ZRMSE: A New and Reliable Approach for Computing the Circuit Parameters of Single-Diode Solar Photovoltaic Model

Because the parameters have been determined through experimental observations, it is possible to make an accurate estimate to forecast the output current of PhotoVoltaic (PV) cells. PV system study and analysis may be made significantly easier, which may be beneficial theoretically and practically. The parameter identification problem has been addressed by a plethora of stochastic models that have been extensively prominent in recent years. Many researchers have developed hybrid approaches that use the advantage of two or more algorithms to improve the reliability, precision, and overall performance of existing algorithms. Although most approaches in the literature are concerned with approach, only a few research have looked at the design of the objective function, leaving a conceptual void in this field of study. In this paper, a novel chaotic northern goshawk optimization algorithm based on the adoption of modified Levenberg-Marquardt is proposed to extract the parameter of the single-diode PV model of the cell/module globally. The findings from the experiment indicate that the suggested strategy performs remarkably well in achieving zero error for cells/modules, as evidenced by statistical data analysis and comparison with experimental data.