Electric Grid Vulnerability Analysis to Identify Communities Prone to Wildfires

Abstract

Natural hazards, like wildfires, present various challenges to the electric grid that can leave many communities without power. To identify vulnerabilities in the grid and the corresponding at-risk communities, this work considers the implementation of two Graph Theory assessment approaches, namely betweenness centrality and minimum cut, and combines the results from each with spatial fire probability data to produce a novel assessment of communities at-risk of losing service because of a wildfire. The results from a betweenness centrality analysis identified at-risk communities whose critical lines, necessary for routing power to the community from the numerous generators, were found to be at-risk if they were located within high probability burn zones. Communities at-risk of separation from the grid with one cut (or electrical shorting) of a transmission line due its proximity to a high burn probability (BP) area were also identified using the minimum cut Graph Theory algorithm. When the methodologies were applied to a demonstration transmission grid, the results found that about one third of the 585 substations had centrally located lines in high BP areas. About 46% of the substations require just one cut to be removed from the grid, and the average length of these one-cut segments was 37 km and the longest was 188 km.