Extracting Double Diode Model Parameters Based on Cross Entropy Optimization Algorithm

Abstract

A Cross Entropy (CE) optimization technique is suggested in this study in order to extract the optimal parameters of solar cell model. The solar cell model namely Double diode model, is used in this paper in the purpose to verify the proposed method. The seven unknown parameters of double diode model are: the photo-generated current, the diffusion current, saturation current, the series resistance, the shunt resistance, the diffusion ideality factor and recombination diode ideality factor. These parameters were used to determine the corresponding maximum power point (MPP) from the illuminated current–voltage (I–V) characteristic. The metaheuristic algorithms have created a center of attention due to the non-linearity of the solar cell models and the incapability of traditional optimization methods to precisely extract the parameters. Different cases and studies have been done to identify the unknown parameters of the solar cell double model. The efficiency of CE algorithm is investigated by comparing this method with various and different other techniques. This comparison is done using statistical indicators and analysis such as: mean absolute bias error, root mean square error and coefficient of determination. The results show that CE is a very efficient technique to identify the electrical parameters of the PV solar cells and modules.