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A linear method to extract diode model parameters of solar panels from a single I–V curve

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  • Lim, Li Hong Idris
  • Ye, Zhen
  • Ye, Jiaying
  • Yang, Dazhi
  • Du, Hui

Abstract

The I–V characteristic curve is very important for solar cells/modules being a direct indicator of performance. But the reverse derivation of the diode model parameters from the I–V curve is a big challenge due to the strong nonlinear relationship between the model parameters. It seems impossible to solve such a nonlinear problem accurately using linear identification methods, which is proved wrong in this paper. By changing the viewpoint from conventional static curve fitting to dynamic system identification, the integral-based linear least square identification method is proposed to extract all diode model parameters simultaneously from a single I–V curve. No iterative searching or approximation is required in the proposed method. Examples illustrating the accuracy and effectiveness of the proposed method, as compared to the existing approaches, are presented in this paper. The possibility of real-time monitoring of model parameters versus environmental factors (irradiance and/or temperatures) is also discussed.

Suggested Citation

  • Lim, Li Hong Idris & Ye, Zhen & Ye, Jiaying & Yang, Dazhi & Du, Hui, 2015. "A linear method to extract diode model parameters of solar panels from a single I–V curve," Renewable Energy, Elsevier, vol. 76(C), pages 135-142.
    • Handle: RePEc:eee:renene:v:76:y:2015:i:c:p:135-142
    DOI: 10.1016/j.renene.2014.11.018
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    References listed on IDEAS

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    1. Yordanov, Georgi Hristov & Midtgård, Ole-Morten & Saetre, Tor Oskar, 2012. "Series resistance determination and further characterization of c-Si PV modules," Renewable Energy, Elsevier, vol. 46(C), pages 72-80.
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    Cited by:

    1. Esteban Velilla & Juan Bernardo Cano & Keony Jimenez & Jaime Valencia & Daniel Ramirez & Franklin Jaramillo, 2018. "Numerical Analysis to Determine Reliable One-Diode Model Parameters for Perovskite Solar Cells," Energies, MDPI, vol. 11(8), pages 1-12, July.
    2. Peñaranda Chenche, Luz Elena & Hernandez Mendoza, Oscar Saul & Bandarra Filho, Enio Pedone, 2018. "Comparison of four methods for parameter estimation of mono- and multi-junction photovoltaic devices using experimental data," Renewable and Sustainable Energy Reviews, Elsevier, vol. 81(P2), pages 2823-2838.
    3. Singh, Rashmi & Sharma, Madhu & Rawat, Rahul & Banerjee, Chandan, 2018. "An assessment of series resistance estimation techniques for different silicon based SPV modules," Renewable and Sustainable Energy Reviews, Elsevier, vol. 98(C), pages 199-216.
    4. Wang, Shinong & Luo, Huan & Ge, Yuan & Liu, Shilin, 2021. "A new approach for modeling photovoltaic modules based on difference equation," Renewable Energy, Elsevier, vol. 168(C), pages 85-96.
    5. Kumar, Manish & Kumar, Arun, 2017. "Performance assessment and degradation analysis of solar photovoltaic technologies: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 554-587.
    6. Gulkowski, Slawomir & Muñoz Diez, José Vicente & Aguilera Tejero, Jorge & Nofuentes, Gustavo, 2019. "Computational modeling and experimental analysis of heterojunction with intrinsic thin-layer photovoltaic module under different environmental conditions," Energy, Elsevier, vol. 172(C), pages 380-390.
    7. Zhang, Yunpeng & Hao, Peng & Lu, Hao & Ma, Jiao & Yang, Ming, 2022. "Modelling and estimating performance for PV module under varying operating conditions independent of reference condition," Applied Energy, Elsevier, vol. 310(C).
    8. Jordehi, A. Rezaee, 2016. "Parameter estimation of solar photovoltaic (PV) cells: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 354-371.
    9. Pillai, Dhanup S. & Rajasekar, N., 2018. "Metaheuristic algorithms for PV parameter identification: A comprehensive review with an application to threshold setting for fault detection in PV systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3503-3525.
    10. Gong, Yujian & Wang, Zuo & Lai, Zeyu & Jiang, Minlin, 2021. "TVACPSO-assisted analysis of the effects of temperature and irradiance on the PV module performances," Energy, Elsevier, vol. 227(C).
    11. Abbassi, Rabeh & Abbassi, Abdelkader & Jemli, Mohamed & Chebbi, Souad, 2018. "Identification of unknown parameters of solar cell models: A comprehensive overview of available approaches," Renewable and Sustainable Energy Reviews, Elsevier, vol. 90(C), pages 453-474.
    12. Slawomir Gulkowski, 2023. "Modeling and Experimental Studies of the Photovoltaic System Performance in Climate Conditions of Poland," Energies, MDPI, vol. 16(20), pages 1-16, October.
    13. Singh, Rashmi & Sharma, Madhu & Yadav, Kamlesh, 2022. "Degradation and reliability analysis of photovoltaic modules after operating for 12 years: A case study with comparisons," Renewable Energy, Elsevier, vol. 196(C), pages 1170-1186.
    14. 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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