Abstract
Since the behavior of photovoltaic (PV) modules under different operational conditions is highly nonlinear, predicting the performance of PV systems in industrial applications is becoming a major challenge issue. Moreover, the most important information required to configure an optimal PV system is unavailable in all manufacturer’s datasheets. In this context, a novel method is recommended to optimize PV cells/module parameters with the ability to correctly characterize the I-V and P–V curves of different PV models. In the present article, a chaotic map is incorporated in the so-called quasi-oppositional Rao-1 algorithm to improve its efficiency, and the resulting algorithm is named quasi-oppositional logistic chaotic Rao-1 (QOLCR) algorithm. Numerical results indicate that the QOLCR algorithm has presented very good performance in terms of accuracy and robustness. The idea is to minimize the root mean square error (RMSE) between the estimated and the actual data. Simulation results in the single diode model give an RMSE of value \(7.73006208 \times {10}^{-4}\), and in the double diode model, an RMSE of value \(7.445111655 \times {10}^{-4}\) has been reached as the minimum value among the other compared optimization methods. Hence, the QOLCR approach also converges faster than the basic Rao-1 algorithm and its other variants. Moreover, the modified QO Rao-1 algorithm shows its perfectness and could be involved as tools for optimal designing of PV systems.
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The datasets generated and/or analysed during the current study are included in the manuscript.
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The researchers wish to extend their sincere gratitude to the Deanship of Scientific Research at the Islamic University of Madinah for the support provided to the Post-Publishing Program.
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The researchers wish to extend their sincere gratitude to the Deanship of Scientific Research at the Islamic University of Madinah for the support provided to the Post-Publishing Program.
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All authors contributed equally in all parts of this work as follows: the study conception and design has been prepared by Dr. B. Lekouaghet and Dr. S. Haddad. Data analysis and interpretation of results were performed by Prof. M. Benghanem and Dr. A. Soukkou. The draft manuscript has been prepared by Dr. B. Lekouaghet and Dr. S. Haddad. The review, correction, and editing have been elaborated by Prof. Mohamed Benghanem. All authors reviewed the results and approved the final version of the manuscript.
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Benghanem, M., Lekouaghet, B., Haddad, S. et al. Optimization of pv cells/modules parameters using a modified quasi-oppositional logistic chaotic rao-1 (QOLCR) algorithm. Environ Sci Pollut Res 30, 44536–44552 (2023). https://doi.org/10.1007/s11356-022-24941-2
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DOI: https://doi.org/10.1007/s11356-022-24941-2