Maximum power point tracking of SPV at varying atmospheric condition using Genetic Algorithm

Abstract

The output power of the PV panel depends on the amount of irradiation, temperature and the connected load. This controls the operating point i.e. voltage and current of the panel. The maximum power from the PV panel can be extracted if the impedances of both source (PV panel) and load are matching. The internal resistance of the panel depends upon the irradiation i.e. the intensity of the sunlight falling on it. The change in the atmospheric conditions results in the mismatch between the load and source impedance. Due to this mismatch, panel is not operated at its maximum power point (MPP) resulting in lower generation of power thereby decreasing the overall efficiency of the system. This paper presents a simulation study on enhancing the efficiency of a solar photovoltaic panel by finding the optimum operating parameters under varying atmospheric conditions using Genetic Algorithm. The said technique finds the optimum voltage and current corresponding to the given atmospheric condition. The proposed algorithm is tested at different temperature and irradiation. Results show that the Genetic Algorithm can track the maximum power point accurately with high conversion performance.