A hybrid numerical-analytical approach for solar cells and modules parameter extraction using the Regula-Falsi method
Year: 2025
Type: article
Abstract: The growing world interest in clean and sustainable energy has tremendously driven research on photovoltaic systems, with a strong emphasis on the need for accurate modeling and parameter extraction. Accurate PV modeling is vital for optimizing, simulating, and generally enhancing PV device performance. As much as there has been great development, available techniques have commonly faced limitations in finding an adequate balance between analytical accuracy and numerical reliability. In order to overcome these limitations, this paper proposes an innovative hybrid technique that integrates analytical solutions with numerical iterative strategies to accurately extract parameters of the single diode model using the Regula Falsi method. The new approach provides high accuracy in simulating photovoltaic modules by minimizing the Root Mean Square Error (RMSE) between experimental and simulated current-voltage data. It achieves an RMSE value of 7.746E-04 A, which is 1.35% better than the best alternative approach for RTC France. For Photowatt-PWP 201, it achieves 2.148E-03 A with a 0.12% improvement. It maintains comparable accuracy for PVM 752 GaAs, with an RMSE of 2.912E-04A, and reaches 1.731E-03A with an increase of 9.02% for the STM6-40/36 module. Comparative analysis with state-of-the-art techniques highlights the superior efficiency and reliability of the proposed method. • A new hybrid method combining analytical and iterative approaches is proposed for accurate extraction of single-diode model parameters. • The method improves convergence stability and reduces estimation error under diverse operating conditions. • The approach is validated on multiple PV technologies using real datasheets, showing high accuracy and low RMSE values. • Comparative analysis confirms the method's superiority over state-of-the-art analytical, numerical, hybrid, and meta-heuristic techniques.
Source: Unconventional Resources
Institution: Université Ibn Zohr
Language: English
Field: Energy
Domain: Physical Sciences
Open Access status: diamond
OpenAlex ID: W4415423805