Wildfire Risk and Grid Resilience

Associate Professor of Engineering Vikrant Vaze. (Photo courtesy of CERAWeek by S&P Global.)

Their research explores the optimization of Public Safety Power Shutoffs (PSPS), a common strategy used to prevent wildfires by temporarily disabling sections of the power grid. Although effective in reducing fire risk, PSPS events inconvenience communities by causing power outages that can disrupt medical devices, spoil food, and create other social challenges.

The research highlights three key risk factors: low humidity, dry vegetation, and strong winds, which interact with electrical infrastructure. The team utilizes sophisticated simulations to analyze how these factors contribute to wildfire risks. Despite the ongoing nature of their work, initial findings demonstrate the advantages of using calibrated risk assessments to optimize PSPS strategies, allowing for more precise control over which grid sections to shut down.

Two case studies illustrate the power of this approach. In the 2020 Blue Ridge Fire in Southern California, a calibrated model showed only minor differences compared to standard methods. However, in the more severe Mineral Fire in Central California that same year, the calibrated simulator revealed substantial differences, underscoring the importance of a more accurate understanding of risk to prevent extensive damage.

Looking ahead, Vaze and Bertsch plan to investigate interactions across diverse power systems and conduct worst‑case scenario analyses. Their work underscores the need for advanced models that more precisely forecast wildfire risk and inform strategies to minimize the impact of fires on power systems and communities.