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ESTIMATING FAILURE PROPAGATION IN MODELS OF CASCADING BLACKOUTS

Published online by Cambridge University Press:  31 August 2005

Ian Dobson ,
Benjamin A. Carreras ,
Vickie E. Lynch ,
Bertrand Nkei  and
David E. Newman
Ian Dobson
Affiliation:
ECE Department, University of Wisconsin, Madison, Wisconsin 53706, E-mail: dobson@engr.wisc.edu
Benjamin A. Carreras
Affiliation:
Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, E-mail: carrerasba@ornl.gov
Vickie E. Lynch
Affiliation:
Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, E-mail: carrerasba@ornl.gov
Bertrand Nkei
Affiliation:
Oak Ridge National Laboratory, Oak Ridge, Tennessee 37831, E-mail: carrerasba@ornl.gov
David E. Newman
Affiliation:
Physics Department, University of Alaska, Fairbanks, Alaska 99775, E-mail: ffden@uaf.edu
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Abstract

We compare and test statistical estimates of failure propagation in data from versions of a probabilistic model of loading-dependent cascading failure and a power system blackout model of cascading transmission line overloads. The comparisons suggest mechanisms affecting failure propagation and are an initial step toward monitoring failure propagation from practical system data. Approximations to the probabilistic model describe the forms of probability distribution of cascade sizes.

Information

Type
Papers from the 8th International PMAPS Conference
Information
Probability in the Engineering and Informational Sciences , Volume 19 , Issue 4 , October 2005 , pp. 475 - 488
Copyright
© 2005 Cambridge University Press

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References

REFERENCES

Carreras, B.A., Lynch, V.E., Dobson, I., & Newman, D.E. (2002). Critical points and transitions in an electric power transmission model for cascading failure blackouts. Chaos 12(4): 985–994.Google Scholar
Carreras, B.A., Lynch, V.E., Dobson, I., & Newman, D.E. (2004). Complex dynamics of blackouts in power transmission systems. Chaos 14(3): 643–652.Google Scholar
Carreras, B.A., Lynch, V.E., Dobson, I., & Newman, D.E. (2004). Dynamical and probabilistic approaches to the study of blackout vulnerability of the power transmission grid. 37th Hawaii International Conference on System Sciences.
Carreras, B.A., Lynch, V.E., Newman, D.E., & Dobson, I. (2003). Blackout mitigation assessment in power transmission systems. 36th Hawaii International Conference on System Sciences.
Chen, J. & Thorp, J.S. (2002). A reliability study of transmission system protection via a hidden failure DC load flow model. IEE Fifth International Conference on Power System Management and Control, pp. 384–389.
Chen, J., Thorp, J.S., & Dobson, I. (2005). Cascading dynamics and mitigation assessment in power system disturbances via a hidden failure model. International Journal of Electrical Power and Energy Systems 27(4): 318–326.Google Scholar
Chen, Q., Zhu, K., & McCalley, J.D. (2001). Dynamic decision-event trees for rapid response to unfolding events in bulk transmission systems. IEEE Porto Power Tech Proceedings, vol. 2.
Consul, P.C. (1974). A simple urn model dependent upon predetermined strategy. Sankhya: The Indian Journal of Statistics, Series B 36(4): 391–399.Google Scholar
Consul, P.C. (1988). On some models leading to the generalized Poisson distribution. Communications in Statistics—Theory and Methods 17(2): 423–442.Google Scholar
Consul, P.C. (1989). Generalized Poisson distributions. New York: Dekker.
Dobson, I., Carreras, B.A., Lynch, V.E., & Newman, D.E. (2004). Complex systems analysis of series of blackouts: Cascading failure, criticality, and self-organization. IREP Symposium on Bulk Power System Dynamics and Control—VI.
Dobson, I., Carreras, B.A., & Newman, D.E. (2003). A probabilistic loading-dependent model of cascading failure and possible implications for blackouts. 36th Hawaii International Conference on System Sciences.
Dobson, I., Carreras, B.A., & Newman, D.E. (2004). A branching process approximation to cascading load-dependent system failure. 37th Hawaii International Conference on System Sciences.
Dobson, I., Carreras, B.A., & Newman, D.E. (2004). Probabilistic load-dependent cascading failure with limited component interactions. IEEE International Symposium on Circuits and Systems.
Dobson, I., Carreras, B.A., & Newman, D.E. (2005). A loading-dependent model of probabilistic cascading failure. Probability in the Engineering and Informational Sciences 19(1): 15–32.Google Scholar
Harris, T.E. (1989). Theory of branching processes. New York: Dover.
NERC (2002). 1996 system disturbances. Princeton, NJ: North American Electric Reliability Council.
Ni, M., McCalley, J.D., Vittal, V., & Tayyib, T. (2003). Online risk-based security assessment. IEEE Transactions on Power Systems 18(1): 258–265.Google Scholar
Rios, M.A., Kirschen, D.S., Jawayeera, D., Nedic, D.P., & Allan, R.N. (2002). Value of security: Modeling time-dependent phenomena and weather conditions. IEEE Transactions on Power Systems 17(3): 543–548.Google Scholar
U.S.–Canada Power System Outage Task Force (2004). Final report on the August 14th blackout in the United States and Canada, United States Department of Energy, Washington, DC, and National Resources Canada.