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September 19, 2025INFORMS Journal on Data Science3 citations

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

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SZShixiang ZhuRYRui YaoYXYao Xie

Key Points

  • Prolonged local outages can be reduced by 45.5% through targeted interventions, specifically in critical grid nodes.
  • Excessive weather stress at particular grid nodes leads to system-wide outages, indicating a need for strategic planning.
  • A spatio-temporal model was employed to analyze customer-level power outage data alongside weather records.
  • Enhancing grid resilience may mitigate future power disruptions, guiding better decision-making for the power sector.

Abstract

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. History: Bianca M. Colosimo served as the senior editor for this article. Funding: This work is supported by the U.S. Department of Energy Advanced Grid Modeling Program Grant DE-OE0000875. Supplemental Material: The online appendices are available at https://doi.org/10.1287/ijds.2023.0017 .

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Cite This Study

Zhu et al. (2025) studied this question.

synapsesocial.com/papers/68d464f831b076d99fa648b8https://doi.org/10.1287/ijds.2023.0017
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