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Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models

Author

Listed:
  • En-Jui Liu

    (Department of Green Energy and Information Technology, National Taitung University, Taitung 950309, Taiwan)

  • Rou-Wen Chen

    (Department of Green Energy and Information Technology, National Taitung University, Taitung 950309, Taiwan)

  • Qing-An Wang

    (Department of Green Energy and Information Technology, National Taitung University, Taitung 950309, Taiwan)

  • Wan-Ling Lu

    (Department of Green Energy and Information Technology, National Taitung University, Taitung 950309, Taiwan)

Abstract

Photovoltaic (PV) systems are the core technology for implementing net-zero carbon emissions by 2050. The performance of PV systems is strongly influenced by environmental factors, including irradiance, temperature, and shading, which makes it difficult to characterize the nonlinear and multi-coupling behavior of the systems. Accurate modeling is essential for reliable performance prediction and lifespan estimation. To address this challenge, a novel metaheuristic algorithm called shuffled puma optimizer (SPO) is deployed to perform parameter extraction and optimal configuration identification across four PV models. The robustness and stability of SPO are comprehensively evaluated through comparisons with advanced algorithms based on best fitness, mean fitness, and standard deviation. The root mean square error (RMSE) obtained by SPO for parameter extraction are 8.8180 × 10 −4 , 8.5513 × 10 −4 , 8.4900 × 10 −4 , and 2.3941 × 10 −3 for the single diode model (SDM), double diode model (DDM), triple diode model (TDM), and photovoltaic module model (PMM), respectively. A one-factor-at-a-time (OFAT) sensitivity analysis is employed to assess the relative importance of undetermined parameters within each PV model. The SPO-based modeling framework enables high-accuracy PV performance prediction, and its application to sensitivity analysis can accurately identify key factors that lead to reduced computational cost and improved adaptability for integration with energy management systems and intelligent electric grids.

Suggested Citation

  • En-Jui Liu & Rou-Wen Chen & Qing-An Wang & Wan-Ling Lu, 2025. "Shuffled Puma Optimizer for Parameter Extraction and Sensitivity Analysis in Photovoltaic Models," Energies, MDPI, vol. 18(15), pages 1-25, July.
    • Handle: RePEc:gam:jeners:v:18:y:2025:i:15:p:4008-:d:1711675
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    References listed on IDEAS

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    1. Słowik, Adam & Cpałka, Krzysztof & Xue, Yu & Hapka, Aneta, 2024. "An efficient approach to parameter extraction of photovoltaic cell models using a new population-based algorithm," Applied Energy, Elsevier, vol. 364(C).
    2. Hanaa Fathi & Deema Mohammed Alsekait & Arar Al Tawil & Israa Wahbi Kamal & Mohammad Sameer Aloun & Ibrahim I. M. Manhrawy, 2025. "Enhancing Sustainability in Renewable Energy: Comparative Analysis of Optimization Algorithms for Accurate PV Parameter Estimation," Sustainability, MDPI, vol. 17(6), pages 1-17, March.
    3. Hegazy Rezk & A. G. Olabi & Tabbi Wilberforce & Enas Taha Sayed, 2023. "A Comprehensive Review and Application of Metaheuristics in Solving the Optimal Parameter Identification Problems," Sustainability, MDPI, vol. 15(7), pages 1-24, March.
    4. Wenjing Lei & Qing He & Liu Yang & Hongzan Jiao, 2022. "Solar Photovoltaic Cell Parameter Identification Based on Improved Honey Badger Algorithm," Sustainability, MDPI, vol. 14(14), pages 1-26, July.
    5. Yacine Bouali & Basem Alamri, 2024. "Parameter Extraction for Photovoltaic Models with Flood-Algorithm-Based Optimization," Mathematics, MDPI, vol. 13(1), pages 1-39, December.
    6. Shufu Yuan & Yuzhang Ji & Yongxu Chen & Xin Liu & Weijun Zhang, 2023. "An Improved Differential Evolution for Parameter Identification of Photovoltaic Models," Sustainability, MDPI, vol. 15(18), pages 1-28, September.
    7. Samuel R. Fahim & Hany M. Hasanien & Rania A. Turky & Shady H. E. Abdel Aleem & Martin Ćalasan, 2022. "A Comprehensive Review of Photovoltaic Modules Models and Algorithms Used in Parameter Extraction," Energies, MDPI, vol. 15(23), pages 1-56, November.
    8. En-Jui Liu & Yi-Hsuan Hung & Che-Wun Hong, 2021. "Improved Metaheuristic Optimization Algorithm Applied to Hydrogen Fuel Cell and Photovoltaic Cell Parameter Extraction," Energies, MDPI, vol. 14(3), pages 1-16, January.
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