IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v15y2022i21p8031-d956557.html

Evaluation, Analysis and Diagnosis for HVDC Transmission System Faults via Knowledge Graph under New Energy Systems Construction: A Critical Review

Author

Listed:
  • Jiyang Wu

    (CSG EHV Power Transmission Company of China Southern Power Grid Co., Ltd., Guangzhou 510000, China)

  • Qiang Li

    (CSG EHV Power Transmission Company of China Southern Power Grid Co., Ltd., Guangzhou 510000, China)

  • Qian Chen

    (CSG EHV Power Transmission Company of China Southern Power Grid Co., Ltd., Guangzhou 510000, China)

  • Guangqiang Peng

    (Maintenance and Test Center of CSG EHV Power Transmission Company of China Southern Power Grid Co., Ltd., Guangzhou 510663, China)

  • Jinyu Wang

    (CSG EHV Power Transmission Company of China Southern Power Grid Co., Ltd., Dali Bureau, Dali 671000, China)

  • Qiang Fu

    (CSG EHV Power Transmission Company of China Southern Power Grid Co., Ltd., Dali Bureau, Dali 671000, China)

  • Bo Yang

    (Faculty of Electric Power Engineering, Kunming University of Science and Technology, Kunming 650500, China)

Abstract

High voltage direct current (HVDC) transmission systems play a critical role to optimize resource allocation and stabilize power grid operation in the current power grid thanks to their asynchronous networking and large transmission capacity. To ensure the operation reliability of the power grid and reduce the outage time, it is imperative to realize fault diagnosis of HVDC transmission systems in a short time. Based on the prior research on fault diagnosis methods of HVDC systems, this work comprehensively summarizes and analyzes the existing fault diagnosis methods from three different angles: fault type, fault influence, and fault diagnosis. Meanwhile, with the construction of the digital power grid system, the type, quantity, and complexity of power equipment have considerably increased, thus, traditional fault diagnosis methods can basically no longer meet the development needs of the new power system. Artificial intelligence (AI) techniques can effectively simplify solutions’ complexity and enhance self-learning ability, which are ideal tools to solve this problem. Therefore, this work develops a knowledge graph technology-based fault diagnosis framework for HVDC transmission systems to remedy the aforementioned drawbacks, in which the detailed principle and mechanism are introduced, as well as its technical framework for intelligent fault diagnosis decision.

Suggested Citation

  • Jiyang Wu & Qiang Li & Qian Chen & Guangqiang Peng & Jinyu Wang & Qiang Fu & Bo Yang, 2022. "Evaluation, Analysis and Diagnosis for HVDC Transmission System Faults via Knowledge Graph under New Energy Systems Construction: A Critical Review," Energies, MDPI, vol. 15(21), pages 1-20, October.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:21:p:8031-:d:956557
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/15/21/8031/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/15/21/8031/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Li, Jianwei & Yang, Qingqing & Mu, Hao & Le Blond, Simon & He, Hongwen, 2018. "A new fault detection and fault location method for multi-terminal high voltage direct current of offshore wind farm," Applied Energy, Elsevier, vol. 220(C), pages 13-20.
    2. Shrestha, Anil & Mustafa, Andy Ali & Htike, Myo Myo & You, Vithyea & Kakinaka, Makoto, 2022. "Evolution of energy mix in emerging countries: Modern renewable energy, traditional renewable energy, and non-renewable energy," Renewable Energy, Elsevier, vol. 199(C), pages 419-432.
    3. Benasla, Mokhtar & Allaoui, Tayeb & Brahami, Mostefa & Denaï, Mouloud & Sood, Vijay K., 2018. "HVDC links between North Africa and Europe: Impacts and benefits on the dynamic performance of the European system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 3981-3991.
    4. Pierri, Erika & Binder, Ole & Hemdan, Nasser G.A. & Kurrat, Michael, 2017. "Challenges and opportunities for a European HVDC grid," Renewable and Sustainable Energy Reviews, Elsevier, vol. 70(C), pages 427-456.
    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. Chenchen Song & Zhiling Guo & Xiaoyue Ma & Jijiang He & Zhengguang Liu, 2025. "Evaluating the Role of Next-Generation Productive Forces in Mitigating Carbon Lock-In: Evidence from Regional Disparities in China," Sustainability, MDPI, vol. 17(9), pages 1-29, May.
    2. Qiang Li & Qian Chen & Jiyang Wu & Youqiang Qiu & Changhong Zhang & Yilong Huang & Jianbao Guo & Bo Yang, 2023. "XGBoost-Based Intelligent Decision Making of HVDC System with Knowledge Graph," Energies, MDPI, vol. 16(5), pages 1-21, March.
    3. Bing Liu & Jichong Lei & Jinsen Xie & Jianliang Zhou, 2022. "Development and Validation of a Nuclear Power Plant Fault Diagnosis System Based on Deep Learning," Energies, MDPI, vol. 15(22), pages 1-15, November.
    4. Bo Yang & Yulin Li & Wei Yao & Lin Jiang & Chuanke Zhang & Chao Duan & Yaxing Ren, 2023. "Optimization and Control of New Power Systems under the Dual Carbon Goals: Key Issues, Advanced Techniques, and Perspectives," Energies, MDPI, vol. 16(9), pages 1-4, May.

