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Climate change is expected to intensify the effects of extreme weather events on power systems and increase the frequency of severe power outages. The large-scale integration of environment-dependent renewables during energy decarbonization could induce increased uncertainty in the supply–demand balance and climate vulnerability of power grids. This Perspective discusses the superimposed risks of climate change, extreme weather events and renewable energy integration, which collectively affect power system resilience. Insights drawn from large-scale spatiotemporal data on historical US power outages induced by tropical cyclones illustrate the vital role of grid inertia and system flexibility in maintaining the balance between supply and demand, thereby preventing catastrophic cascading failures. Alarmingly, the future projections under diverse emission pathways signal that climate hazards — especially tropical cyclones and heatwaves — are intensifying and can cause even greater impacts on the power grids. High-penetration renewable power systems under climate change may face escalating challenges, including more severe infrastructure damage, lower grid inertia and flexibility, and longer post-event recovery. Towards a net-zero future, this Perspective then explores approaches for harnessing the inherent potential of distributed renewables for climate resilience through forming microgrids, aligned with holistic technical solutions such as grid-forming inverters, distributed energy storage, cross-sector interoperability, distributed optimization and climate–energy integrated modelling.
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This content will become publicly available on April 1, 2027
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. 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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- Award ID(s):
- 2134037
- PAR ID:
- 10690360
- Publisher / Repository:
- INFORMS Journal on Data Science
- Date Published:
- Journal Name:
- INFORMS Journal on Data Science
- Volume:
- 5
- Issue:
- 2
- ISSN:
- 2694-4022
- Page Range / eLocation ID:
- 102 to 118
- Format(s):
- Medium: X
- Sponsoring Org:
- National Science Foundation
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