Enhance Power Quality with Cascade Multilevel Inverter-Based Grid Integration of Photovoltaic Systems using Machine Learning Algorithms

Abstract

The integration of renewable energy sources into the power grid has gained significant attention due to the increasing demand for clean and sustainable energy. Among various renewable sources, photovoltaic (PV) systems have emerged as a promising solution for electricity generation. However, integrating PV systems with the grid presents several challenges, including power quality issues, harmonic distortion, and voltage instability. To address these challenges, this paper proposes an advanced control strategy for grid integration of PV systems using a Cascade Multilevel Inverter (CMLI) and Convolutional Neural Network (CNN)-based control. The primary objective is to enhance power quality, minimize harmonics, and improve overall system efficiency.