An Maximum Power Point Tracking Algorithm for Photovoltaic Power Systems Using the Particle Swarm Optimization Technique

Abstract

The application of Maximum Power Point Tracking (MPPT) techniques is extensively studied and widely utilized in photovoltaic (PV) systems to optimize power transfer from PV panels. These optimization techniques are crucial for the efficient operation of PV systems, with various types of converters, such as boost, buck-boost and Cuk converters, playing a pivotal role. Serving as a critical interface between the PV panel and the load, MPPT circuits are essential for maximizing energy transfer. In this study, a boost converter is chosen, and a control algorithm for the MPPT controller is proposed. The MPPT implementation is based on the Particle Swarm Optimization (PSO) technique. To validate its effectiveness, this method is compared with a commonly used MPPT algorithm, the Perturb and Observe (P&O) method, through simulations conducted in MATLAB. The simulation results clearly demonstrate the superiority of the PSO method. It provides faster convergence, improved tracking efficiency, and reduced steady-state oscillations compared to the P&O algorithm. These results confirm the potential of the PSO method as a high-performance and reliable MPPT solution for modern photovoltaic systems.