A 5-Level Asymmetrical Multilevel Inverter Using Catch Fish Optimization Algorithm Based On Islanded Mode Single-Phase Community Microgrid

The concept of inverters aims to improve efficiency and power quality in high-power applications. Traditional two-level inverters produce a square waveform, requiring extensive filtering to achieve a sine wave. In contrast, multilevel inverters use a staircase approach for better waveform quality. To minimize errors and harmonic distortion in a 5-level MLI, this paper proposes Catch Fish Optimization Algorithm (CFOA) optimized controller. The primary objective is to enhance maximum power extraction from a photovoltaic (PV) array, integrating a battery energy storage system for efficiency. Battery paired with PV stores excess energy and supply when required. A quantum neural network-based MPPT, optimized using Red Panda Optimization (RPO) technique, tracks maximum power. A 3DOF-FOTD-FOTID controller efficiently manages the 5-level MLI. The system achieves low total harmonic distortion (THD) of 1.26% for voltage and 1.12% for current, improving efficiency and reducing distortion. This demonstrates significant improvements in the MPPT performance, making the proposed system highly effective.