Application of Swarm Optimization Algorithms for Maximum Power Point Tracking of Photovoltaic System – A comparative study

Abstract

In recent years, given the growing attention towards the usage of renewable energy sources, maximum power point tracking (MPPT) based on Swarm Optimization Algorithms (SOAs) have widely developed. The main advantage of SOAs-based MPPT methods are the robust, reliable, and fast performance. Furthermore, these approaches are capability of tracking of maximum power in real-time conditions, such as partial shading conditions (PSC) and different levels of temperature and irradiance. The paper considers five SOAs, including proposed differential particle swarm optimization (DPSO), particle swarm optimization (PSO), genetic algorithm (GA), differential evolution (DE) and harmony search (HS). These SOAs have been tested on an experimental MPPT system at Control Engineering and Automatic Lab, Ho Chi Minh City University of Transport, Vietnam. A comparison of these methods have been employed by running 100 times for each method with the same initial conditions and then the proposed DPSO method is proven to be the most effective to tackle MPPT problem.