Particle Swarm Optimization Based Super Twisting Sliding Mode Controller MPPT Algorithm Design for Solar PV System

Abstract

To maximise energy harvest while keeping the solar photovoltaic (PV) system stable, proper regulation is essential. In this study, we explore the state-of-the-art in solar PV system management and offer a fresh method: Super Twisting Sliding Mode Controller (STSMC) using Particle Swarm Optimisation (PSO). The suggested method enhances control performance by combining the stability of Sliding Mode Control (SMC) with the optimisation skills of PSO. The goal is to improve solar PV systems' fault tolerance, resilience against uncertainties and disturbances, and Maximum Power Point Tracking (MPPT) accuracy. Results show that the suggested PSO-based STSMC is superior to traditional methods of control. Effective maximum power point tracking (MPPT) is made possible by combining PSO optimisation with the SMC structure. This allows for precise MPPT tracking regardless of the sun irradiation or ambient temperature. The technique also improves the system's fault tolerance and robustness by dealing with uncertainty and disturbances efficiently in real time. The study highlights limitations, such as the use of idealised settings, and provides recommendations for further research to enhance the suggested method. The MATLAB/Simulink Simulation Tool is used for the research.