Optimizing PV Inverter Performance with Particle Swarm Optimization and Sugeno Fuzzy Logic for Reduced THD in Mismatched Conditions

This work presents an optimized solution for enhancing power performance and reducing Total Harmonic Distortion (THD) in grid-connected photovoltaic (PV) inverters under mismatched environmental conditions. By integrating Particle Swarm Optimization (PSO) with Sugeno fuzzy logic in the Maximum Power Point Tracking (MPPT) process, we offer a novel approach that surpasses traditional methods in efficiency and power quality. This research focuses on addressing the critical challenge of THD in PV inverters, a key factor affecting grid stability and power quality. Our method dynamically adjusts MPPT settings in response to environmental variations, ensuring optimal power extraction and minimal THD. The innovative combination of PSO and Sugeno fuzzy logic provides a robust and efficient control strategy, demonstrating significant improvements in THD levels—current THD reduced from 2.12 to 0.43% and voltage THD from 0.09 to 0.05%. These enhancements not only improve the electrical efficiency and reliability of PV systems but also contribute to the stability of the power grid. The findings of this study mark a substantial advancement in the design and optimization of grid-connected PV inverters, paving the way for cleaner and more efficient solar energy utilization.