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Wildfires are a threat to public safety and have increased in both frequencyand severity due to climate change. To mitigate wildfire ignition risks,electric power system operators proactively de-energize high-risk power linesduring "public safety power shut-off" (PSPS) events. Line de-energizations cancause communities to lose power, which may result in negative economic, health,and safety impacts. Furthermore, the same communities may repeatedly experiencepower shutoffs over the course of a wildfire season, which compounds thesenegative impacts. However, there may be many combinations of power lines whosede-energization will result in about the same reduction of system-wide wildfirerisk, but the associated power outages affect different communities. Therefore,one may raise concerns regarding the fairness of de-energization decisions.Accordingly, this paper proposes a framework to select lines to de-energize inorder to balance wildfire risk reduction, total load shedding, and fairnessconsiderations. The goal of the framework is to prevent a small fraction ofcommunities from disproportionally being impacted by PSPS events, and toinstead more equally share the burden of power outages. For a geolocated testcase in the southwestern United States, we use actual California demand data aswell as real wildfire risk forecasts to simulate PSPS events during the 2021wildfire season and compare the performance of various methods for promotingfairness. Our results demonstrate that the proposed formulation can providesignificantly more fair outcomes with limited impacts on system-wideperformance.

Sharing the Load: Considering Fairness in De-energization Scheduling to Mitigate Wildfire Ignition Risk using Rolling Optimization