Quantifying household vulnerability to power outages: Assessing risks of rapid electrification in smart cities

As cities accelerate decarbonization through building electrification, the growing dependence on electrical systems introduces new vulnerabilities during power disruptions. While grid-level resilience has been widely studied, household-scale impacts of electrification remain poorly understood. In this study, we develop a vulnerability assessment framework that combines machine learning classification with high-resolution synthetic energy data from 129,000 U.S. single-family homes. Our two-stage approach first identifies household electrification levels with over 80% accuracy and then quantifies outage vulnerability using a composite risk index that incorporates electrification profiles, backup capabilities, and climate exposure. A simulated case study reveals that fully electrified households face significantly higher risks during winter storms, with a 60% greater vulnerability compared to mixed-energy homes. In contrast, solar-equipped electrified households exhibit enhanced resilience during heat waves, leveraging renewable energy resources to mitigate risks. By highlighting critical dependencies and adaptive capacities, our framework emphasizes the importance of energy diversity and distributed energy resources in reducing outage vulnerabilities. This scalable, non-intrusive methodology provides actionable insights for policymakers and urban planners to design climate-resilient urban energy systems.