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Single-Diode Models of PV Modules: A Comparison of Conventional Approaches and Proposal of a Novel Model

Author

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  • Tuyen Nguyen-Duc

    (Power System Department, Hanoi University of Science and Technology, Hanoi 11615, Vietnam)

  • Huy Nguyen-Duc

    (Power System Department, Hanoi University of Science and Technology, Hanoi 11615, Vietnam)

  • Thinh Le-Viet

    (Power System Department, Hanoi University of Science and Technology, Hanoi 11615, Vietnam)

  • Hirotaka Takano

    (Department of Electrical, Electronic and Computer Engineering, Gifu University, Gifu 501-1193, Japan)

Abstract

In this paper, the seven traditional models of photovoltaic (PV) modules are reviewed comprehensively to find out the appropriate model for reliability. All the models are validated using the Matlab code and graphical comparisons between models are made. The accuracy and convergence of each model is evaluated using the data of manufactured PV panels. Then, a novel model is proposed showing its consistent performance. The three most key parameters of the single-diode model are self-revised to adapt to various types of PV modules. This new method is verified in three types of PV panels’ data measured by the National Renewable Energy Laboratory (NREL), USA. The validated data show promising results when the error RMSEs’ range of the proposed model is under 0.36.

Suggested Citation

  • Tuyen Nguyen-Duc & Huy Nguyen-Duc & Thinh Le-Viet & Hirotaka Takano, 2020. "Single-Diode Models of PV Modules: A Comparison of Conventional Approaches and Proposal of a Novel Model," Energies, MDPI, vol. 13(6), pages 1-22, March.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:6:p:1296-:d:330979
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    References listed on IDEAS

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    1. Dehghanzadeh, Ahmad & Farahani, Gholamreza & Maboodi, Mohsen, 2017. "A novel approximate explicit double-diode model of solar cells for use in simulation studies," Renewable Energy, Elsevier, vol. 103(C), pages 468-477.
    2. Ciulla, Giuseppina & Lo Brano, Valerio & Di Dio, Vincenzo & Cipriani, Giovanni, 2014. "A comparison of different one-diode models for the representation of I–V characteristic of a PV cell," Renewable and Sustainable Energy Reviews, Elsevier, vol. 32(C), pages 684-696.
    3. Khanna, Vandana & Das, B.K. & Bisht, Dinesh & Vandana, & Singh, P.K., 2015. "A three diode model for industrial solar cells and estimation of solar cell parameters using PSO algorithm," Renewable Energy, Elsevier, vol. 78(C), pages 105-113.
    4. Oliva, Diego & Cuevas, Erik & Pajares, Gonzalo, 2014. "Parameter identification of solar cells using artificial bee colony optimization," Energy, Elsevier, vol. 72(C), pages 93-102.
    5. Wang, Gang & Zhao, Ke & Shi, Jiangtao & Chen, Wei & Zhang, Haiyang & Yang, Xinsheng & Zhao, Yong, 2017. "An iterative approach for modeling photovoltaic modules without implicit equations," Applied Energy, Elsevier, vol. 202(C), pages 189-198.
    6. Celik, Ali Naci & Acikgoz, NasIr, 2007. "Modelling and experimental verification of the operating current of mono-crystalline photovoltaic modules using four- and five-parameter models," Applied Energy, Elsevier, vol. 84(1), pages 1-15, January.
    7. Wang, Gang & Zhao, Ke & Qiu, Tian & Yang, Xinsheng & Zhang, Yong & Zhao, Yong, 2016. "The error analysis of the reverse saturation current of the diode in the modeling of photovoltaic modules," Energy, Elsevier, vol. 115(P1), pages 478-485.
    8. Humada, Ali M. & Hojabri, Mojgan & Mekhilef, Saad & Hamada, Hussein M., 2016. "Solar cell parameters extraction based on single and double-diode models: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 56(C), pages 494-509.
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    Cited by:

    1. Tuyen Nguyen-Duc & Duong Nguyen-Dang & Thinh Le-Viet & Goro Fujita, 2022. "Continuous Reconfiguration Framework for Photovoltaic Array under Variable Partial Shading Conditions: Heuristic-Based Algorithms with Optimizing Switching Operation," Energies, MDPI, vol. 15(18), pages 1-25, September.
    2. Angela Amato & Matteo Bilardo & Enrico Fabrizio & Valentina Serra & Filippo Spertino, 2021. "Energy Evaluation of a PV-Based Test Facility for Assessing Future Self-Sufficient Buildings," Energies, MDPI, vol. 14(2), pages 1-23, January.

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