Extraction Of Electrical Parameters for Two-Diode Photovoltaic Model Using Combined Analytical and Genetic Algorithm

Abstract

Nowadays, the modeling of the photovoltaic model becomes more and more important because it allows the industry to understand more about its electrical circuit, which leads to better reliability. This electrical circuit can have five, seven, or nine parameters depending on the number of diodes. This paper discusses a novel method to extract the seven parameters of a double diode (DD) model based on datasheet parameters. The present approach combines genetic algorithms (GA) and analytical methods: Two parameters (photo-generated current and parallel resistance) are computed analytically, while the other parameters are optimized using the GA. The objective function used contains open circuit, short-circuit, and maximum power equations. The extracted seven parameters generated with this method are compared to those obtained through other methods. To assess the efficacy and reliability of the proposed approach, the P-V and I-V properties are evaluated using datasheet at various temperatures and solar irradiations. The results demonstrate a strong correlation; moreover, the Root Mean Square (RMSE) and the absolute error of current have been computed, and the model’s performance has been confirmed.