IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2019i1p100-d301415.html
   My bibliography  Save this article

Analysis of Photovoltaic String Failure and Health Monitoring with Module Fault Identification

Author

Listed:
  • Ahmad Rivai

    (Higher Institution Centre of Excellence (HICoE), UM Power Energy Dedicated Advanced Centre (UMPEDAC) Level 4, Wisma R&D, University of Malaya, Kuala Lumpur 59990, Malaysia)

  • Nasrudin Abd Rahim

    (Higher Institution Centre of Excellence (HICoE), UM Power Energy Dedicated Advanced Centre (UMPEDAC) Level 4, Wisma R&D, University of Malaya, Kuala Lumpur 59990, Malaysia)

  • Mohamad Fathi Mohamad Elias

    (Higher Institution Centre of Excellence (HICoE), UM Power Energy Dedicated Advanced Centre (UMPEDAC) Level 4, Wisma R&D, University of Malaya, Kuala Lumpur 59990, Malaysia)

  • Jafferi Jamaludin

    (Higher Institution Centre of Excellence (HICoE), UM Power Energy Dedicated Advanced Centre (UMPEDAC) Level 4, Wisma R&D, University of Malaya, Kuala Lumpur 59990, Malaysia)

Abstract

In this paper, photovoltaic (PV) string failure analysis and health monitoring of PV modules based on a low-cost self-powered wireless sensor network (WSN) are presented. Simple and effective fault detection and diagnosis method based on the real-time operating voltage of PV modules is proposed. The proposed method is verified using the developed health monitoring system which is installed in a grid-connected PV system. Each of the PV modules is monitored via WSN to detect any individual faulty module. The analysis of PV string failure includes several electrical fault scenarios and their impact on the PV string characteristics. The results show that a degraded or faulty module exhibits low operating voltage as compared to the normal module. The developed health monitoring system also includes a graphical user interface (GUI) program which graphically displays the real-time operating voltage of each module with colors and thus helping users to identify the faulty modules easily. The faulty modules identification approach is further validated using the PV module electroluminescence (EL) imaging system.

Suggested Citation

  • Ahmad Rivai & Nasrudin Abd Rahim & Mohamad Fathi Mohamad Elias & Jafferi Jamaludin, 2019. "Analysis of Photovoltaic String Failure and Health Monitoring with Module Fault Identification," Energies, MDPI, vol. 13(1), pages 1-16, December.
  • Handle: RePEc:gam:jeners:v:13:y:2019:i:1:p:100-:d:301415
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/1/100/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/13/1/100/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    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. Harrou, Fouzi & Sun, Ying & Taghezouit, Bilal & Saidi, Ahmed & Hamlati, Mohamed-Elkarim, 2018. "Reliable fault detection and diagnosis of photovoltaic systems based on statistical monitoring approaches," Renewable Energy, Elsevier, vol. 116(PA), pages 22-37.
    3. Silvano Vergura, 2016. "A Complete and Simplified Datasheet-Based Model of PV Cells in Variable Environmental Conditions for Circuit Simulation," Energies, MDPI, vol. 9(5), pages 1-12, April.
    4. Triki-Lahiani, Asma & Bennani-Ben Abdelghani, Afef & Slama-Belkhodja, Ilhem, 2018. "Fault detection and monitoring systems for photovoltaic installations: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2680-2692.
    5. Tingting Pei & Xiaohong Hao, 2019. "A Fault Detection Method for Photovoltaic Systems Based on Voltage and Current Observation and Evaluation," Energies, MDPI, vol. 12(9), pages 1-16, May.
    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. Reda El Abbadi & Mohamed Aatabe & Allal El Moubarek Bouzid, 2024. "Wireless Diagnosis and Control of DC–DC Converter for Off-Grid Photovoltaic Systems," Sustainability, MDPI, vol. 16(8), pages 1-20, April.
    2. Mariusz T. Sarniak, 2020. "Researches of the Impact of the Nominal Power Ratio and Environmental Conditions on the Efficiency of the Photovoltaic System: A Case Study for Poland in Central Europe," Sustainability, MDPI, vol. 12(15), pages 1-15, July.
    3. de Jesus dos Santos Rodrigues, Marinaldo & Torres, Pedro Ferreira & Barros Galhardo, Marcos André & Chase, Otavio Andre & Monteiro, Weslley Leão & de Arimatéia Alves Vieira Filho, José & Mares, Fabríc, 2021. "A new methodology for the assessing of power losses in partially shaded SPV arrays," Energy, Elsevier, vol. 232(C).

