Intelligent Controller based Maximum Power Point Tracking for Solar PV System

Abstract

Solar photovoltaic system performance depends on environmental conditions. Solar photovoltaic panel is a power source having nonlinear internal resistance. As the intensity of light falling on the panel varies, its voltage as well as its internal resistance both varies. To extract maximum power from the panel, the load resistance should be equal to the internal resistance of the panel. This paper analyses the improved modelling of solar PV module and proposes a genetic algorithm (GA) based maximum power point tracking. The GA optimized values are used to train the artificial neural network (ANN). The MPPT is simulated and studied using MATLAB software.