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Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination

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Abstract

The parameter determination based on experimental data aids in providing an accurate assessment for predicting the output current of the PV cells. This may be extremely helpful both practically and theoretically in the PV system simulation, optimization, and evaluation. Numerous stochastic methods have been widely utilized in recent decades to tackle the parameter extraction optimization problem. Hybrid methods that take advantage of two or more algorithms have been proposed by many to further enhance their accuracy, stability, and overall performance. However, the majority of the methods in the literature concentrate on the methodology, with few studies considering the formulation of the objective function, resulting in a theoretical gap in this area of study. In this work, a new improved arithmetic optimization method based on the adaption of Newton–Raphson and Levenberg–Marquardt damping parameter (IAOANRaLMp) is presented to globally extract the parameter of the single- and double-diode PV models. The experimental findings demonstrate that the proposed IAOANRaLMp approach performs exceptionally well in terms of minimizing error to zero for both models, as indicated by various statistical criteria and comparison with experimental data.

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Ridha, H.M., Hizam, H., Mirjalili, S. et al. Zero root-mean-square error for single- and double-diode photovoltaic models parameter determination. Neural Comput & Applic 34, 11603–11624 (2022). https://doi.org/10.1007/s00521-022-07047-1

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