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A comprehensive review on DC arc faults and their diagnosis methods in photovoltaic systems

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  • Lu, Shibo
  • Phung, B.T.
  • Zhang, Daming

Abstract

Integration of renewable energy including solar energy is growing faster than ever before. Solar energy supplies more than 1.3% of global power, and it is predicted to become the largest electricity source by 2050 with about 11% of global power consumption. However, the improper installation, non-frequently scheduled maintenance, and aging effect can accelerate the deterioration of PV system components, which directly increase the possibility of arc fault occurrence. The undetected arc faults pose a severe fire hazard to residential, commercial, and utility-scaled PV systems. To deliver electricity in a safe and reliable manner, such a dangerous event must be detected at early stage. This paper presents a comprehensive review of the-state-of-art techniques for DC arc faults detection in photovoltaic systems (PV). Different methods and the features used for detection are discussed and compared in detail. This paper also emphasizes the importance of DC arc fault simulation for characteristics study and fault diagnosis purpose. Several DC arc fault models have been reviewed and compared.

Suggested Citation

  • Lu, Shibo & Phung, B.T. & Zhang, Daming, 2018. "A comprehensive review on DC arc faults and their diagnosis methods in photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 89(C), pages 88-98.
    • Handle: RePEc:eee:rensus:v:89:y:2018:i:c:p:88-98
    DOI: 10.1016/j.rser.2018.03.010
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    References listed on IDEAS

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    1. Cotfas, D.T. & Cotfas, P.A. & Kaplanis, S., 2016. "Methods and techniques to determine the dynamic parameters of solar cells: Review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 61(C), pages 213-221.
    2. 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.
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    Cited by:

    1. Yao Wang & Cuiyan Bai & Xiaopeng Qian & Wanting Liu & Chen Zhu & Leijiao Ge, 2022. "A DC Series Arc Fault Detection Method Based on a Lightweight Convolutional Neural Network Used in Photovoltaic System," Energies, MDPI, vol. 15(8), pages 1-20, April.
    2. Lina Wang & Hongcheng Qiu & Pu Yang & Longhua Mu, 2021. "Arc Fault Detection Algorithm Based on Variational Mode Decomposition and Improved Multi-Scale Fuzzy Entropy," Energies, MDPI, vol. 14(14), pages 1-16, July.
    3. Teng Li & Zhijie Jiao & Lina Wang & Yong Mu, 2020. "A Method of DC Arc Detection in All-Electric Aircraft," Energies, MDPI, vol. 13(16), pages 1-14, August.
    4. 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).
    5. Khairul Eahsun Fahim & Liyanage C. De Silva & Fayaz Hussain & Hayati Yassin, 2023. "A State-of-the-Art Review on Optimization Methods and Techniques for Economic Load Dispatch with Photovoltaic Systems: Progress, Challenges, and Recommendations," Sustainability, MDPI, vol. 15(15), pages 1-29, August.
    6. Yaseen Ahmed Mohammed Alsumaidaee & Chong Tak Yaw & Siaw Paw Koh & Sieh Kiong Tiong & Chai Phing Chen & Kharudin Ali, 2022. "Review of Medium-Voltage Switchgear Fault Detection in a Condition-Based Monitoring System by Using Deep Learning," Energies, MDPI, vol. 15(18), pages 1-34, September.
    7. Arturo Y. Jaen-Cuellar & David A. Elvira-Ortiz & Roque A. Osornio-Rios & Jose A. Antonino-Daviu, 2022. "Advances in Fault Condition Monitoring for Solar Photovoltaic and Wind Turbine Energy Generation: A Review," Energies, MDPI, vol. 15(15), pages 1-36, July.
    8. Lina Wang & Ehtisham Lodhi & Pu Yang & Hongcheng Qiu & Waheed Ur Rehman & Zeeshan Lodhi & Tariku Sinshaw Tamir & M. Adil Khan, 2022. "Adaptive Local Mean Decomposition and Multiscale-Fuzzy Entropy-Based Algorithms for the Detection of DC Series Arc Faults in PV Systems," Energies, MDPI, vol. 15(10), pages 1-16, May.

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