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基于贝叶斯网络的输电线路单相接地事故风险评估

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

机构信息

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

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

出版信息

Int J Environ Res Public Health. 2020 Mar 12;17(6):1841. doi: 10.3390/ijerph17061841.

DOI:10.3390/ijerph17061841
PMID:32178361
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC7142559/
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.

摘要

随着电力输配电需求的不断增加，单相接地事故频繁发生，造成了巨大的经济损失和人员伤亡。本研究提出了一种基于贝叶斯网络（BN）的单相接地事故风险评估模型，用于从事故原因到潜在后果的角度来研究事故的演变过程。单相接地事故的贝叶斯网络包含 21 个节点，考虑了环境、管理、设备和人为错误等影响因素。采用蝴蝶结法（Bow-tie method）构建了事故演化路径，并将其转换为贝叶斯网络。贝叶斯网络条件概率表参考了历史事故数据和通过德尔菲法获得的专家意见来确定。分析了正常情况下和三种典型事故场景下单相接地事故的发生概率及其潜在后果。研究结果表明，“风暴”是单相接地事故最关键的危害因素，其次是“老化”和“结冰”。本研究可以对多危害因素耦合场景下的单相接地事故进行定量评估，为输电线路职业健康和安全管理提供技术支持。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/5c46a7252eac/ijerph-17-01841-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/9309e42d915d/ijerph-17-01841-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/df80a4d19eb1/ijerph-17-01841-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/d4e4742f3a32/ijerph-17-01841-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/87225a80eb31/ijerph-17-01841-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/b0102b237f10/ijerph-17-01841-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/1597b66a3612/ijerph-17-01841-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/d2ca46998ce8/ijerph-17-01841-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/5049b3142262/ijerph-17-01841-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/cdb68cac613b/ijerph-17-01841-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/521ac05b31b0/ijerph-17-01841-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/d54e6d79916e/ijerph-17-01841-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/02801e309361/ijerph-17-01841-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/0f455741bcc9/ijerph-17-01841-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/5c46a7252eac/ijerph-17-01841-g014.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/9309e42d915d/ijerph-17-01841-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/df80a4d19eb1/ijerph-17-01841-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/d4e4742f3a32/ijerph-17-01841-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/87225a80eb31/ijerph-17-01841-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/b0102b237f10/ijerph-17-01841-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/1597b66a3612/ijerph-17-01841-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/d2ca46998ce8/ijerph-17-01841-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/5049b3142262/ijerph-17-01841-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/cdb68cac613b/ijerph-17-01841-g009.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/521ac05b31b0/ijerph-17-01841-g010.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/d54e6d79916e/ijerph-17-01841-g011.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/02801e309361/ijerph-17-01841-g012.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/0f455741bcc9/ijerph-17-01841-g013.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/2bcc/7142559/5c46a7252eac/ijerph-17-01841-g014.jpg

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