Artificial Intelligent Based Controller to Improve the Power Quality of Grid Connected Solar PV System

Abstract

Grid-connected photovoltaic (PV) power systems are becoming increasingly common in many nations. Achieving optimal power and high power quality in a grid-connected photovoltaic system is regarded as one of the major problems. To this end, a novel cascade multilevel inverter (MLI) is suggested for PV system grid integration, and artificial intelligence (AI) controller-based maximum power point tracking (MPPT) algorithm has been studied for PV system. The suggested cascade MLI is best suitable for PV systems as it has fewer power electronic switches in its architecture and can run at asynchronous voltage sources. By raising the output voltage level, this suggested inverter can lower the total harmonic distortion (THD) at the output side, improving the system's power quality. An AI-based voltage source controller has been used to regulate the proposed inverter's micro-grid integration. The system has been constructed and simulated in a MATLAB environment under a variety of loads and weather scenarios.