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The Use of Simulation to Reduce the Domain of “Black Swans” with Application to Hurricane Impacts to Power Systems

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  • Christine L. Berner
  • Andrea Staid
  • Roger Flage
  • Seth D. Guikema

Abstract

Recently, the concept of black swans has gained increased attention in the fields of risk assessment and risk management. Different types of black swans have been suggested, distinguishing between unknown unknowns (nothing in the past can convincingly point to its occurrence), unknown knowns (known to some, but not to relevant analysts), or known knowns where the probability of occurrence is judged as negligible. Traditional risk assessments have been questioned, as their standard probabilistic methods may not be capable of predicting or even identifying these rare and extreme events, thus creating a source of possible black swans. In this article, we show how a simulation model can be used to identify previously unknown potentially extreme events that if not identified and treated could occur as black swans. We show that by manipulating a verified and validated model used to predict the impacts of hazards on a system of interest, we can identify hazard conditions not previously experienced that could lead to impacts much larger than any previous level of impact. This makes these potential black swan events known and allows risk managers to more fully consider them. We demonstrate this method using a model developed to evaluate the effect of hurricanes on energy systems in the United States; we identify hurricanes with potentially extreme impacts, storms well beyond what the historic record suggests is possible in terms of impacts.

Suggested Citation

  • Christine L. Berner & Andrea Staid & Roger Flage & Seth D. Guikema, 2017. "The Use of Simulation to Reduce the Domain of “Black Swans” with Application to Hurricane Impacts to Power Systems," Risk Analysis, John Wiley & Sons, vol. 37(10), pages 1879-1897, October.
  • Handle: RePEc:wly:riskan:v:37:y:2017:i:10:p:1879-1897
    DOI: 10.1111/risa.12742
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    References listed on IDEAS

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    1. Johansson, Jonas & Hassel, Henrik & Zio, Enrico, 2013. "Reliability and vulnerability analyses of critical infrastructures: Comparing two approaches in the context of power systems," Reliability Engineering and System Safety, Elsevier, vol. 120(C), pages 27-38.
    2. Andrea Staid & Seth Guikema & Roshanak Nateghi & Steven Quiring & Michael Gao, 2014. "Simulation of tropical cyclone impacts to the U.S. power system under climate change scenarios," Climatic Change, Springer, vol. 127(3), pages 535-546, December.
    3. Alan T. Murray & Timothy C. Matisziw & Tony H. Grubesic, 2008. "A Methodological Overview of Network Vulnerability Analysis," Growth and Change, Wiley Blackwell, vol. 39(4), pages 573-592, December.
    4. Seung‐Ryong Han & Seth D. Guikema & Steven M. Quiring, 2009. "Improving the Predictive Accuracy of Hurricane Power Outage Forecasts Using Generalized Additive Models," Risk Analysis, John Wiley & Sons, vol. 29(10), pages 1443-1453, October.
    5. Roshanak Nateghi & Seth D. Guikema & Steven M. Quiring, 2011. "Comparison and Validation of Statistical Methods for Predicting Power Outage Durations in the Event of Hurricanes," Risk Analysis, John Wiley & Sons, vol. 31(12), pages 1897-1906, December.
    6. Stanley Kaplan & B. John Garrick, 1981. "On The Quantitative Definition of Risk," Risk Analysis, John Wiley & Sons, vol. 1(1), pages 11-27, March.
    7. Aven, Terje, 2015. "Implications of black swans to the foundations and practice of risk assessment and management," Reliability Engineering and System Safety, Elsevier, vol. 134(C), pages 83-91.
    8. Yacov Y. Haimes, 2006. "On the Definition of Vulnerabilities in Measuring Risks to Infrastructures," Risk Analysis, John Wiley & Sons, vol. 26(2), pages 293-296, April.
    9. Aven, Terje & Krohn, Bodil S., 2014. "A new perspective on how to understand, assess and manage risk and the unforeseen," Reliability Engineering and System Safety, Elsevier, vol. 121(C), pages 1-10.
    10. Han, Seung-Ryong & Guikema, Seth D. & Quiring, Steven M. & Lee, Kyung-Ho & Rosowsky, David & Davidson, Rachel A., 2009. "Estimating the spatial distribution of power outages during hurricanes in the Gulf coast region," Reliability Engineering and System Safety, Elsevier, vol. 94(2), pages 199-210.
    11. Andrea Saltelli, 2002. "Sensitivity Analysis for Importance Assessment," Risk Analysis, John Wiley & Sons, vol. 22(3), pages 579-590, June.
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