Review and Comparative Analysis of Metaheuristic MPPT Algorithms in PV Systems Under Partial Shading Conditions

The power efficiency of photovoltaic energy systems mainly depends on climatic conditions such as solar irradiation and temperature. Therefore, several types of maximum power point tracking (MPPT) algorithms have been proposed to get the maximum efficiency. However, traditional algorithms perform insufficient response for reaching global maximum power points (GMPPs) under partial shading conditions. In order to improve this issue, this paper investigates and compares the tracking capability of particle swarm optimization (PSO), gray wolf algorithm (GWO) and dragonfly optimization algorithm (DFO) methods at first. Results show that DFO responds faster and operates with less error in tracking GMPPs than others. Furthermore, a hybrid PSO-DFO algorithm is proposed in the paper by using the best position of the particle in the PSO algorithm and the best position of the swarm into the dragonfly algorithm. It is observed that the maximum power point tracking performance of this proposed hybrid algorithm is better than DFO, GWO and PSO algorithms.