Equitably allocating wildfire resilience investments for power grids — The curse of aggregation and vulnerability indices

Abstract

Social vulnerability indices have increased traction for guiding infrastructure investment decisions to prioritize communities that need these investments most. One such plan is the Biden-Harris Justice40 initiative, which aims to guide equitable infrastructure investments by ensuring that disadvantaged communities defined by the Climate & Economic Justice Screening Tool (CEJST) receive 40% of the total benefit realized by the investment. However, there is limited research on the practicality of applying vulnerability indices like the CEJST to real-world decision-making for policy outcomes. In this paper, we study this gap by examining the effectiveness of vulnerability indices in a case study focused on power shutoff and undergrounding decisions in wildfire-prone regions. Using a mixed-integer program and a high-fidelity synthetic transmission network in Texas, we model resource allocation policies inspired by Justice40 and evaluate their impact on reducing power outages and mitigating wildfire risk for vulnerable groups. Our analysis reveals that the Justice40 framework may fail to protect certain communities facing high wildfire risk. In our case study, we show that Indigenous groups are particularly impacted. We posit that this outcome is likely due to information losses from data aggregation and the use of generalized vulnerability indices. By incorporating explicit group-level protections, we illustrate the potential for improving outcomes for the most disproportionately affected communities.