Risk analysis of tripping accidents of power grid caused by typical natural hazards based on FTA-BN model

As the scale of the power grid becomes larger, the requirements for transmission reliability are getting higher. Due to the large geographical span and the harsh environment of the power transmission line, it has become the most severely affected equipment of the power grid by natural factors. However, the quantitative assessment of transmission line tripping accidents caused by multiple natural hazards has rarely been investigated. In this study, a risk analysis method to probabilistically analyze the tripping accidents of power transmission lines caused by wildfire, lightning, strong wind and ice storm was proposed. The analysis process consists of comprehensively identifying the risk of tripping accidents based on fault tree analysis and dynamically performing the predictive analysis of tripping accident evolution process in transmission line from causes to consequences based on Bayesian network. Critical risk evolution paths corresponding to four natural hazards are determined through a 72-node BN. The source risks of the four critical risk evolution paths are artificial ignition source from the wildfire path, aging from the lightning path, thoughtless of surrounding environment from the strong wind path and wind effect from the ice storm path. The countermeasures of tripping accidents are derived through the source risks and synergy between risks in three scenario analysis. This study is expected to examine the key challenges of risk management in power grid tripping accidents, which provides technical supports for accident preventing, handling and recovering of tripping accidents of the power transmission line according to scenario-response-based hazard response strategy.

Automated summary

With the expansion of the power grid, the requirements for transmission reliability are increasing. This study proposes a risk analysis method to probabilistically analyze transmission line tripping accidents caused by various natural hazards, providing technical support for accident prevention, handling, and recovery in the power grid.