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Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines

Author

Listed:
  • Jun Zhang

    (State Grid Energy Research Institute Co., Ltd., Beijing 102209, China)

  • Haifeng Bian

    (State Grid Energy Research Institute Co., Ltd., Beijing 102209, China)

  • Huanhuan Zhao

    (School of Emergency Management and Engineering, China University of Mining & Technology, Beijing 100083, China)

  • Xuexue Wang

    (School of Emergency Management and Engineering, China University of Mining & Technology, Beijing 100083, China)

  • Linlin Zhang

    (School of Emergency Management and Engineering, China University of Mining & Technology, Beijing 100083, China)

  • Yiping Bai

    (School of Emergency Management and Engineering, China University of Mining & Technology, Beijing 100083, China)

Abstract

With the increasing demand for electricity transmission and distribution, single-phase grounding accidents, which cause great economic losses and casualties, have occurred frequently. In this study, a Bayesian network (BN)-based risk assessment model for representing single-phase grounding accidents is proposed to examine accident evolution from causes to potential consequences. The Bayesian network of single-phase grounding accidents includes 21 nodes that take into account the influential factors of environment, management, equipment and human error. The Bow-tie method was employed to build the accident evolution path and then converted to a BN. The BN conditional probability tables are determined with reference to historical accident data and expert opinion obtained by the Delphi method. The probability of a single-phase grounding accident and its potential consequences in normal conditions and three typical accident scenarios are analyzed. We found that “Storm” is the most critical hazard of single-phase grounding, followed by “Aging” and “Icing”. This study could quantitatively evaluate the single-phase grounding accident in multi-hazard coupling scenarios and provide technical support for occupational health and safety management of power transmission lines.

Suggested Citation

  • Jun Zhang & Haifeng Bian & Huanhuan Zhao & Xuexue Wang & Linlin Zhang & Yiping Bai, 2020. "Bayesian Network-Based Risk Assessment of Single-Phase Grounding Accidents of Power Transmission Lines," IJERPH, MDPI, vol. 17(6), pages 1-17, March.
    • Handle: RePEc:gam:jijerp:v:17:y:2020:i:6:p:1841-:d:331685
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    References listed on IDEAS

    as
    1. Khakzad, Nima & Khan, Faisal & Amyotte, Paul, 2012. "Dynamic risk analysis using bow-tie approach," Reliability Engineering and System Safety, Elsevier, vol. 104(C), pages 36-44.
    2. Iamsumang, Chonlagarn & Mosleh, Ali & Modarres, Mohammad, 2018. "Monitoring and learning algorithms for dynamic hybrid Bayesian network in on-line system health management applications," Reliability Engineering and System Safety, Elsevier, vol. 178(C), pages 118-129.
    3. Belton, Ian & MacDonald, Alice & Wright, George & Hamlin, Iain, 2019. "Improving the practical application of the Delphi method in group-based judgment: A six-step prescription for a well-founded and defensible process," Technological Forecasting and Social Change, Elsevier, vol. 147(C), pages 72-82.
    4. Lina Han & Qing Ma & Feng Zhang & Yichen Zhang & Jiquan Zhang & Yongbin Bao & Jing Zhao, 2019. "Risk Assessment of An Earthquake-Collapse-Landslide Disaster Chain by Bayesian Network and Newmark Models," IJERPH, MDPI, vol. 16(18), pages 1-17, September.
    5. Vileiniskis, Marius & Remenyte-Prescott, Rasa, 2017. "Quantitative risk prognostics framework based on Petri Net and Bow-Tie models," Reliability Engineering and System Safety, Elsevier, vol. 165(C), pages 62-73.
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    Cited by:

    1. Yunmeng Lu & Tiantian Wang & Tiezhong Liu, 2020. "Bayesian Network-Based Risk Analysis of Chemical Plant Explosion Accidents," IJERPH, MDPI, vol. 17(15), pages 1-20, July.
    2. Jianbo He & Yao Zhou & Yilin Li & Guangqing Zhang & Jiayu Liang & Hao Shang & Wenjun Ning, 2023. "Characteristic Quantity Analysis of Single-Phase Contact Tree Ground Fault of Distribution Network Overhead Lines," Energies, MDPI, vol. 17(1), pages 1-15, December.
    3. Jeong-Hun Won & Hyeon-Ji Jeong & WonSeok Kim & Seungjun Kim & Sung-Yong Kang & Jong Moon Hwang, 2022. "Mechanisms Analysis for Fatal Accident Types Caused by Multiple Processes in the Workplace: Based on Accident Case in South Korea," IJERPH, MDPI, vol. 19(18), pages 1-23, September.
    4. Mei Liu & Boning Li & Hongjun Cui & Pin-Chao Liao & Yuecheng Huang, 2022. "Research Paradigm of Network Approaches in Construction Safety and Occupational Health," IJERPH, MDPI, vol. 19(19), pages 1-22, September.

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