Assessing Individual Level Power Outage Vulnerability through Synthetic Populations

Extreme weather power outages disproportionately impact vulnerable populations, but existing data does not fully capture how individual demographics contribute to infrastructure vulnerability. This study addresses this gap by developing a comprehensive power outage vulnerability dataset for Houston, Texas, integrating synthetic population modeling with census tract-level outage likelihood focusing on Winter Storm Uri. Using Public Use Microdata from the American Community Survey (2015–2019) and Oak Ridge National Laboratory’s UrbanPop framework, we constructed a synthetic population to evaluate intersecting social vulnerabilities at the individual level. Multiple Correspondence Analysis (MCA) identified vulnerability profiles tied to risk factors such as independent living difficulty (e.g., disability, age >65), economic sensitivity (low income, unemployment), and linguistic isolation. Affinity Propagation clustering and distance-based Redundancy Analysis (dbRDA) revealed eight distinct neighborhood typologies, highlighting spatial disparities in healthcare access and preexisting health conditions that exacerbate outage impacts. Results demonstrate that individuals facing overlapping vulnerabilities—particularly those in linguistically isolated or economically disadvantaged households—reside in areas with the highest outage likelihood. These findings challenge aggregate-scale analyses by emphasizing intersectionality in vulnerability, where multidimensional risks amplify susceptibility. We propose three policy interventions to address power outage vulnerability: (1) multilingual emergency communication strategies, (2) community resilience hubs for resource distribution, and (3) participatory engagement frameworks to integrate marginalized voices in planning. This novel methodology advances energy equity research by coupling infrastructure resilience with individual-level social vulnerability, offering actionable pathways to mitigate disparities in disaster preparedness and response.