A flame combustion model-based wildfire-induced tripping risk assessment approach of transmission lines - Zhou, Enze; Wang, Lei; Wei, Ruizeng; Liu, Shuqing; Zhou, You (Frontiers in Energy Research, 2024)
With the escalating global climate change, the frequency of wildfires has significantly increased, posing a heightened emergency. Accurately predicting the tripping failures of transmission lines caused by wildfires is of importance for ensuring the safety and reliability of power systems. This paper proposes an innovative method that assesses the spatial risk distribution of wildfire-induced trips on transmission lines. By employing the Bayes theory and flame combustion model, the wildfire-induced trip risk assessment integrates the wildfire occurrence probability and insulation breakdown risk. A case study was conducted in the Guizhou province, China to validate the accuracy of the proposed model. By using ArcGIS, the wildfire occurrence probability distribution of Guizhou is visualized to enhance the work efficiency of operation and maintenance. The case study revealed that over 80% of the wildfire incidents occurred in areas with occurrence probability exceeding 50%. This finding substantiates the precision and reliability of the proposed method.