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Testing Branching Process Estimators of Cascading Failure with Data from a Simulation of Transmission Line Outages

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  • Ian Dobson
  • Janghoon Kim
  • Kevin R. Wierzbicki

Abstract

We suggest a statistical estimator to quantify the propagation of cascading transmission line failures in large blackouts of electric power systems. We use a Galton‐Watson branching process model of cascading failure and the standard Harris estimator of the mean propagation modified to work when the process saturates at a maximum number of components. If the mean number of initial failures and the mean propagation are estimated, then the branching process model predicts the distribution of the total number of failures. We initially test this prediction on failure data generated by a simulation of cascading transmission line outages on two standard test systems. We discuss the effectiveness of the estimator in terms of how many cascades need to be simulated to predict the distribution of the total number of line outages accurately.

Suggested Citation

  • Ian Dobson & Janghoon Kim & Kevin R. Wierzbicki, 2010. "Testing Branching Process Estimators of Cascading Failure with Data from a Simulation of Transmission Line Outages," Risk Analysis, John Wiley & Sons, vol. 30(4), pages 650-662, April.
    • Handle: RePEc:wly:riskan:v:30:y:2010:i:4:p:650-662
    DOI: 10.1111/j.1539-6924.2010.01369.x
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    References listed on IDEAS

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    1. Hines, Paul & Apt, Jay & Talukdar, Sarosh, 2009. "Large blackouts in North America: Historical trends and policy implications," Energy Policy, Elsevier, vol. 37(12), pages 5249-5259, December.
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    Cited by:

    1. König, Sandra & Rass, Stefan & Schauer, Stefan, 2019. "Cyber-attack impact estimation for a port," Chapters from the Proceedings of the Hamburg International Conference of Logistics (HICL), in: Jahn, Carlos & Kersten, Wolfgang & Ringle, Christian M. (ed.), Digital Transformation in Maritime and City Logistics: Smart Solutions for Logistics. Proceedings of the Hamburg International Conference of Logistics, volume 28, pages 164-183, Hamburg University of Technology (TUHH), Institute of Business Logistics and General Management.
    2. Zhong, Jilong & Sanhedrai, Hillel & Zhang, FengMing & Yang, Yi & Guo, Shu & Yang, Shunkun & Li, Daqing, 2020. "Network endurance against cascading overload failure," Reliability Engineering and System Safety, Elsevier, vol. 201(C).
    3. Michael R. Greenberg & Karen Lowrie & Henry Mayer & Tayfur Altiok, 2011. "Risk‐Based Decision Support Tools: Protecting Rail‐Centered Transit Corridors from Cascading Effects," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1849-1858, December.
    4. John Hamer Powell & Michael Hammond & Albert Chen & Navonil Mustafee, 2018. "Human Agency in Disaster Planning: A Systems Approach," Risk Analysis, John Wiley & Sons, vol. 38(7), pages 1422-1443, July.

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