Hybrid gravitational search particle swarm optimization algorithm for GMPPT under partial shading conditions.

Solar energy has become one of the popular choices among all renewable energy resources. In order to harvest solar energy, a photovoltaic (PV) system is required. Nowadays, researchers are increasingly paying more attention to PV system since it is affordable and easy to install and maintain. However, unpredictable weather and operating conditions of a PV system may reduce power generation. Therefore, a global maximum power point tracking (GMPPT) controller needs to be installed in the PV system to improve the power generation capability. However, the conventional GMPPT algorithm is less effective because of unsteady oscillations. In this paper, we propose a hybrid method of gravitational search particle swarm optimization (GSPSO) algorithm to track GMPP faster and more efficiently. The proposed algorithm utilizes the exploitation ability of the particle swarm optimization (PSO) algorithm and the exploration ability of the gravitational search algorithm (GSA). Simulation results show that the proposed algorithm has the fastest tracking speed and the highest generated power compared with the other competitive algorithms. [ABSTRACT FROM AUTHOR]