IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i23p4547-d292176.html
   My bibliography  Save this article

Detection of Typical Defects in Silicon Photovoltaic Modules and Application for Plants with Distributed MPPT Configuration

Author

Listed:
  • Jawad Ahmad

    (Energy Department, Politecnico di Torino, corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Alessandro Ciocia

    (Energy Department, Politecnico di Torino, corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Stefania Fichera

    (Energy Department, Politecnico di Torino, corso Duca degli Abruzzi 24, 10129 Torino, Italy)

  • Ali Faisal Murtaza

    (Department of Electrical Engineering, University of Central Punjab, Lahore 54590, Pakistan)

  • Filippo Spertino

    (Energy Department, Politecnico di Torino, corso Duca degli Abruzzi 24, 10129 Torino, Italy)

Abstract

During their operational life, photovoltaic (PV) modules may exhibit various defects for poor sorting of electrical performance during manufacturing, mishandling during transportation and installation, and severe thermo-mechanical stresses. Electroluminescence testing and infrared thermographic imaging are the most common tests for checking these defects, but they are only economically viable for large PV plants. The defects are also manifested as abnormal electrical properties of the affected PV modules. For defect diagnosis, the appropriate parameters on their I-V curves are open circuit voltage, photo-generated current, series resistance, and the shunt resistance. The health of PV modules can be assessed by calculating these values and comparing them with the reference parameters. If these defects are diagnosed in time, the power loss is avoided and safety hazards are mitigated. This paper first presents a review of common defects in PV modules and then a review of the methods used to find the above-mentioned parameters during the normal PV operation. A simple approach to determine the resistances of the equivalent circuit is discussed. Finally, through a modification in an ordinary maximum power point tracking (MPPT) algorithm, information about the state of health of PV modules is obtained. This method is effective, especially if applied to submodule-integrated MPPT architectures.

Suggested Citation

  • Jawad Ahmad & Alessandro Ciocia & Stefania Fichera & Ali Faisal Murtaza & Filippo Spertino, 2019. "Detection of Typical Defects in Silicon Photovoltaic Modules and Application for Plants with Distributed MPPT Configuration," Energies, MDPI, vol. 12(23), pages 1-26, November.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:23:p:4547-:d:292176
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/23/4547/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/23/4547/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Jen-Cheng & Shieh, Jyh-Cherng & Su, Yu-Li & Kuo, Kun-Chang & Chang, Yen-Wei & Liang, Yu-Ting & Chou, Jui-Jen & Liao, Kuo-Chi & Jiang, Joe-Air, 2011. "A novel method for the determination of dynamic resistance for photovoltaic modules," Energy, Elsevier, vol. 36(10), pages 5968-5974.
    2. Rashid, Khalid & Safdarnejad, Seyed Mostafa & Ellingwood, Kevin & Powell, Kody M., 2019. "Techno-economic evaluation of different hybridization schemes for a solar thermal/gas power plant," Energy, Elsevier, vol. 181(C), pages 91-106.
    3. Djordjevic, Sinisa & Parlevliet, David & Jennings, Philip, 2014. "Detectable faults on recently installed solar modules in Western Australia," Renewable Energy, Elsevier, vol. 67(C), pages 215-221.
    4. Tsanakas, John A. & Ha, Long & Buerhop, Claudia, 2016. "Faults and infrared thermographic diagnosis in operating c-Si photovoltaic modules: A review of research and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 62(C), pages 695-709.
    5. Khan, O. & Xiao, W., 2017. "Review and qualitative analysis of submodule-level distributed power electronic solutions in PV power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 76(C), pages 516-528.
    6. Orioli, Aldo & Di Gangi, Alessandra, 2013. "A procedure to calculate the five-parameter model of crystalline silicon photovoltaic modules on the basis of the tabular performance data," Applied Energy, Elsevier, vol. 102(C), pages 1160-1177.
    7. Ikkurti, Hanumath Prasad & Saha, Suman, 2015. "A comprehensive techno-economic review of microinverters for Building Integrated Photovoltaics (BIPV)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 47(C), pages 997-1006.
    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. Antonio D’Angola & Diana Enescu & Marianna Mecca & Alessandro Ciocia & Paolo Di Leo & Giovanni Vincenzo Fracastoro & Filippo Spertino, 2020. "Theoretical and Numerical Study of a Photovoltaic System with Active Fluid Cooling by a Fully-Coupled 3D Thermal and Electric Model," Energies, MDPI, vol. 13(4), pages 1-17, February.
    2. Rahman, Md Momtazur & Khan, Imran & Alameh, Kamal, 2021. "Potential measurement techniques for photovoltaic module failure diagnosis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    3. Michelle Kitayama da Silva & Mehreen Saleem Gul & Hassam Chaudhry, 2021. "Review on the Sources of Power Loss in Monofacial and Bifacial Photovoltaic Technologies," Energies, MDPI, vol. 14(23), pages 1-29, November.

