An Improvement of Maximum Power Point Tracking Algorithm Based on Particle Swarm Optimization Method for Photovoltaic System

摘要

Partial shading is the cause of the reduction of the output power of the photovoltaic (PV) system due to changes in its P-V characteristic curve. Global Maximum Power Point Tracking (GMPPT) in more complex and multiple peaks conditions is the biggest challenge for current MPPT techniques to improve the performance of the system. This article introduces an improved method based on the traditional Particle Swarm optimization (I-PSO) algorithm to increase the convergence speed in a constantly changing and complex environment. The study not only considers the influence of the best location of the individual and the swarm but also focuses on the experience of the neighboring individuals with a better position to avoid the local extreme trap. In addition to that, a boost converter uses to simulate the proposed algorithm applying PSIM software. The simulating results with those previously under the same operating conditions showed the superiority of the proposed approach in improving the efficiency of the photovoltaic system.