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Large-scale data analysis of power grid resilience across multiple US service regions

Author

Listed:
  • Chuanyi Ji

    (School of Electrical and Computer Engineering, Georgia Institute of Technology)

  • Yun Wei

    (School of Electrical and Computer Engineering, Georgia Institute of Technology)

  • Henry Mei

    (School of Electrical and Computer Engineering, Georgia Institute of Technology)

  • Jorge Calzada

    (National Grid)

  • Matthew Carey

    (New York State Public Service Commission)

  • Steve Church

    (New York State Electric and Gas Corporation)

  • Timothy Hayes

    (Central Hudson Gas & Electric Corp.)

  • Brian Nugent

    (Orange & Rockland Utilities)

  • Gregory Stella

    (New York State Public Service Commission)

  • Matthew Wallace

    (New York State Public Service Commission)

  • Joe White

    (Orange & Rockland Utilities)

  • Robert Wilcox

    (National Grid)

Abstract

Severe weather events frequently result in large-scale power failures, affecting millions of people for extended durations. However, the lack of comprehensive, detailed failure and recovery data has impeded large-scale resilience studies. Here, we analyse data from four major service regions representing Upstate New York during Super Storm Sandy and daily operations. Using non-stationary spatiotemporal random processes that relate infrastructural failures to recoveries and cost, our data analysis shows that local power failures have a disproportionally large non-local impact on people (that is, the top 20% of failures interrupted 84% of services to customers). A large number (89%) of small failures, represented by the bottom 34% of customers and commonplace devices, resulted in 56% of the total cost of 28 million customer interruption hours. Our study shows that extreme weather does not cause, but rather exacerbates, existing vulnerabilities, which are obscured in daily operations.

Suggested Citation

  • Chuanyi Ji & Yun Wei & Henry Mei & Jorge Calzada & Matthew Carey & Steve Church & Timothy Hayes & Brian Nugent & Gregory Stella & Matthew Wallace & Joe White & Robert Wilcox, 2016. "Large-scale data analysis of power grid resilience across multiple US service regions," Nature Energy, Nature, vol. 1(5), pages 1-8, May.
    • Handle: RePEc:nat:natene:v:1:y:2016:i:5:d:10.1038_nenergy.2016.52
    DOI: 10.1038/nenergy.2016.52
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    Cited by:

    1. Tormos-Aponte, Fernando & García-López, Gustavo & Painter, Mary Angelica, 2021. "Energy inequality and clientelism in the wake of disasters: From colorblind to affirmative power restoration," Energy Policy, Elsevier, vol. 158(C).
    2. Rachunok, Benjamin & Nateghi, Roshanak, 2020. "The sensitivity of electric power infrastructure resilience to the spatial distribution of disaster impacts," Reliability Engineering and System Safety, Elsevier, vol. 193(C).
    3. Shang, Ce & Lin, Teng & Li, Canbing & Wang, Keyou & Ai, Qian, 2021. "Joining resilience and reliability evaluation against both weather and ageing causes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    4. Patrick Gasser & Marco Cinelli & Anna Labijak & Matteo Spada & Peter Burgherr & Miłosz Kadziński & Božidar Stojadinović, 2020. "Quantifying Electricity Supply Resilience of Countries with Robust Efficiency Analysis," Energies, MDPI, vol. 13(7), pages 1-35, March.
    5. Heffron, Raphael J. & Körner, Marc-Fabian & Schöpf, Michael & Wagner, Jonathan & Weibelzahl, Martin, 2021. "The role of flexibility in the light of the COVID-19 pandemic and beyond: Contributing to a sustainable and resilient energy future in Europe," Renewable and Sustainable Energy Reviews, Elsevier, vol. 140(C).
    6. Xu, Jiuping & Tian, Yalou & Wang, Fengjuan & Yang, Guocan & Zhao, Chuandang, 2024. "Resilience-economy-environment equilibrium based configuration interaction approach towards distributed energy system in energy intensive industry parks," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
    7. Kairui Feng & Min Ouyang & Ning Lin, 2022. "Tropical cyclone-blackout-heatwave compound hazard resilience in a changing climate," Nature Communications, Nature, vol. 13(1), pages 1-11, December.
    8. Glasmeier, Amy K. & Williams, Darien Alexander, 2022. "Toward a theory of high reliability for natural gas distribution utilities," Utilities Policy, Elsevier, vol. 75(C).
    9. Wang, Jing & Zuo, Wangda & Rhode-Barbarigos, Landolf & Lu, Xing & Wang, Jianhui & Lin, Yanling, 2019. "Literature review on modeling and simulation of energy infrastructures from a resilience perspective," Reliability Engineering and System Safety, Elsevier, vol. 183(C), pages 360-373.
    10. Das, Laya & Munikoti, Sai & Natarajan, Balasubramaniam & Srinivasan, Babji, 2020. "Measuring smart grid resilience: Methods, challenges and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
    11. Xu, Min & Li, Guoyuan & Chen, Anthony, 2024. "Resilience-driven post-disaster restoration of interdependent infrastructure systems under different decision-making environments," Reliability Engineering and System Safety, Elsevier, vol. 241(C).
    12. Dunn, Laurel N. & Sohn, Michael D. & LaCommare, Kristina Hamachi & Eto, Joseph H., 2019. "Exploratory analysis of high-resolution power interruption data reveals spatial and temporal heterogeneity in electric grid reliability," Energy Policy, Elsevier, vol. 129(C), pages 206-214.
    13. Hao Wu & Xiangyi Meng & Michael M. Danziger & Sean P. Cornelius & Hui Tian & Albert-László Barabási, 2022. "Fragmentation of outage clusters during the recovery of power distribution grids," Nature Communications, Nature, vol. 13(1), pages 1-7, December.

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