Abstract
This paper presents a data-driven approach for quantifying the resilience of distribution power grids to extreme weather events using two key metrics: (a) the number of outages and (b) restoration time. The method leverages historical outage records maintained by power utilities and weather measurements collected by the National Oceanic and Atmospheric Administration (NOAA) to evaluate resilience across a utility’s service territory. The proposed framework consists of three stages. First, outage events are systematically extracted from the outage records by temporally and spatially aggregating coincident component outages. In the second stage, weather zones across the service territory are delineated using a Voronoi polygon approach, based on the locations of NOAA weather sensors. Finally, data-driven models for outage fragility and restoration time are developed for each weather zone. These models enable the quantification and visualization of resilience metrics under varying intensities of extreme weather events. The proposed method is demonstrated using real-world data from a Midwestern US distribution utility, focused on wind- and precipitation-related events. The dataset spans two decades and includes over 160,000 outage records. The data-driven models accurately capture the nonlinear relationship between weather intensity, outage accumulation, and restoration time, and the resulting zone-specific resilience maps provide utilities with actionable insights for prioritizing hardening and operational planning.
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Data availability
The data that support the findings of this study are available from the corresponding author upon reasonable request.
Code availability
The code packages that support the findings of this study are available from the corresponding author upon reasonable request.
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Funding
This work was partially supported by the Power System Engineering and Research Center under Grant PSERC S-110, the U.S. Department of Energy’s Office of Electricity under the award Number DE-OE0000986, and the National Science Foundation under Grant ECCS 2042314. The funders had no role in the design of the study, data collection, analysis, interpretation, or writing of the manuscript.
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S.M. and Z.W. conceived the experiments, D.W., L.L., and J.Z. conducted the experiments, D.W. and S.M. analyzed the results. D.W. and S.M. prepared the manuscript, and all authors reviewed it.
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Wang, D., Maharjan, S., Zheng, J. et al. Data-driven quantification and visualization of resilience metrics of power distribution systems. Sci Rep (2026). https://doi.org/10.1038/s41598-026-37040-w
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DOI: https://doi.org/10.1038/s41598-026-37040-w
