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Maximum likelihood parameters estimation of single-diode model of photovoltaic generator

Author

Listed:
  • Ayang, Albert
  • Wamkeue, René
  • Ouhrouche, Mohand
  • Djongyang, Noël
  • Essiane Salomé, Ndjakomo
  • Pombe, Joseph Kessel
  • Ekemb, Gabriel

Abstract

In this paper, review on modeling photovoltaic (PV) generator is established first; next, the combination of the optimization method of maximum likelihood estimator (MLE) and Newton Raphson (NR) resolution for identifying unknown parameters of single diode PV module at different test conditions is proposed. This predicted method is compared with generalized least square estimator (LSE) known also as optimization method. The results are also compared with popular predictive methods as Villalva's and Lambert solution. The proposed method is applied for polycrystalline silicon photovoltaic MSX60 solar module at standard test conditions (STC) and at 1000 W/m2, 75 °C. Two types of comparison are made: first, the dynamic variations of parameters values are carried out by graphs and compared in tables with the values found with the other methods (mentioned above); the parameters have converged after up to 150 iterations at STC and the accuracy of estimated parameters is sensitive to the initial parameters of trust region. Secondly, the (I-V) or (P-V) curves are superposed, justifying the accuracy of the proposed method. The comparative errors graphs are also carried out. The results proved the effectiveness of the maximum likelihood estimator, by accuracy parameters of the PV module. An extended study is done for the recent mono-crystalline module CSK6-280M known as Canadian Solar's module. This last study reveals the accuracy for the proposed method during irradiation variation.

Suggested Citation

  • Ayang, Albert & Wamkeue, René & Ouhrouche, Mohand & Djongyang, Noël & Essiane Salomé, Ndjakomo & Pombe, Joseph Kessel & Ekemb, Gabriel, 2019. "Maximum likelihood parameters estimation of single-diode model of photovoltaic generator," Renewable Energy, Elsevier, vol. 130(C), pages 111-121.
    • Handle: RePEc:eee:renene:v:130:y:2019:i:c:p:111-121
    DOI: 10.1016/j.renene.2018.06.039
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    References listed on IDEAS

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    1. Carrero, C. & Ramírez, D. & Rodríguez, J. & Platero, C.A., 2011. "Accurate and fast convergence method for parameter estimation of PV generators based on three main points of the I–V curve," Renewable Energy, Elsevier, vol. 36(11), pages 2972-2977.
    2. Carrero, C. & Amador, J. & Arnaltes, S., 2007. "A single procedure for helping PV designers to select silicon PV modules and evaluate the loss resistances," Renewable Energy, Elsevier, vol. 32(15), pages 2579-2589.
    3. McHenry, Mark P., 2012. "Are small-scale grid-connected photovoltaic systems a cost-effective policy for lowering electricity bills and reducing carbon emissions? A technical, economic, and carbon emission analysis," Energy Policy, Elsevier, vol. 45(C), pages 64-72.
    4. Askarzadeh, Alireza & Rezazadeh, Alireza, 2013. "Artificial bee swarm optimization algorithm for parameters identification of solar cell models," Applied Energy, Elsevier, vol. 102(C), pages 943-949.
    5. 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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    4. Oumaima Mesbahi & Daruez Afonso & Mouhaydine Tlemçani & Amal Bouich & Fernando M. Janeiro, 2023. "Measurement Interval Effect on Photovoltaic Parameters Estimation," Energies, MDPI, vol. 16(18), pages 1-18, September.
    5. Kelachukwu J. Iheanetu, 2022. "Solar Photovoltaic Power Forecasting: A Review," Sustainability, MDPI, vol. 14(24), pages 1-31, December.
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    7. Rui Castro & Miguel Silva, 2021. "Experimental and Theoretical Validation of One Diode and Three Parameters–Based PV Models," Energies, MDPI, vol. 14(8), pages 1-25, April.
    8. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2019. "Identification of electrical parameters for three-diode photovoltaic model using analytical and sunflower optimization algorithm," Applied Energy, Elsevier, vol. 250(C), pages 109-117.
    9. CH Hussaian Basha & C Rani, 2020. "Different Conventional and Soft Computing MPPT Techniques for Solar PV Systems with High Step-Up Boost Converters: A Comprehensive Analysis," Energies, MDPI, vol. 13(2), pages 1-27, January.
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