On the problem formulation for parameter extraction of the photovoltaic model: Novel integration of hybrid evolutionary algorithm and Levenberg Marquardt based on adaptive damping parameter formula

The estimation of the unknown parameters of the photovoltaic (PV) model is crucial for accurately verifying its real performance precisely under a wide range of climatic conditions. This paper presents an approach to determine the nine parameters of the three diode (TD) PV model based on the integration of the guaranteed convergence arithmetic optimization algorithm and Levenberg-Marquardt with adaptive damping nonlinear parameter method named as GCAOA(AdLM). The keystone of the GCAOA(AdLM) model is accomplished by efficaciously enhancing the exploiter-explorer tendency with inclusion of various powerful hybrid strategies in terms the methodology itself. In addition, the objective function is newly designed leveraging on Levenberg-Marquardt with adaptive damping parameter method to accurately determine the initial roots parameters of the TD PV model. The experimental results demonstrate that the proposed GCAOA(AdLM) can reduce the root mean square error (RMSE), mean bias error (MBE), deviation of solar radiation's levels (d(i)), test statistical (TS), and absolute error (AE) to zero and the determination coefficient (R-2) to 1 for all environmental conditions, with statistical reasons and comparisons against well-published approaches available in the literature.