Hybrid Optimization for Enhanced PV Parameter Extraction: Integrating CJAYA and Numerical Methods in Single-Diode Model Analysis

This study introduces an advanced optimization approach for parameter extraction in photovoltaic (PV) cell modeling based on the Single-Diode Model (SDM). The method employs the CJAYA algorithm alongside numerical techniques to minimize the Root Mean Square Error (RMSE) between modeled and experimental current values. The aim of this combined approach is to improve the accuracy of SDM-based PV performance modeling. By integrating CJAYA with numerical methods such as Secant, Newton-Raphson, and Halley, the model achieves precise and consistent parameter estimation, effectively addressing the complex nonlinearities inherent in SDM PV cell behavior. The results demonstrate that this hybrid metaheuristic-numerical method provides a robust solution for parameter extraction, closely aligning simulation results with experimental data. This research highlights the potential of hybrid optimization techniques for SDM-based PV modeling, emphasizing their applicability in industrial settings where high-precision parameterization is crucial.