Maximum Power Point Genetic Identification Function for Photovoltaic System

This paper proposes the identification of maximum power point (MPP) function for photovoltaic (PV) module using the genetic algorithm (GA). Then deduction of the required function to generate the reference values to drive the tracking system in the PV system at MPP is done with the aid of Artificial Neural Network (ANN). This function deals with the more probable situations for variable values of temperature and irradiance to get the corresponding voltage and current at maximum power. The mathematical PV module modeling depends on Schott ASE-300-DGF PV panel with the aid of MATLAB environment. The aim of this paper is to pick peaks of the power curves (maximum points). The simulation results at MPP are well depicted in 3-D figures to be used as training or learning data for the ANN model.