Hybrid Firefly Algorithm with Sine Cosine Algorithm for solar photovoltaic parameter estimation

For designing high-performance photovoltaic (PV) systems, parameter determination of solar cell models is very important. In this article, a hybrid method using Firefly Algorithm (FA) with the Sine Cosine Algorithm (SCA) is proposed to identify the unknown electrical parameters of single diode model (SDM) of PV solar cells based on experimental data of I-V characteristic curve. During the optimization process, the main objective is to minimize the root mean square error (RMSE) between the measured data and the calculated data. To demonstrate the efficiency of the suggested HFASCA, a comparison between its numerical results and those of other optimisation methods in the literature, is made. The simulation results reveal a high performance of the HFASCA with an accurate identification of the extracted parameters.