Dynamic grid management reduces wildfire adaptation costs in the electric power sector

Abstract

Wildfire is among the fastest-growing economic risks of climate change, yet cost-effective adaptation strategies remain underexplored. In the electric power sector, where utility infrastructure has ignited some of the most destructive fires, companies are investing heavily to reduce risk. Here we evaluate the costs, reliability implications and risk-reduction benefits of the largest utility wildfire mitigation programme in the United States. Using weather and vegetation data for 25,000 miles of high-risk power lines, we develop a predictive model of ignition risk and compare outcomes across locations that had similar risk profiles but received different interventions. A newer strategy—adjusting protective device sensitivity during high-risk conditions—has reduced more wildfire risk at lower cost per avoided structure burned than conventional approaches such as undergrounding or vegetation management. Our results underscore the importance of comprehensive accounting of costs, risks and reliability when evaluating adaptation investments, particularly where capital-intensive measures may be over-incentivized. Extreme events are increasingly becoming severe risks to the electric grid, yet there is limited understanding of the cost-effectiveness of adaptation investments. This research demonstrates that dynamic grid management could reduce large capital spending and limit wildfire risks in the USA.