstract

In the last few years, several concepts have been developed in the field of Power Quality (PQ) improvements. Features of PQ plays a significant part in power system based applications. Nowadays, technologies in Renewable Energy Source (RES) have got more opportunities for promoting Photo-Voltaic (PV) for generating electric power. It may affect the reliability and stability of entire power system, also produces the switching frequency with irregular manner and variation within the certain region. Also, Incremental-Conductance (IC) method miserably fails to recognize Global Maximum Power Point (MPP) and gets trapped in one of the Local MPP. Since the conventional MPPT (Maximum Power Point Tracking) might not separate the maximum power of the P-V characteristic curve, a novel tracking system needs to be established. In this research work, Kinetic Gas Molecular Optimization (KGMO) is implemented with IC for improving the PQ by providing the adequate switching pulse to inverter for enhancing the system performance. The proposed method reduced the Total Harmonic Distortion (THD) up to 4.67 %, and the efficiency is observed by evaluation over the traditional Radial Basis Function Neural Network (RBFNN) and IC-MPPT techniques. The proposed method is implemented in the MATLAB/Simulink software to analyze the performance of PQ issues.

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