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Risk‐Management and Risk‐Analysis‐Based Decision Tools for Attacks on Electric Power

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  • Jeffrey S. Simonoff
  • Carlos E. Restrepo
  • Rae Zimmerman

Abstract

Incident data about disruptions to the electric power grid provide useful information that can be used as inputs into risk management policies in the energy sector for disruptions from a variety of origins, including terrorist attacks. This article uses data from the Disturbance Analysis Working Group (DAWG) database, which is maintained by the North American Electric Reliability Council (NERC), to look at incidents over time in the United States and Canada for the period 1990–2004. Negative binomial regression, logistic regression, and weighted least squares regression are used to gain a better understanding of how these disturbances varied over time and by season during this period, and to analyze how characteristics such as number of customers lost and outage duration are related to different characteristics of the outages. The results of the models can be used as inputs to construct various scenarios to estimate potential outcomes of electric power outages, encompassing the risks, consequences, and costs of such outages.

Suggested Citation

  • Jeffrey S. Simonoff & Carlos E. Restrepo & Rae Zimmerman, 2007. "Risk‐Management and Risk‐Analysis‐Based Decision Tools for Attacks on Electric Power," Risk Analysis, John Wiley & Sons, vol. 27(3), pages 547-570, June.
  • Handle: RePEc:wly:riskan:v:27:y:2007:i:3:p:547-570
    DOI: 10.1111/j.1539-6924.2007.00905.x
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    References listed on IDEAS

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    1. Peter Gordon & James E. Moore II & Harry W. Richardson & Qisheng Pan, 2005. "The Economic Impact of a Terrorist Attack on the Twin Ports of Los Angeles–Long Beach," Chapters, in: Harry W. Richardson & Peter Gordon & James E. Moore II (ed.), The Economic Impacts of Terrorist Attacks, chapter 14, Edward Elgar Publishing.
    2. Adam Rose & Shu‐Yi Liao, 2005. "Modeling Regional Economic Resilience to Disasters: A Computable General Equilibrium Analysis of Water Service Disruptions," Journal of Regional Science, Wiley Blackwell, vol. 45(1), pages 75-112, February.
    3. Rae Zimmerman & Carlos E. Restrepo, 2006. "The next step: quantifying infrastructure interdependencies to improve security," International Journal of Critical Infrastructures, Inderscience Enterprises Ltd, vol. 2(2/3), pages 215-230.
    4. Rae Zimmerman & Carlos E. Restrepo & Jeffrey S. Simonoff & Lester B Lave, 2007. "Risk and Economic Costs of a Terrorist Attack on the Electric System," Chapters, in: Harry W Richardson & Peter Gordon & James E. Moore II (ed.), The Economic Costs and Consequences of Terrorism, chapter 14, Edward Elgar Publishing.
    5. George E. Apostolakis & Douglas M. Lemon, 2005. "A Screening Methodology for the Identification and Ranking of Infrastructure Vulnerabilities Due to Terrorism," Risk Analysis, John Wiley & Sons, vol. 25(2), pages 361-376, April.
    6. Harry F. Martz & Mark E. Johnson, 1987. "Risk Analysis of Terrorist Attacks," Risk Analysis, John Wiley & Sons, vol. 7(1), pages 35-47, March.
    7. Masiello, Ralph & Spare, John & Roark, Alan & Brattini, Sam, 2004. "Reliability @ Risk: A New Paradigm for Assessing Reliability," The Electricity Journal, Elsevier, vol. 17(10), pages 71-84, December.
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    Cited by:

    1. Shen, Lijuan & Tang, Loon Ching, 2019. "Enhancing resilience analysis of power systems using robust estimation," Reliability Engineering and System Safety, Elsevier, vol. 186(C), pages 134-142.
    2. Restrepo, Carlos E. & Simonoff, Jeffrey S. & Zimmerman, Rae, 2009. "Causes, cost consequences, and risk implications of accidents in US hazardous liquid pipeline infrastructure," International Journal of Critical Infrastructure Protection, Elsevier, vol. 2(1), pages 38-50.
    3. Rae Zimmerman, 2009. "Making Infrastructure Competitive in an Urban World," The ANNALS of the American Academy of Political and Social Science, , vol. 626(1), pages 226-241, November.

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