Quantifying Grid Resilience Against Extreme Weather Using Large-Scale Customer Power Outage Data

In recent years, extreme weather events frequently cause large-scale power outages. Resilience, the capability of withstanding, adapting to, and recovering from a large-scale disruption, has become a top priority for the power sector. However, a system-level understanding of power grid resilience remains limited, with most studies yielding conceptual insights or focusing on isolated technical issues. Using a spatio-temporal model, this study adopts a data-driven approach and analyzes quarter-hourly, customer-level power outage data and corresponding weather records from three major service territories on the U.S. East Coast. Our findings reveal that excessive weather stress and planning vulnerabilities at specific grid nodes are key drivers of prolonged local outages, which propagate system-wide. Simulations show that targeted interventions, such as isolating critical nodes and protecting vulnerable nodes from transient faults, can reduce customer outages by 45.5% and 49.5%, respectively. These insights inform actionable strategies for decision makers to enhance grid resilience and mitigate future disruptions.