IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i15p5350-d870077.html
   My bibliography  Save this article

Low-Cost I–V Tracer for PV Fault Diagnosis Using Single-Diode Model Parameters and I–V Curve Characteristics

Author

Listed:
  • Vorachack Kongphet

    (GeePs, CentraleSupélec, CNRS, Université Paris-Saclay/Sorbonne Université, 3-11 Rue Joliot Curie, 91192 Gif Sur Yvette, France
    CNRS, CentraleSupélec, Université Paris-Saclay, L2S, 3 Rue Joliot Curie, 91192 Gif Sur Yvette, France)

  • Anne Migan-Dubois

    (GeePs, CentraleSupélec, CNRS, Université Paris-Saclay/Sorbonne Université, 3-11 Rue Joliot Curie, 91192 Gif Sur Yvette, France)

  • Claude Delpha

    (CNRS, CentraleSupélec, Université Paris-Saclay, L2S, 3 Rue Joliot Curie, 91192 Gif Sur Yvette, France)

  • Jean-Yves Lechenadec

    (IUT Cachan, Université Paris-Saclay, 9 Avenue de la Division Leclerc, 94230 Cachan, France)

  • Demba Diallo

    (GeePs, CentraleSupélec, CNRS, Université Paris-Saclay/Sorbonne Université, 3-11 Rue Joliot Curie, 91192 Gif Sur Yvette, France)

Abstract

The continuous health monitoring of PV modules is mandatory to maintain their high efficiency and minimize power losses due to faults or failures. In this work, a low-cost embedded tracer is developed to measure the I–V curve of a PV module in less than 0.2 s. The data are used to extract the five parameters of the single-diode model and its main characteristics (open-circuit voltage, short-circuit current, and maximum power). Experimental data are used to validate the analytical model and evaluate the two fault diagnosis methods, using as fault features the parameters of the single-diode model or the main characteristics of the I–V curve. The results, based on field data under different temperatures and irradiances, show that the degradation of series and shunt resistances could be detected more accurately with the main characteristics rather than with the parameters. However, the estimated parameters could still be used to monitor the long-term degradation effects.

Suggested Citation

  • Vorachack Kongphet & Anne Migan-Dubois & Claude Delpha & Jean-Yves Lechenadec & Demba Diallo, 2022. "Low-Cost I–V Tracer for PV Fault Diagnosis Using Single-Diode Model Parameters and I–V Curve Characteristics," Energies, MDPI, vol. 15(15), pages 1-31, July.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:15:p:5350-:d:870077
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/15/5350/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/15/5350/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. 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.
    2. Isidoro Lillo-Bravo & Pablo González-Martínez & Miguel Larrañeta & José Guasumba-Codena, 2018. "Impact of Energy Losses Due to Failures on Photovoltaic Plant Energy Balance," Energies, MDPI, vol. 11(2), pages 1-23, February.
    Full references (including those not matched with items on IDEAS)

    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. Madi, Saida & Kheldoun, Aissa, 2017. "Bond graph based modeling for parameter identification of photovoltaic module," Energy, Elsevier, vol. 141(C), pages 1456-1465.
    2. 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.
    3. Jose-Maria Delgado-Sanchez & Isidoro Lillo-Bravo, 2020. "Influence of Degradation Processes in Lead–Acid Batteries on the Technoeconomic Analysis of Photovoltaic Systems," Energies, MDPI, vol. 13(16), pages 1-28, August.
    4. Tao, Yunkun & Bai, Jianbo & Pachauri, Rupendra Kumar & Wang, Yue & Li, Jian & Attaher, Harouna Kerzika, 2021. "Parameterizing mismatch loss in bifacial photovoltaic modules with global deployment: A comprehensive study," Applied Energy, Elsevier, vol. 303(C).
    5. 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.
    6. Efstratios Batzelis, 2019. "Non-Iterative Methods for the Extraction of the Single-Diode Model Parameters of Photovoltaic Modules: A Review and Comparative Assessment," Energies, MDPI, vol. 12(3), pages 1-26, January.
    7. Tamer Khatib & Dhiaa Halboot Muhsen, 2020. "Optimal Sizing of Standalone Photovoltaic System Using Improved Performance Model and Optimization Algorithm," Sustainability, MDPI, vol. 12(6), pages 1-18, March.
    8. Senturk, Ali, 2020. "Investigation of datasheet provided temperature coefficients of photovoltaic modules under various sky profiles at the field by applying a new validation procedure," Renewable Energy, Elsevier, vol. 152(C), pages 644-652.
    9. Carlos Toledo & Lucía Serrano-Lujan & Jose Abad & Antonio Lampitelli & Antonio Urbina, 2019. "Measurement of Thermal and Electrical Parameters in Photovoltaic Systems for Predictive and Cross-Correlated Monitorization," Energies, MDPI, vol. 12(4), pages 1-20, February.
    10. Nawal Rai & Amel Abbadi & Fethia Hamidia & Nadia Douifi & Bdereddin Abdul Samad & Khalid Yahya, 2023. "Biogeography-Based Teaching Learning-Based Optimization Algorithm for Identifying One-Diode, Two-Diode and Three-Diode Models of Photovoltaic Cell and Module," Mathematics, MDPI, vol. 11(8), pages 1-30, April.
    11. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    12. Guohong Lai & Guoping Zhang & Shaowu Li, 2024. "An MPPT Control Strategy Based on Current Constraint Relationships for a Photovoltaic System with a Battery or Supercapacitor," Energies, MDPI, vol. 17(16), pages 1-27, August.
    13. Tihomir Betti & Ante Kristić & Ivan Marasović & Vesna Pekić, 2024. "Accuracy of Simscape Solar Cell Block for Modeling a Partially Shaded Photovoltaic Module," Energies, MDPI, vol. 17(10), pages 1-19, May.
    14. Zhou, Junfeng & Zhang, Yanhui & Zhang, Yubo & Shang, Wen-Long & Yang, Zhile & Feng, Wei, 2022. "Parameters identification of photovoltaic models using a differential evolution algorithm based on elite and obsolete dynamic learning," Applied Energy, Elsevier, vol. 314(C).
    15. 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.
    16. Hugues Renaudineau & Pol Paradell-Solà & Lluís Trilla & Alber Filba-Martinez & David Cardoner & José Luis Domínguez-García, 2020. "Reliability Assessment of a Fault-Tolerant PV Multistring Inverter," Energies, MDPI, vol. 13(24), pages 1-13, December.
    17. Issa, Mohamed & Samn, Anas, 2022. "Passive vehicle suspension system optimization using Harris Hawk Optimization algorithm," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 191(C), pages 328-345.
    18. Li, Yuanliang & Ding, Kun & Zhang, Jingwei & Chen, Fudong & Chen, Xiang & Wu, Jiabing, 2019. "A fault diagnosis method for photovoltaic arrays based on fault parameters identification," Renewable Energy, Elsevier, vol. 143(C), pages 52-63.
    19. Hu, Mingke & Zhao, Bin & Li, Jing & Wang, Yunyun & Pei, Gang, 2017. "Preliminary thermal analysis of a combined photovoltaic–photothermic–nocturnal radiative cooling system," Energy, Elsevier, vol. 137(C), pages 419-430.
    20. Ryan M. Smith & Manjunath Matam & Hubert Seigneur, 2023. "Simulated Impact of Shortened Strings in Commercial and Utility-Scale Photovoltaic Arrays," Energies, MDPI, vol. 16(21), pages 1-15, October.

    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:gam:jeners:v:15:y:2022:i:15:p:5350-:d:870077. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.