    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. Alassi, Abdulrahman & Bañales, Santiago & Ellabban, Omar & Adam, Grain & MacIver, Callum, 2019. "HVDC Transmission: Technology Review, Market Trends and Future Outlook," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 530-554.
    2. Nansheng Pang & Wenjing Guo, 2019. "Uncertain Hybrid Multiple Attribute Group Decision of Offshore Wind Power Transmission Mode Based on theVIKOR Method," Sustainability, MDPI, vol. 11(21), pages 1-21, November.
    3. Ardelean, Mircea & Minnebo, Philip, 2023. "The suitability of seas and shores for building submarine power interconnections," Renewable and Sustainable Energy Reviews, Elsevier, vol. 176(C).
    4. Tarek Abedin & M. Shahadat Hossain Lipu & Mahammad A. Hannan & Pin Jern Ker & Safwan A. Rahman & Chong Tak Yaw & Sieh K. Tiong & Kashem M. Muttaqi, 2021. "Dynamic Modeling of HVDC for Power System Stability Assessment: A Review, Issues, and Recommendations," Energies, MDPI, vol. 14(16), pages 1-25, August.
    5. Trivedi, Jatin & Chakraborty, Dipanwita & Nobanee, Haitham, 2023. "Modelling the growth dynamics of sustainable renewable energy – Flourishing green financing," Energy Policy, Elsevier, vol. 183(C).
    6. He, Jingting & Zou, Xuejun & Dong, Yuying & Ke, Jun & Ge, Hui & Chen, Dan & Cui, Yubo, 2026. "Construction of CoOx/tubular C3N4 Z-scheme heterojunction for synergistically enhanced photocatalytic hydrogen production," Renewable Energy, Elsevier, vol. 256(PE).
    7. Jiang, Sufan & Gao, Shan & Pan, Guangsheng & Zhao, Xin & Liu, Yu & Guo, Yasen & Wang, Sicheng, 2020. "A novel robust security constrained unit commitment model considering HVDC regulation," Applied Energy, Elsevier, vol. 278(C).
    8. Wang, Lili & Pang, Jun, 2025. "Assessing the impact of climate mitigation technology and environmental tax on renewable energy development: A dynamic threshold approach," Renewable Energy, Elsevier, vol. 244(C).
    9. Navid Bayati & Mehdi Savaghebi, 2021. "Protection Systems for DC Shipboard Microgrids," Energies, MDPI, vol. 14(17), pages 1-20, August.
    10. Yue Li & Muhammad Tayyab Sohail & Yanan Zhang & Sana Ullah, 2024. "Bioenergy for Sustainable Rural Development: Elevating Government Governance with Environmental Policy in China," Land, MDPI, vol. 13(12), pages 1-18, December.
    11. Ziyuan Liu & Junjing Tan & Wei Guo & Chong Fan & Wenhe Peng & Zhijian Fang & Jingke Gao, 2024. "Hierarchical Optimal Dispatching of Electric Vehicles Based on Photovoltaic-Storage Charging Stations," Mathematics, MDPI, vol. 12(21), pages 1-13, October.
    12. Silvestri, Luca & De Santis, Michele, 2024. "Renewable-based load shifting system for demand response to enhance energy-economic-environmental performance of industrial enterprises," Applied Energy, Elsevier, vol. 358(C).
    13. Sahebkar Farkhani, Jalal & Çelik, Özgür & Ma, Kaiqi & Bak, Claus Leth & Chen, Zhe, 2024. "A comprehensive review of potential protection methods for VSC multi-terminal HVDC systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 192(C).
    14. Song, Yuguang & Xia, Mingchao & Yang, Liu & Chen, Qifang & Su, Su, 2023. "Multi-granularity source-load-storage cooperative dispatch based on combined robust optimization and stochastic optimization for a highway service area micro-energy grid," Renewable Energy, Elsevier, vol. 205(C), pages 747-762.
    15. Mohamed Radwan & Sahar Pirooz Azad, 2022. "Protection of Multi-Terminal HVDC Grids: A Comprehensive Review," Energies, MDPI, vol. 15(24), pages 1-37, December.
    16. Liang, Jinping & Zhang, Ke & Al-Durra, Ahmed & Zhou, Daming, 2020. "A novel fault diagnostic method in power converters for wind power generation system," Applied Energy, Elsevier, vol. 266(C).
    17. Geovanna Bernardino Bello & Luana Beatriz Martins Valero Viana & Gregory Matheus Pereira de Moraes & Diogo Ferraz, 2025. "Renewable Energy Index: The Country-Group Performance Using Data Envelopment Analysis," Energies, MDPI, vol. 18(14), pages 1-27, July.
    18. Assareh, Ehsanolah & Mousavi Asl, Seyed Sajad & Agarwal, Neha & Ahmadinejad, Mehrdad & Ghodrat, Maryam & Lee, Moonyong, 2023. "New optimized configuration for a hybrid PVT solar/electrolyzer/absorption chiller system utilizing the response surface method as a machine learning technique and multi-objective optimization," Energy, Elsevier, vol. 281(C).
    19. Li, Xinzhe & Dong, Yufeng & Chang, Lu & Chen, Lifan & Wang, Guan & Zhuang, Yingping & Yan, Xuefeng, 2023. "Dynamic hybrid modeling of fuel ethanol fermentation process by integrating biomass concentration XGBoost model and kinetic parameter artificial neural network model into mechanism model," Renewable Energy, Elsevier, vol. 205(C), pages 574-582.
    20. Zuo, Yinhui & Sun, Yigao & Zhang, Luquan & Zhang, Chao & Wang, Yingchun & Jiang, Guangzheng & Wang, Xiaoguang & Zhang, Tao & Cui, Longqing, 2024. "Geothermal resource evaluation in the Sichuan Basin and suggestions for the development and utilization of abandoned oil and gas wells," Renewable Energy, Elsevier, vol. 225(C).

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:15:y:2022:i:21:p:8031-:d:956557. 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 The email address of this maintainer does not seem to be valid anymore. Please ask MDPI Indexing Manager to update the entry or send us the correct address (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.