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Extraction of Single Diode Model Parameters of Solar Cells and PV Modules by Combining an Intelligent Optimization Algorithm with Simplified Explicit Equation Based on Lambert W Function

Author

Listed:
  • Jianing Li

    (School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China)

  • Cheng Qin

    (School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China)

  • Chen Yang

    (School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China)

  • Bin Ai

    (School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China
    Guangdong Provincial Key Laboratory of Photovoltaic Technologies, Sun Yat-Sen University, Guangzhou 510006, China)

  • Yecheng Zhou

    (School of Materials Science and Engineering, Sun Yat-Sen University, Guangzhou 510006, China)

Abstract

In this paper, the explicit equation of the single diode model (SDM) expressed by the Lambert W function was reduced to its simplified form through variable replacement; then the simplified explicit equation was combined with an intelligent optimization algorithm to estimate the SDM parameters of solar cells and PV modules. To evaluate the parameter extraction performance of the new method, eight typical intelligent optimization algorithms were combined with the implicit, explicit, and simplified explicit equation to extract the SDM parameters of a solar cell and three types of PV modules. The results show that the new method not only improves the accuracy of parameter extraction but also enhances the robustness and convergence speed. Most importantly, the new method can nearly improve the parameter extraction accuracy of a poor-performing algorithm in traditional methods to the level of other well-performing algorithms without enhancing the algorithm itself. In a word, this study offers a new choice for a more accurate and reliable extraction of SDM parameters from both solar cells and PV modules.

Suggested Citation

  • Jianing Li & Cheng Qin & Chen Yang & Bin Ai & Yecheng Zhou, 2023. "Extraction of Single Diode Model Parameters of Solar Cells and PV Modules by Combining an Intelligent Optimization Algorithm with Simplified Explicit Equation Based on Lambert W Function," Energies, MDPI, vol. 16(14), pages 1-23, July.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:14:p:5425-:d:1195877
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    References listed on IDEAS

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    1. Tong, Nhan Thanh & Pora, Wanchalerm, 2016. "A parameter extraction technique exploiting intrinsic properties of solar cells," Applied Energy, Elsevier, vol. 176(C), pages 104-115.
    2. Toledo, F.J. & Blanes, José M., 2016. "Analytical and quasi-explicit four arbitrary point method for extraction of solar cell single-diode model parameters," Renewable Energy, Elsevier, vol. 92(C), pages 346-356.
    3. Chen, Yifeng & Wang, Xuemeng & Li, Da & Hong, Ruijiang & Shen, Hui, 2011. "Parameters extraction from commercial solar cells I-V characteristics and shunt analysis," Applied Energy, Elsevier, vol. 88(6), pages 2239-2244, June.
    4. Chen, Xu & Xu, Bin & Mei, Congli & Ding, Yuhan & Li, Kangji, 2018. "Teaching–learning–based artificial bee colony for solar photovoltaic parameter estimation," Applied Energy, Elsevier, vol. 212(C), pages 1578-1588.
    5. Yu, Kunjie & Qu, Boyang & Yue, Caitong & Ge, Shilei & Chen, Xu & Liang, Jing, 2019. "A performance-guided JAYA algorithm for parameters identification of photovoltaic cell and module," Applied Energy, Elsevier, vol. 237(C), pages 241-257.
    6. Yu, Kunjie & Liang, J.J. & Qu, B.Y. & Cheng, Zhiping & Wang, Heshan, 2018. "Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models," Applied Energy, Elsevier, vol. 226(C), pages 408-422.
    7. 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.
    8. Chellaswamy, C. & Ramesh, R., 2016. "Parameter extraction of solar cell models based on adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 97(C), pages 823-837.
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    Cited by:

    1. Tomas Ruzgas & Irma Jankauskienė & Audrius Zajančkauskas & Mantas Lukauskas & Matas Bazilevičius & Rugilė Kaluževičiūtė & Jurgita Arnastauskaitė, 2024. "Solving Linear and Nonlinear Delayed Differential Equations Using the Lambert W Function for Economic and Biological Problems," Mathematics, MDPI, vol. 12(17), pages 1-15, September.
    2. Andreea Sabadus & Nicoleta Stefu & Marius Paulescu, 2024. "Evaluating Outdoor Performance of PV Modules Using an Innovative Explicit One-Diode Model," Energies, MDPI, vol. 17(11), pages 1-12, May.
    3. Cheng Qin & Jianing Li & Chen Yang & Bin Ai & Yecheng Zhou, 2024. "Comparative Study of Parameter Extraction from a Solar Cell or a Photovoltaic Module by Combining Metaheuristic Algorithms with Different Simulation Current Calculation Methods," Energies, MDPI, vol. 17(10), pages 1-32, May.

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