IDEAS home Printed from https://ideas.repec.org/a/oup/ijlctc/v18y2023ip659-674..html
   My bibliography  Save this article

Detection, location, and diagnosis of different faults in large solar PV system—a review

Author

Listed:
  • G R Venkatakrishnan
  • R Rengaraj
  • S Tamilselvi
  • J Harshini
  • Ansheela Sahoo
  • C Ahamed Saleel
  • Mohamed Abbas
  • Erdem Cuce
  • C Jazlyn
  • Saboor Shaik
  • Pinar Mert Cuce
  • Saffa Riffat

Abstract

Over the past decade, the significance of solar photovoltaic (PV) system has played a major role due to the rapid growth in the solar PV industry. Reliability, efficiency and safety of solar PV systems can be enhanced by continuous monitoring of the system and detecting the faults if any as early as possible. Reduced real time power generation and reduced life span of the solar PV system are the results if the fault in solar PV system is found undetected. Therefore, it is mandatory to identify and locate the type of fault occurring in a solar PV system. The faults occurring in the solar PV system are classified as follows: physical, environmental, and electrical faults that are further classified into different types as described in this paper. Once a fault is located and detected, an appropriate diagnosis method needs to be used to rectify it. In this paper, a comprehensive review of diverse fault diagnosis techniques reported in various literature is listed and described. This paper helps the researchers to get an awareness of the various faults occurring in a solar PV system and enables them to choose a suitable diagnosis technique based on its performance metrics to rectify the fault occurring in solar PV systems.

Suggested Citation

  • G R Venkatakrishnan & R Rengaraj & S Tamilselvi & J Harshini & Ansheela Sahoo & C Ahamed Saleel & Mohamed Abbas & Erdem Cuce & C Jazlyn & Saboor Shaik & Pinar Mert Cuce & Saffa Riffat, 2023. "Detection, location, and diagnosis of different faults in large solar PV system—a review," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 18, pages 659-674.
    • Handle: RePEc:oup:ijlctc:v:18:y:2023:i::p:659-674.
    as

    Download full text from publisher

    File URL: http://hdl.handle.net/10.1093/ijlct/ctad018
    Download Restriction: Access to full text is restricted to subscribers.
    ---><---

