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Cited by 542

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Critical points and transitions in an electric power transmission model for cascading failure blackouts

Open access
Carreras, B. A., Lynch, V. E., Dobson, I., Newman, D. E.·2002·Chaos: An Interdisciplinary Journal of Nonlinear Science

Abstract

Cascading failures in large-scale electric power transmission systems are an important cause of blackouts. Analysis of North American blackout data has revealed power law (algebraic) tails in the blackout size probability distribution which suggests a dynamical origin. With this observation as motivation, we examine cascading failure in a simplified transmission system model as load power demand is increased. The model represents generators, loads, the transmission line network, and the operating limits on these components. Two types of critical points are identified and are characterized by transmission line flow limits and generator capability limits, respectively. Results are obtained for tree networks of a regular form and a more realistic 118-node network. It is found that operation near critical points can produce power law tails in the blackout size probability distribution similar to those observed. The complex nature of the solution space due to the interaction of the two critical points is examined.

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Metadata

Authors
Carreras, B. A., Lynch, V. E., Dobson, I., & Newman, D. E.
Venue
Chaos: An Interdisciplinary Journal of Nonlinear Science
Published
2002-12-01
Volume
12
Issue
4
Pages
985-994
ISSN
  • 1054-1500 (ISSN-L)
  • 1089-7682
OpenAlex
W2147040528
Cited by
542
References
1
FWCI
5.22
Type
journal article
Language
en
Open access
green

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CoChat. (2026). Citation check: Critical points and transitions in an electric power transmission model for cascading failure blackouts. https://app.cochat.ai/papers/10.1063/1.1505810
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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: An Interdisciplinary Journal of Nonlinear Science. https://doi.org/10.1063/1.1505810

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Contains information from the Semantic Scholar Academic Graph Datasets, made available under the ODC Attribution License (ODC-BY 1.0).

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