Rigorous reduction of partial shading condition in grid connected solar PV system using discrete time-based PSO controller

Abstract

Solar industry has seen tremendous development over the past decade and in particular, the PV (Photovoltaic) system which has an imperative advancement almost in all fields of science. Envisaging various faults in the PV system will significantly enhance the efficiency, reliability, and life of the PV system. The main vulnerable element in the PV system which is subjected under different weather condition causes total damage to the system. Proper monitoring and maintenance are needed to increase the life of the system. Several investigations were made so far to predict the faults in the PV system such as the Visual method, the Thermal method, the Electrical detection method, the Machine learning techniques, the Arc fault detection technique and the Protection device-based techniques were used generally. But more effective fault diagnosis techniques are required for PV arrays. The proposes a novel method for reducing the partial shading condition in solar PV system connected to a grid which consists of a discrete time-based particle swarm optimization (PSO) controller that controls the irradiation or partial shading as well as any short circuits in PV cell. Hence, this proposed work enhances with producing efficient energy by achieving high predictive accuracy of about 99%, high efficiency of about 98.9% and low THD (0.9) under partial shading conditions as well as harmonics.