    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. Rico Espinosa, Alejandro & Bressan, Michael & Giraldo, Luis Felipe, 2020. "Failure signature classification in solar photovoltaic plants using RGB images and convolutional neural networks," Renewable Energy, Elsevier, vol. 162(C), pages 249-256.
    2. Mercure, Jean-François & Salas, Pablo, 2012. "An assessement of global energy resource economic potentials," Energy, Elsevier, vol. 46(1), pages 322-336.
    3. Cuce, Erdem & Cuce, Pinar Mert & Young, Chin-Huai, 2016. "Energy saving potential of heat insulation solar glass: Key results from laboratory and in-situ testing," Energy, Elsevier, vol. 97(C), pages 369-380.
    4. Erdem Cuce & Saffa B. Riffat, 2017. "A smart building material for low/zero carbon applications: heat insulation solar glass—characteristic results from laboratory and in situ tests," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 12(2), pages 126-135.
    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. Chen, Yen-Hsiang & Shih, Fu-Yuan & Lee, Ming-Tsang & Lee, Yung-Chun & Chen, Yu-Bin, 2020. "Development of lightweight energy-saving glass and its near-field electromagnetic analysis," Energy, Elsevier, vol. 193(C).
    2. Kamjoo, Azadeh & Maheri, Alireza & Putrus, Ghanim A., 2014. "Chance constrained programming using non-Gaussian joint distribution function in design of standalone hybrid renewable energy systems," Energy, Elsevier, vol. 66(C), pages 677-688.
    3. Michalis Michael & Fabio Favoino & Qian Jin & Alessandra Luna-Navarro & Mauro Overend, 2023. "A Systematic Review and Classification of Glazing Technologies for Building Façades," Energies, MDPI, vol. 16(14), pages 1-47, July.
    4. Meng Xiao & Bo Yang & Shilong Wang & Yongsheng Chang & Song Li & Gang Yi, 2023. "Research on recognition methods of spot-welding surface appearances based on transfer learning and a lightweight high-precision convolutional neural network," Journal of Intelligent Manufacturing, Springer, vol. 34(5), pages 2153-2170, June.
    5. Cheng Yang & Fuhao Sun & Yujie Zou & Zhipeng Lv & Liang Xue & Chao Jiang & Shuangyu Liu & Bochao Zhao & Haoyang Cui, 2024. "A Survey of Photovoltaic Panel Overlay and Fault Detection Methods," Energies, MDPI, vol. 17(4), pages 1-37, February.
    6. Sairam, Seshapalli & Seshadhri, Subathra & Marafioti, Giancarlo & Srinivasan, Seshadhri & Mathisen, Geir & Bekiroglu, Korkut, 2022. "Edge-based Explainable Fault Detection Systems for photovoltaic panels on edge nodes," Renewable Energy, Elsevier, vol. 185(C), pages 1425-1440.
    7. Castellini, Marta & Menoncin, Francesco & Moretto, Michele & Vergalli, Sergio, 2021. "Photovoltaic Smart Grids in the prosumers investment decisions: a real option model," Journal of Economic Dynamics and Control, Elsevier, vol. 126(C).
    8. Cuce, Erdem, 2016. "Toward multi-functional PV glazing technologies in low/zero carbon buildings: Heat insulation solar glass – Latest developments and future prospects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1286-1301.
    9. Bertolini, Marina & D’Alpaos, Chiara & Moretto, Michele, 2016. "Investing in Photovoltaics: Timing, Plant Sizing and Smart Grids Flexibility," MITP: Mitigation, Innovation and Transformation Pathways 244540, Fondazione Eni Enrico Mattei (FEEM).
    10. Sijm, Jos & Lehmann, Paul & Chewpreecha, Unnada & Gawel, Erik & Mercure, Jean-Francois & Pollitt, Hector & Strunz, Sebastian, 2014. "EU climate and energy policy beyond 2020: Are additional targets and instruments for renewables economically reasonable?," UFZ Discussion Papers 3/2014, Helmholtz Centre for Environmental Research (UFZ), Division of Social Sciences (ÖKUS).
    11. Mercure, J.-F. & Pollitt, H. & Chewpreecha, U. & Salas, P. & Foley, A.M. & Holden, P.B. & Edwards, N.R., 2014. "The dynamics of technology diffusion and the impacts of climate policy instruments in the decarbonisation of the global electricity sector," Energy Policy, Elsevier, vol. 73(C), pages 686-700.
    12. Mercure, Jean-François & Salas, Pablo, 2013. "On the global economic potentials and marginal costs of non-renewable resources and the price of energy commodities," Energy Policy, Elsevier, vol. 63(C), pages 469-483.
    13. Castellini, Marta & Di Corato, Luca & Moretto, Michele & Vergalli, Sergio, 2021. "Energy exchange among heterogeneous prosumers under price uncertainty," Energy Economics, Elsevier, vol. 104(C).
    14. Gopinath Subramani & Vigna K. Ramachandaramurthy & Sanjeevikumar Padmanaban & Lucian Mihet-Popa & Frede Blaabjerg & Josep M. Guerrero, 2017. "Grid-Tied Photovoltaic and Battery Storage Systems with Malaysian Electricity Tariff—A Review on Maximum Demand Shaving," Energies, MDPI, vol. 10(11), pages 1-17, November.
    15. Narvaez, Gabriel & Giraldo, Luis Felipe & Bressan, Michael & Pantoja, Andres, 2021. "Machine learning for site-adaptation and solar radiation forecasting," Renewable Energy, Elsevier, vol. 167(C), pages 333-342.
    16. Lancker, Kira & Quaas, Martin F., 2019. "Increasing marginal costs and the efficiency of differentiated feed-in tariffs," Energy Economics, Elsevier, vol. 83(C), pages 104-118.
    17. Miranda, Nicole D. & Renaldi, Renaldi & Khosla, Radhika & McCulloch, Malcolm D., 2021. "Bibliometric analysis and landscape of actors in passive cooling research," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    18. Kästel, Peter & Gilroy-Scott, Bryce, 2015. "Economics of pooling small local electricity prosumers—LCOE & self-consumption," Renewable and Sustainable Energy Reviews, Elsevier, vol. 51(C), pages 718-729.
    19. Sun, Yanyi & Shanks, Katie & Baig, Hasan & Zhang, Wei & Hao, Xia & Li, Yongxue & He, Bo & Wilson, Robin & Liu, Hao & Sundaram, Senthilarasu & Zhang, Jingquan & Xie, Lingzhi & Mallick, Tapas & Wu, Yupe, 2018. "Integrated semi-transparent cadmium telluride photovoltaic glazing into windows: Energy and daylight performance for different architecture designs," Applied Energy, Elsevier, vol. 231(C), pages 972-984.
    20. Langer, Jannis & Quist, Jaco & Blok, Kornelis, 2020. "Recent progress in the economics of ocean thermal energy conversion: Critical review and research agenda," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).

    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:oup:ijlctc:v:18:y:2023:i::p:659-674.. 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: Oxford University Press (email available below). General contact details of provider: https://academic.oup.com/ijlct .

    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.