    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. Mellit, A. & Tina, G.M. & Kalogirou, S.A., 2018. "Fault detection and diagnosis methods for photovoltaic systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 91(C), pages 1-17.
    2. Tamás Orosz & Anton Rassõlkin & Pedro Arsénio & Peter Poór & Daniil Valme & Ádám Sleisz, 2024. "Current Challenges in Operation, Performance, and Maintenance of Photovoltaic Panels," Energies, MDPI, vol. 17(6), pages 1-22, March.
    3. Rahman, Md Momtazur & Khan, Imran & Alameh, Kamal, 2021. "Potential measurement techniques for photovoltaic module failure diagnosis: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    4. Bouaichi, Abdellatif & Alami Merrouni, Ahmed & Hajjaj, Charaf & Messaoudi, Choukri & Ghennioui, Abdellatif & Benlarabi, Ahmed & Ikken, Badr & El Amrani, Aumeur & Zitouni, Houssin, 2019. "In-situ evaluation of the early PV module degradation of various technologies under harsh climatic conditions: The case of Morocco," Renewable Energy, Elsevier, vol. 143(C), pages 1500-1518.
    5. Waqar Akram, M. & Li, Guiqiang & Jin, Yi & Chen, Xiao, 2022. "Failures of Photovoltaic modules and their Detection: A Review," Applied Energy, Elsevier, vol. 313(C).
    6. Deihimi, M.H. & Naghizadeh, R.A. & Meyabadi, A. Fattahi, 2016. "Systematic derivation of parameters of one exponential model for photovoltaic modules using numerical information of data sheet," Renewable Energy, Elsevier, vol. 87(P1), pages 676-685.
    7. Segovia Ramírez, Isaac & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2022. "A novel approach to optimize the positioning and measurement parameters in photovoltaic aerial inspections," Renewable Energy, Elsevier, vol. 187(C), pages 371-389.
    8. Jose-María Sierra-Fernández & Sarah Rönnberg & Juan-José González de la Rosa & Math H. J. Bollen & José-Carlos Palomares-Salas, 2019. "Application of Spectral Kurtosis to Characterize Amplitude Variability in Power Systems’ Harmonics," Energies, MDPI, vol. 12(1), pages 1-15, January.
    9. Chiwu Bu & Tao Liu & Tao Wang & Hai Zhang & Stefano Sfarra, 2023. "A CNN-Architecture-Based Photovoltaic Cell Fault Classification Method Using Thermographic Images," Energies, MDPI, vol. 16(9), pages 1-13, April.
    10. Shi, Nan & Lv, Yanling & Zhang, Yuchen & Zhu, Xianhui, 2023. "Linear fitting Rule of I–V characteristics of thin-film cells based on Bezier function," Energy, Elsevier, vol. 278(PB).
    11. Zhang, Minhui & Zhang, Qin & Zhou, Dequn & Wang, Lei, 2021. "Punishment or reward? Strategies of stakeholders in the quality of photovoltaic plants based on evolutionary game analysis in China," Energy, Elsevier, vol. 220(C).
    12. Yu, Kunjie & Liang, J.J. & Qu, B.Y. & Cheng, Zhiping & Wang, Heshan, 2018. "Multiple learning backtracking search algorithm for estimating parameters of photovoltaic models," Applied Energy, Elsevier, vol. 226(C), pages 408-422.
    13. 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.
    14. Madi, Saida & Kheldoun, Aissa, 2017. "Bond graph based modeling for parameter identification of photovoltaic module," Energy, Elsevier, vol. 141(C), pages 1456-1465.
    15. Kahoul, Nabil & Chenni, Rachid & Cheghib, Hocine & Mekhilef, Saad, 2017. "Evaluating the reliability of crystalline silicon photovoltaic modules in harsh environment," Renewable Energy, Elsevier, vol. 109(C), pages 66-72.
    16. Singh, Rashmi & Sharma, Madhu & Rawat, Rahul & Banerjee, Chandan, 2020. "Field Analysis of three different silicon-based Technologies in Composite Climate Condition – Part II – Seasonal assessment and performance degradation rates using statistical tools," Renewable Energy, Elsevier, vol. 147(P1), pages 2102-2117.
    17. Peharz, Gerhard & Ulm, Andreas, 2018. "Quantifying the influence of colors on the performance of c-Si photovoltaic devices," Renewable Energy, Elsevier, vol. 129(PA), pages 299-308.
    18. 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.
    19. 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.
    20. Kolesnik, Sergei & Sitbon, Moshe & Gadelovits, Shlomo & Suntio, Teuvo & Kuperman, Alon, 2015. "Interfacing renewable energy sources for maximum power transfer—Part II: Dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 1771-1783.

    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:12:y:2019:i:23:p:4547-:d:292176. 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.