    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. 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.
    2. Livera, Andreas & Theristis, Marios & Makrides, George & Georghiou, George E., 2019. "Recent advances in failure diagnosis techniques based on performance data analysis for grid-connected photovoltaic systems," Renewable Energy, Elsevier, vol. 133(C), pages 126-143.
    3. Rouani, Lahcene & Harkat, Mohamed Faouzi & Kouadri, Abdelmalek & Mekhilef, Saad, 2021. "Shading fault detection in a grid-connected PV system using vertices principal component analysis," Renewable Energy, Elsevier, vol. 164(C), pages 1527-1539.
    4. 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.
    5. Gomathy Balasubramani & Venkatesan Thangavelu & Muniraj Chinnusamy & Umashankar Subramaniam & Sanjeevikumar Padmanaban & Lucian Mihet-Popa, 2020. "Infrared Thermography Based Defects Testing of Solar Photovoltaic Panel with Fuzzy Rule-Based Evaluation," Energies, MDPI, vol. 13(6), pages 1-14, March.
    6. Li, Chenxi & Yang, Yongheng & Spataru, Sergiu & Zhang, Kanjian & Wei, Haikun, 2021. "A robust parametrization method of photovoltaic modules for enhancing one-diode model accuracy under varying operating conditions," Renewable Energy, Elsevier, vol. 168(C), pages 764-778.
    7. Sunme Park & Soyeong Park & Myungsun Kim & Euiseok Hwang, 2020. "Clustering-Based Self-Imputation of Unlabeled Fault Data in a Fleet of Photovoltaic Generation Systems," Energies, MDPI, vol. 13(3), pages 1-16, February.
    8. Saeedreza Jadidi & Hamed Badihi & Youmin Zhang, 2020. "Passive Fault-Tolerant Control Strategies for Power Converter in a Hybrid Microgrid," Energies, MDPI, vol. 13(21), pages 1-28, October.
    9. Nien-Che Yang & Harun Ismail, 2022. "Voting-Based Ensemble Learning Algorithm for Fault Detection in Photovoltaic Systems under Different Weather Conditions," Mathematics, MDPI, vol. 10(2), pages 1-18, January.
    10. Srivastava, Chetan & Tripathy, Manoj, 2021. "DC microgrid protection issues and schemes: A critical review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 151(C).
    11. Fabrizio Bonacina & Alessandro Corsini & Lucio Cardillo & Francesca Lucchetta, 2019. "Complex Network Analysis of Photovoltaic Plant Operations and Failure Modes," Energies, MDPI, vol. 12(10), pages 1-14, May.
    12. Zeb, Kamran & Islam, Saif Ul & Khan, Imran & Uddin, Waqar & Ishfaq, M. & Curi Busarello, Tiago Davi & Muyeen, S.M. & Ahmad, Iftikhar & Kim, H.J., 2022. "Faults and Fault Ride Through strategies for grid-connected photovoltaic system: A comprehensive review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 158(C).
    13. Høiaas, Ingeborg & Grujic, Katarina & Imenes, Anne Gerd & Burud, Ingunn & Olsen, Espen & Belbachir, Nabil, 2022. "Inspection and condition monitoring of large-scale photovoltaic power plants: A review of imaging technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 161(C).
    14. Bilal Taghezouit & Fouzi Harrou & Cherif Larbes & Ying Sun & Smail Semaoui & Amar Hadj Arab & Salim Bouchakour, 2022. "Intelligent Monitoring of Photovoltaic Systems via Simplicial Empirical Models and Performance Loss Rate Evaluation under LabVIEW: A Case Study," Energies, MDPI, vol. 15(21), pages 1-30, October.
    15. Jae-Sub Ko & Dae-Kyong Kim, 2021. "Localization of Disconnection Faults in PV Installations Using the Multiple Frequencies Injection Method," Energies, MDPI, vol. 14(21), pages 1-28, November.
    16. Mellit, Adel & Kalogirou, Soteris, 2021. "Artificial intelligence and internet of things to improve efficacy of diagnosis and remote sensing of solar photovoltaic systems: Challenges, recommendations and future directions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    17. Wang, Haizheng & Zhao, Jian & Sun, Qian & Zhu, Honglu, 2019. "Probability modeling for PV array output interval and its application in fault diagnosis," Energy, Elsevier, vol. 189(C).
    18. Silvano Vergura, 2018. "Hypothesis Tests-Based Analysis for Anomaly Detection in Photovoltaic Systems in the Absence of Environmental Parameters," Energies, MDPI, vol. 11(3), pages 1-18, February.
    19. 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).
    20. Peinado Gonzalo, Alfredo & Pliego Marugán, Alberto & García Márquez, Fausto Pedro, 2020. "Survey of maintenance management for photovoltaic power systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 134(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:gam:jeners:v:13:y:2019:i:1:p:100-:d:301415. 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.