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Photovoltaic (PV) systems play a crucial role in renewable energy production, and accurate parameter estimation is essential for modeling and performance analysis. In this paper, a hybrid method combining the secant and Newton-Raphson methods is employed to accurately estimate the five key parameters (I ph , I 0 , n, R s , and R sh ) of the single diode PV model. The method starts by using the secant method to estimate the series resistance (R s ), then analytical equations are used to estimate the other parameters (I ph , I 0 and R sh ). The Newton-Raphson technique is then applied to iteratively solve the I-V equation to finalize parameter estimation, while minimizing the root mean square error (RMSE) between modeled and measured data. The proposed method was tested on multiple solar cells and modules, including RTC France, PVM 752, PWP-201, STM6-40/36, and STP6-120/36, achieving RMSE values of , , and , respectively. Additionally, it was applied to the SP75 and SM55 modules under variable temperature and irradiance, and exhibited high accuracy. This hybrid approach provides significant improvement over purely numerical techniques and metaheuristic algorithms because it provides rapid convergence, reduced computational load, and high accuracy in PV parameter extraction. • The proposed hybrid method for PV parameter extraction combines the secant method with an iterative approach. • The proposed method validated using experimental data from various PV modules. • This method is simple, fast, and highly effective in solving nonlinear equations. • The method demonstrates superior accuracy in terms of RMSE compared to other cited methods. • The proposed method is applied to other modules under various environmental conditions of temperature T and irradiance G, i.e., solar module SM55 and SP75.
Fahmi et al. (Wed,) studied this question.