IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v130y2019icp111-121.html
   My bibliography  Save this article

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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148118306840
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2018.06.039?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Ding, Kun & Chen, Xiang & Jiang, Meng & Yang, Hang & Chen, Xihui & Zhang, Jingwei & Gao, Ruiguang & Cui, Liu, 2024. "Feature extraction and fault diagnosis of photovoltaic array based on current–voltage conversion," Applied Energy, Elsevier, vol. 353(PB).
    2. Arthur H.A. Melani & Carlos A. Murad & Adherbal Caminada Netto & Gilberto F.M. Souza & Silvio I. Nabeta, 2019. "Maintenance Strategy Optimization of a Coal-Fired Power Plant Cooling Tower through Generalized Stochastic Petri Nets," Energies, MDPI, vol. 12(10), pages 1-28, May.
    3. Li, Lanyu & Yao, Zhiyi & You, Siming & Wang, Chi-Hwa & Chong, Clive & Wang, Xiaonan, 2019. "Optimal design of negative emission hybrid renewable energy systems with biochar production," Applied Energy, Elsevier, vol. 243(C), pages 233-249.
    4. Mehmet Yesilbudak, 2021. "Parameter Extraction of Photovoltaic Cells and Modules Using Grey Wolf Optimizer with Dimension Learning-Based Hunting Search Strategy," Energies, MDPI, vol. 14(18), pages 1-27, September.
    5. Qais, Mohammed H. & Hasanien, Hany M. & Alghuwainem, Saad, 2020. "Parameters extraction of three-diode photovoltaic model using computation and Harris Hawks optimization," Energy, Elsevier, vol. 195(C).
    6. Vincenzo Stornelli & Mirco Muttillo & Tullio de Rubeis & Iole Nardi, 2019. "A New Simplified Five-Parameter Estimation Method for Single-Diode Model of Photovoltaic Panels," Energies, MDPI, vol. 12(22), pages 1-20, November.
    7. 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.
    8. 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.
    9. Manish Kumar Singla & Jyoti Gupta & Parag Nijhawan & Parminder Singh & Nimay Chandra Giri & Essam Hendawi & Mohamed I. Abu El-Sebah, 2023. "Parameter Estimation Techniques for Photovoltaic System Modeling," Energies, MDPI, vol. 16(17), pages 1-16, August.
    10. 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.
    11. 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.
    12. Kelachukwu J. Iheanetu, 2022. "Solar Photovoltaic Power Forecasting: A Review," Sustainability, MDPI, vol. 14(24), pages 1-31, December.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Chen, Zhicong & Wu, Lijun & Lin, Peijie & Wu, Yue & Cheng, Shuying, 2016. "Parameters identification of photovoltaic models using hybrid adaptive Nelder-Mead simplex algorithm based on eagle strategy," Applied Energy, Elsevier, vol. 182(C), pages 47-57.
    2. 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.
    3. Chin, Vun Jack & Salam, Zainal & Ishaque, Kashif, 2015. "Cell modelling and model parameters estimation techniques for photovoltaic simulator application: A review," Applied Energy, Elsevier, vol. 154(C), pages 500-519.
    4. Mehmet Yesilbudak, 2021. "Parameter Extraction of Photovoltaic Cells and Modules Using Grey Wolf Optimizer with Dimension Learning-Based Hunting Search Strategy," Energies, MDPI, vol. 14(18), pages 1-27, September.
    5. Tong Kang & Jiangang Yao & Min Jin & Shengjie Yang & ThanhLong Duong, 2018. "A Novel Improved Cuckoo Search Algorithm for Parameter Estimation of Photovoltaic (PV) Models," Energies, MDPI, vol. 11(5), pages 1-31, April.
    6. Chaabane Bouali & Horst Schulte & Abdelkader Mami, 2019. "A High Performance Optimizing Method for Modeling Photovoltaic Cells and Modules Array Based on Discrete Symbiosis Organism Search," Energies, MDPI, vol. 12(12), pages 1-32, June.
    7. 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.
    8. Long, Wen & Wu, Tiebin & Xu, Ming & Tang, Mingzhu & Cai, Shaohong, 2021. "Parameters identification of photovoltaic models by using an enhanced adaptive butterfly optimization algorithm," Energy, Elsevier, vol. 229(C).
    9. Chen, Xu & Yu, Kunjie & Du, Wenli & Zhao, Wenxiang & Liu, Guohai, 2016. "Parameters identification of solar cell models using generalized oppositional teaching learning based optimization," Energy, Elsevier, vol. 99(C), pages 170-180.
    10. Nunes, H.G.G. & Pombo, J.A.N. & Mariano, S.J.P.S. & Calado, M.R.A. & Felippe de Souza, J.A.M., 2018. "A new high performance method for determining the parameters of PV cells and modules based on guaranteed convergence particle swarm optimization," Applied Energy, Elsevier, vol. 211(C), pages 774-791.
    11. Ghani, F. & Rosengarten, G. & Duke, M. & Carson, J.K., 2014. "The numerical calculation of single-diode solar-cell modelling parameters," Renewable Energy, Elsevier, vol. 72(C), pages 105-112.
    12. Kumar, Manish & Malik, Prashant & Chandel, Rahul & Chandel, Shyam Singh, 2023. "Development of a novel solar PV module model for reliable power prediction under real outdoor conditions," Renewable Energy, Elsevier, vol. 217(C).
    13. Youssef, Ayman & El-Telbany, Mohammed & Zekry, Abdelhalim, 2017. "The role of artificial intelligence in photo-voltaic systems design and control: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 78(C), pages 72-79.
    14. Bastidas-Rodriguez, J.D. & Petrone, G. & Ramos-Paja, C.A. & Spagnuolo, G., 2017. "A genetic algorithm for identifying the single diode model parameters of a photovoltaic panel," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 131(C), pages 38-54.
    15. Chin, Vun Jack & Salam, Zainal, 2019. "A New Three-point-based Approach for the Parameter Extraction of Photovoltaic Cells," Applied Energy, Elsevier, vol. 237(C), pages 519-533.
    16. Louzazni, Mohamed & Al-Dahidi, Sameer, 2021. "Approximation of photovoltaic characteristics curves using Bézier Curve," Renewable Energy, Elsevier, vol. 174(C), pages 715-732.
    17. 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.
    18. Martin Ćalasan & Dražen Jovanović & Vesna Rubežić & Saša Mujović & Slobodan Đukanović, 2019. "Estimation of Single-Diode and Two-Diode Solar Cell Parameters by Using a Chaotic Optimization Approach," Energies, MDPI, vol. 12(21), pages 1-14, November.
    19. Lin, Xiankun & Wu, Yuhang, 2020. "Parameters identification of photovoltaic models using niche-based particle swarm optimization in parallel computing architecture," Energy, Elsevier, vol. 196(C).
    20. Muangkote, Nipotepat & Sunat, Khamron & Chiewchanwattana, Sirapat & Kaiwinit, Sirilak, 2019. "An advanced onlooker-ranking-based adaptive differential evolution to extract the parameters of solar cell models," Renewable Energy, Elsevier, vol. 134(C), pages 1129-1147.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:130:y:2019:i:c:p:111-121. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.