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A LOADING-DEPENDENT MODEL OF PROBABILISTIC CASCADING FAILURE

Published online by Cambridge University Press:  01 January 2005

Ian Dobson
Affiliation:
Electrical & Computer Engineering Department, University of Wisconsin–Madison, Madison, WI 53706, E-mail: dobson@engr.wisc.edu
Benjamin A. Carreras
Affiliation:
Oak Ridge National Laboratory, Oak Ridge, TN 37831, E-mail: carrerasba@ornl.gov
David E. Newman
Affiliation:
Physics Department, University of Alaska, Fairbanks, AK 99775, E-mail: ffden@uaf.edu

Abstract

We propose an analytically tractable model of loading-dependent cascading failure that captures some of the salient features of large blackouts of electric power transmission systems. This leads to a new application and derivation of the quasibinomial distribution and its generalization to a saturating form with an extended parameter range. The saturating quasibinomial distribution of the number of failed components has a power-law region at a critical loading and a significant probability of total failure at higher loadings.

Type
Research Article
Copyright
© 2005 Cambridge University Press

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References

REFERENCES

Berg, S. & Mutafchiev, L. (1990). Random mappings with an attracting center: Lagrangian distributions and a regression function. Journal of Applied Probability 27: 622636.Google Scholar
Billington, R. & Allan, R.N. (1996). Reliability evaluation of power systems, 2nd ed. New York: Plenum Press.
Burtin, Y.D. (1980). On a simple formula for random mappings and its applications. Journal of Applied Probability 17: 403414.Google Scholar
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): 985994.Google Scholar
Carreras, B.A., Lynch, V.E., Newman, D.E., & Dobson, I. (2003). Blackout mitigation assessment in power transmission systems. In 36th Hawaii International Conference on System Sciences.
Carreras, B.A., Newman, D.E., Dobson, I., & Poole, A.B. (2001). Evidence for self-organized criticality in electric power system blackouts. In 34th Hawaii International Conference on System Sciences.
Carreras, B.A., Newman, D.E., Dobson, I., & Poole, A.B. (2004). Evidence for self-organized criticality in a time series of electric power system blackouts. IEEE Transactions on Circuits and Systems I: Regular Papers 51(9): 17331740.Google Scholar
Chen, J., Thorp, J.S., & Parashar, M. (2001). Analysis of electric power disturbance data. In 34th 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. In IEE Fifth International Conference on Power System Management and Control, pp. 384389.
Charalambides, Ch.A. (1990). Abel series distributions with applications to fluctuations of sample functions of stochastic functions. Communications in Statistics: Theory and Methods 19(1): 317335.Google Scholar
Consul, P.C. (1974). A simple urn model dependent upon predetermined strategy. Sankhya: The Indian Journal of Statistics, Series B 36(4): 391399.Google Scholar
Consul, P.C. (1988). On some models leading to a generalized Poisson distribution. Communications in Statistics: Theory and Methods 17(2): 423442.Google Scholar
Consul, P.C. (1989). Generalized Poisson distributions. New York: Marcel Dekker.
Consul, P.C. & Shoukri, M.M. (1988). Some chance mechanisms leading to a generalized Poisson probability model. American Journal of Mathematical and Management Sciences 8(1&2): 181202.Google Scholar
DeMarco, C.L. (2001). A phase transition model for cascading network failure. IEEE Control Systems Magazine 21(6): 4051.Google Scholar
Dobson, I., Carreras, B.A., & Newman, D.E. (2003). A probabilistic loading-dependent model of cascading failure and possible implications for blackouts. In 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. In 37th Hawaii International Conference on System Sciences.
Dobson, I., Chen, J., Thorp, J.S., Carreras, B.A., & Newman, D.E. (2002). Examining criticality of blackouts in power system models with cascading events. In 35th Hawaii International Conference on System Sciences.
Islam, M.N., O'Shaughnessy, C.D., & Smith, B. (1996). A random graph model for the final-size distribution of household infections. Statistics in Medicine 15: 837843.Google Scholar
Jaworski, J. (1998). Predecessors in a random mapping. Random Structures and Algorithms 14: 501519.Google Scholar
Katz, L. (1955). Probability of indecomposability of a random mapping function. Annals of Mathematical Statistics 26: 512517.Google Scholar
Kloster, M., Hansen, A., & Hemmer, P.C. (1997). Burst avalanches in solvable models of fibrous materials. Physical Review E 56(3).Google Scholar
Kosterev, D.N., Taylor, C.W., & Mittelstadt, W.A. (1999). Model validation for the August 10, 1996 WSCC system outage. IEEE Transactions on Power Systems 13(3): 967979.Google Scholar
Lindley, D.V. & Singpurwalla, N.D. (2002). On exchangeable, causal and cascading failures. Statistical Science 17(2): 209219.Google Scholar
NERC (North American Electric Reliability Council) (2002). 1996 system disturbances. Princeton, NJ: NERC.
Ni, M., McCalley, J.D., Vittal, V., & Tayyib, T. (2003). Online risk-based security assessment. IEEE Transactions on Power Systems 18(1): 258265.Google Scholar
Otter, R. (1949). The multiplicative process. Annals of Mathematical Statistics 20: 206224.Google Scholar
Parrilo, P.A., Lall, S., Paganini, F., Verghese, G.C., Lesieutre, B.C., & Marsden, J.E. (1999). Model reduction for analysis of cascading failures in power systems. Proceedings of the American Control Conference 6: 42084212.Google Scholar
Pepyne, D.L., Panayiotou, C.G., Cassandras, C.G., & Ho, Y.-C. (2001). Vulnerability assessment and allocation of protection resources in power systems. Proceedings of the American Control Conference 6: 47054710.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): 543548.Google Scholar
Roy, S., Asavathiratham, C., Lesieutre, B.C., & Verghese, G.C. (2001). Network models: growth, dynamics, and failure. In 34th Hawaii International Conference on System Sciences, pp. 728737.
Takács, L. (1967). Combinatorial methods in the theory of stochastic processes. New York: Wiley.
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 and National Resources Canada.
Watts, D.J. (2002). A simple model of global cascades on random networks. Proceedings of the National Academy of Sciences USA 99(9): 57665771.Google Scholar