Cody Warner, Duncan Callaway, and Meredith Fowlie, “Dynamic Grid Management Technologies Reduce Wildfire Adaptation Costs in the Electric Power Sector” (Revised March 2025) | WP-347R | Blog Post
Abstract:
Wildfire is among the fastest-growing economic risks of climate change, yet strategies to adapt cost-effectively remain under-explored. In the electric power sector, where ignitions have triggered some of the most destructive wildfires on record, utilities are investing heavily to mitigate risk. This study evaluates the cost, reliability, and risk reduction benefits of the largest utility wildfire mitigation program in the U.S. Using detailed weather and vegetation data for 25,000 miles of high-risk powerlines, we develop a prediction model to estimate ignition risk and compare outcomes across locations with similar risk that received different interventions. With this quasi experimental design, we find that a new strategy that dynamically adjusts protective device sensitivity during elevated wildfire conditions reduces risk more cost-effectively than conventional measures such as burying powerlines underground or trimming vegetation. By combining models of wildfire risk, costs, and electricity outages, we demonstrate that data-driven analysis is critical to guiding adaptation decisions in the electric power sector, especially in cases where utilities face incentives to invest in capital-intensive measures.