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An explicit method to extract fitting parameters in lumped-parameter equivalent circuit model of industrial solar cells

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  • Yu, Fei
  • Huang, Gongyi
  • Xu, Chuanzhong

Abstract

An explicit parameter-extraction method is proposed to estimate the values of fitting parameters in lumped-parameter equivalent circuit model of industrial solar cells. The explicit method is based on polynomial fitting curves on Matlab platform, TCAD device simulation results of Silvaco Atlas, and experimental data of silicon-based solar cells’ current-voltage characteristics. Such an explicit parameter-extraction method can be directly applied into the analytical solutions to one-diode lumped-parameter equivalent circuit model to complete the simulations for electrostatic properties of solar cells. First, the current-voltage characteristics of industrial silicon-based solar cells are also derived analytically as the previous works completed by other researchers and the four key factors especially for the maximum power formula are solved through the effective diode approach. Second, polynomial curve is used to fit current-voltage characteristics from simulation and experiment results of solar cells under illumination. Third, the polynomial fitting result, the short circuit current, and the open circuit voltage are used to extract explicitly all of five parameters included in the one-diode lumped-parameter equivalent circuit model for industrial solar cells. Finally, the extracted fitting parameters are substituted into the analytical solution to current-voltage characteristics and the obtained current-voltage characteristics are compared with device simulation results from Silvaco Atlas and experimental data from silicon-based solar cells. As a result, such an explicit extraction procedure could be regarded as a fast and accurate method to estimate model parameters in industrial solar cells, which is important for not only photoelectric device simulations but also process analysis.

Suggested Citation

  • Yu, Fei & Huang, Gongyi & Xu, Chuanzhong, 2020. "An explicit method to extract fitting parameters in lumped-parameter equivalent circuit model of industrial solar cells," Renewable Energy, Elsevier, vol. 146(C), pages 2188-2198.
  • Handle: RePEc:eee:renene:v:146:y:2020:i:c:p:2188-2198
    DOI: 10.1016/j.renene.2019.08.070
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    References listed on IDEAS

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    1. Jiang, Lian Lian & Maskell, Douglas L. & Patra, Jagdish C., 2013. "Parameter estimation of solar cells and modules using an improved adaptive differential evolution algorithm," Applied Energy, Elsevier, vol. 112(C), pages 185-193.
    2. Biswas, Partha P. & Suganthan, P.N. & Wu, Guohua & Amaratunga, Gehan A.J., 2019. "Parameter estimation of solar cells using datasheet information with the application of an adaptive differential evolution algorithm," Renewable Energy, Elsevier, vol. 132(C), pages 425-438.
    3. Chenni, R. & Makhlouf, M. & Kerbache, T. & Bouzid, A., 2007. "A detailed modeling method for photovoltaic cells," Energy, Elsevier, vol. 32(9), pages 1724-1730.
    4. 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.
    5. Ishaque, Kashif & Salam, Zainal & Mekhilef, Saad & Shamsudin, Amir, 2012. "Parameter extraction of solar photovoltaic modules using penalty-based differential evolution," Applied Energy, Elsevier, vol. 99(C), pages 297-308.
    6. AlHajri, M.F. & El-Naggar, K.M. & AlRashidi, M.R. & Al-Othman, A.K., 2012. "Optimal extraction of solar cell parameters using pattern search," Renewable Energy, Elsevier, vol. 44(C), pages 238-245.
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    Cited by:

    1. Huang, Gongyi & Liang, Ying & Sun, Xiaofang & Xu, Chuanzhong & Yu, Fei, 2020. "Analyzing S-Shaped I–V characteristics of solar cells by solving three-diode lumped-parameter equivalent circuit model explicitly," Energy, Elsevier, vol. 212(C).
    2. Khan, Firoz & Al-Ahmed, Amir & Al-Sulaiman, Fahad A., 2021. "Critical analysis of the limitations and validity of the assumptions with the analytical methods commonly used to determine the photovoltaic cell parameters," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    3. Zheng, Zhihang & Xiao, Jian & Yang, Ying & Xu, Feng & Zhou, Jin & Liu, Hongcheng, 2024. "Optimization of exterior wall insulation in office buildings based on wall orientation: Economic, energy and carbon saving potential in China," Energy, Elsevier, vol. 290(C).

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