IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i11p2450-d1398698.html
   My bibliography  Save this article

Progress of Photovoltaic DC Fault Arc Detection Based on VOSviewer Bibliometric Analysis

Author

Listed:
  • Lei Song

    (Marketing Service Center of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 311152, China)

  • Chunguang Lu

    (Marketing Service Center of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 311152, China)

  • Chen Li

    (Marketing Service Center of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 311152, China)

  • Yongjin Xu

    (Marketing Service Center of State Grid Zhejiang Electric Power Co., Ltd., Hangzhou 311152, China)

  • Lin Liu

    (State Grid Hangzhou Xiaoshan District Power Supply Company, Hangzhou 311200, China)

  • Xianbo Wang

    (Hainan Institute of Zhejiang University, Sanya 572025, China)

Abstract

This paper presents a review of research progress on photovoltaic direct current arc detection based on VOSviewer bibliometric analysis. This study begins by introducing the basic concept and hazards of photovoltaic DC arcing faults, followed by a summary of commonly used arc detection techniques. Utilizing VOSviewer, the relevant literature is subjected to clustering and visualization analysis, offering insights into research hotspots, trends, and interconnections among different fields. Based on the bibliometric analysis method of VOSviewer software, this paper analyzes the articles published in the last 10 years (2014–2023) on photovoltaic DC fault diagnosis. We analyzed the specific characteristics of 2195 articles on arc failures, including year of publication, author, institution, country, references, and keywords. This study reveals the development trend, global cooperation model, basic knowledge, research hotspots, and emerging frontier of PV DC arc. Future research directions and development trends for photovoltaic DC arc detection are proposed which provides valuable references for further studies and applications in this domain. This comprehensive analysis indicates that photovoltaic DC arc detection technology is expected to find broader applications and greater promotion in the future.

Suggested Citation

  • Lei Song & Chunguang Lu & Chen Li & Yongjin Xu & Lin Liu & Xianbo Wang, 2024. "Progress of Photovoltaic DC Fault Arc Detection Based on VOSviewer Bibliometric Analysis," Energies, MDPI, vol. 17(11), pages 1-17, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2450-:d:1398698
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/11/2450/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/11/2450/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Juan D. Velásquez & Lorena Cadavid & Carlos J. Franco, 2023. "Intelligence Techniques in Sustainable Energy: Analysis of a Decade of Advances," Energies, MDPI, vol. 16(19), pages 1-45, October.
    2. Tuhibur Rahman & Ahmed Al Mansur & Molla Shahadat Hossain Lipu & Md. Siddikur Rahman & Ratil H. Ashique & Mohamad Abou Houran & Rajvikram Madurai Elavarasan & Eklas Hossain, 2023. "Investigation of Degradation of Solar Photovoltaics: A Review of Aging Factors, Impacts, and Future Directions toward Sustainable Energy Management," Energies, MDPI, vol. 16(9), pages 1-30, April.
    3. 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.
    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. 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 & 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.
    3. Ahmed Al Mansur & Md. Ruhul Amin & Molla Shahadat Hossain Lipu & Md. Imamul Islam & Ratil H. Ashique & Zubaeer Bin Shams & Mohammad Asif ul Haq & Md. Hasan Maruf & ASM Shihavuddin, 2023. "The Effects of Non-Uniformly-Aged Photovoltaic Array on Mismatch Power Loss: A Practical Investigation towards Novel Hybrid Array Configurations," Sustainability, MDPI, vol. 15(17), pages 1-17, September.
    4. Zahid Javid & Ilhan Kocar & William Holderbaum & Ulas Karaagac, 2024. "Future Distribution Networks: A Review," Energies, MDPI, vol. 17(8), pages 1-45, April.
    5. Farizal Farizal & Muhammad Aqil Noviandri & Hanif Hamdani, 2024. "Sustainability Development through a Nearly Zero Energy Building Implementation Case: An Office Building in South Jakarta," Sustainability, MDPI, vol. 16(16), pages 1-21, August.
    6. Nándor Bozsik & András Szeberényi & Norbert Bozsik, 2024. "Impact of Climate Change on Electric Energy Production from Medium-Size Photovoltaic Module Systems Based on RCP Climate Scenarios," Energies, MDPI, vol. 17(16), pages 1-32, August.
    7. 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.
    8. 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.
    9. 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.
    10. 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).
    11. 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.
    12. Xu, Wenqiang & Wu, Xiaogang & Li, Yalun & Wang, Hewu & Lu, Languang & Ouyang, Minggao, 2023. "A comprehensive review of DC arc faults and their mechanisms, detection, early warning strategies, and protection in battery systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 186(C).
    13. Mina Akhter & Ahmed Al Mansur & Md. Imamul Islam & M. S. Hossain Lipu & Tahia F. Karim & Maher G. M. Abdolrasol & Thamer A. H. Alghamdi, 2024. "Sustainable Strategies for Crystalline Solar Cell Recycling: A Review on Recycling Techniques, Companies, and Environmental Impact Analysis," Sustainability, MDPI, vol. 16(13), pages 1-24, July.
    14. 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.
    15. Fatimah Ameen & Abdulrahman Siddiq & Attila Trohák & Rabab Benotsmane, 2023. "A Scalable Hierarchical Dynamic PV Array Reconfiguration under Partial Shading," Energies, MDPI, vol. 17(1), pages 1-20, December.

    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:17:y:2024:i:11:p:2450-:d:1398698. 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.