Enhanced Photovoltaic System Using Hybrid Fuzzy-PSO MPPT Control for Four-Switch Z-Source Inverter

Abstract

This paper presents a new research regarding a novel hybrid Maximum Power Point Tracking (MPPT) technique that combines Fuzzy Logic Control (FLC) and Particle Swarm Optimization (PSO) for grid-connected photovoltaic (PV) systems using a Z-source four-switch three-phase inverter (FSTPI). The proposed system resolves some critical issues that appear in conventional PV systems. Those issues includes slow convergence, steady-state oscillations, poor partial shading performance, and high component count. The hybrid Fuzzy-PSO algorithm integrates the capacity of PSO algorithm to perform a global search, with the capacity of FLC to give a fast dynamic response, enabling robust maximum power extraction under varying environmental conditions. The system  when integrated with a Z-source FSTPI topology, achieves single-stage power conversion with voltage boost capability while reducing switching devices by 42.9% compared to conventional topologies. The simulations show enhanced performance metrics that include: 98.5% MPPT efficiency, 1.78% output current THD without additional filters, ±0.4% steady-state power oscillation, 45ms tracking time under irradiance transitions, a power factor greater than 0.995 and a 94.8% efficiency. Comparing these results to conventional Perturb & Observe method show 3.3% higher efficiency and comparing them to standard voltage source inverters show 63% THD reduction. The proposed architecture represents a significant advancement in PV system technology, particularly for residential applications requiring cost-effective, high-performance solar energy conversion under challenging partial shading conditions.