Comparison of Swarm Optimization Methods for MPPT in Partially Shaded Photovoltaic Systems

The use of solar energy for electricity grows mainly due to environmental issues. However, several challenges arise for researchers, such as improving the efficiency of photovoltaic systems in shading situations. In this opportunity, several algorithms attempt to search for the point of maximum power in a photovoltaic system, among them the artificial intelligence algorithms. Thus, this paper investigates the use of artificial intelligence in maximum power tracking techniques for partially shaded systems. A review of different methods is done and performed simulations. As a highlight, the particle swarm optimization was the fastest algorithm and the most accurate was artificial bee colony. Therefore, the tested algorithms obtained good efficiency, being the role of the designer to choose the most suitable for each system.