Risk-management and risk-analysis-based decision tools for attacks on electric power

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

Research output: Contribution to journalArticlepeer-review


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.

Original languageEnglish (US)
Pages (from-to)547-570
Number of pages24
JournalRisk Analysis
Issue number3
StatePublished - Jun 2007


  • Electric power outages
  • Logistic regression
  • Negative binomial regression
  • Prediction interval
  • Weighted least squares

ASJC Scopus subject areas

  • Safety, Risk, Reliability and Quality
  • Physiology (medical)


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