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

Jun Zhang, Haifeng Bian, Huanhuan Zhao, Xuexue Wang, Linlin Zhang, Yiping Bai

INTERNATIONAL JOURNAL OF ENVIRONMENTAL RESEARCH AND PUBLIC HEALTH(2020)

Cited 14|Views14
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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.
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Key words
risk assessment,bayesian network (BN),bow-tie,power transmission line,single-phase grounding
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