Accurate Parameter Extraction of Photovoltaic Modules Using A Hybrid Analytical-Genetic Algorithm Based on The Double Diode Model

Reliable modeling of photovoltaic (PV) systems is essential for understanding their electrical behavior and evaluating their performance under different operating conditions. PV modules are presented by equivalent circuits, such as double diode model. In this paper, a hybrid technique is proposed to extract the seven parameters of this model by using analytical methods with a Genetic algorithm (GA) optimization. The shunt resistance and the photocurrent are determined by using the analytical method, while the other parameters are estimated using GA algorithm. Moreover, to enhance the extraction accuracy, an objective function based on the short-circuit current and current at Maximum power point (MPP) was employed to minimize the error of the proposed method. This approach is tested on several PV modules and under different environmental conditions and the obtained results are compared with other studies. The calculated RMSE values confirm the robustness of the suggested method, achieving lower errors.