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    Robust Newton-Raphson method integrated improved Differential Evolution (RoNRIDE) algorithm for accurate PV parameter extraction: a multi-model and multi-condition benchmarking study
    (Springer, 2025) Gungor, Okan
    This study proposes a robust parameter extraction methodology that integrates the Newton-Raphson method into an improved Differential Evolution algorithm (RoNRIDE) to accurately extract photovoltaic (PV) model parameters. The DE approach is modified to enhance the accuracy and stability of the solution, while the Newton-Raphson method is used to reduce computational complexity by solving the nonlinear and implicit equations of PV models. To investigate the performance of the proposed algorithm in PV model parameter extraction, comprehensive evaluations are carried out under five different numbers of agents (50-300), real-time measurements, two different noise levels (0.5% and 1%), four different measurement point quantities (40-100), six different PV sources and three different PV models, such as single-diode model (SDM), double-diode model (DDM) and triple-diode model (TDM). Also, the CEC 2022 test suite is employed to evaluate the overall performance of the proposed algorithm. The RoNRIDE has exhibited outstanding performance in the CEC 2022 test suite and remarkable accuracy by achieving RMSE values of 7.32600E - 04, 1.87269E - 03, 1.72719E - 03 and 1.42510E - 02 for benchmark PV sources such as R.T.C. France, Photowatt-PWP201, STM6-40/36 and STP6-120/36, respectively. Consequently, the proposed algorithm has demonstrated robustness under difficult operating conditions and has been benchmarked against 18 algorithms, clearly showing its superiority.