Conference Paper

A probabilistic loading-dependent model of cascading failure and possible implications for blackouts

Dept. of ECE, Wisconsin Univ., Madison, WI, USA
DOI: 10.1109/HICSS.2003.1173909 Conference: System Sciences, 2003. Proceedings of the 36th Annual Hawaii International Conference on
Source: IEEE Xplore

ABSTRACT Catastrophic disruptions of large, interconnected infrastructure systems are often due to cascading failure. For example, large blackouts of electric power systems are typically caused by cascading failure of heavily loaded system components. We introduce the CASCADE model of cascading failure of a system with many identical components randomly loaded. An initial disturbance causes some components to fail by exceeding their loading limit. Failure of a component causes a fixed load increase for other components. As components fail, the system becomes more loaded and cascading failure of further components becomes likely. The probability distribution of the number of failed components is an extended quasibinomial distribution. Explicit formulas for the extended quasibinomial distribution are derived using a recursion. The CASCADE model in a restricted parameter range gives a new model yielding the quasibinomial distribution. Some qualitative behaviors of the extended quasibinomial distribution are illustrated, including regimes with power tails, exponential tails, and significant probabilities of total system failure.

Download full-text


Available from: Ian Dobson, Jul 01, 2015
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: In this paper, a blackout model that considers the slow process at the beginning of blackouts is proposed based on the improved OPA model. The model contains two layers of iteration. The inner iteration, which describes the fast dynamics of the system, simulates the power system cascading failure, including the tree contact and failure of lines caused by heating. Compared with the improved OPA model, the outer iteration, which describes the long-term slow dynamics of the system, adds the simulation of tree growth and utility vegetation management (UVM). Moreover, the proposed model also improves the simulation of protective relays and the dispatching center and makes them closer to practical conditions. The effectiveness of the proposed model is verified by the simulation results of Northeast Power Grid of China.
    Power and Energy Society General Meeting, 2012 IEEE; 07/2012
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: Hidden failure relay protection is the major cause of cascading failure in power system. Therefore, in this study, a hidden failure model has been developed to study the impact of certain parameter that could cause cascading collapse. The parameters that could lead to major blackout include system loading level, spinning reserve, hidden failure probability and other factors. As the overall load is the key factor that could affect the risk of cascading outages, this study will reveal the impact of it to the system. A test system of IEEE 24 bus RTS is used as a case study. The hidden failure model adopts here is the steady state analysis, which is caused by line tripping. The significant loads at which blackout risk sharply increases are identifiable for cascading collapse. This study can provide guidance for the utility on when and how to mitigate the cascading collapse from spreading to the entire power system. This study also can determine the critical loading in the risk of cascading failure.
    Informatics and Computational Intelligence (ICI), 2011 First International Conference on; 01/2011
  • Source
    [Show abstract] [Hide abstract]
    ABSTRACT: We quantify the closeness of the approximation between two high-level probabilistic models of cascading failure. In one model called CASCADE, failing components successively load the unfailed components, whereas the other model is based on a Galton-Watson branching process. Both models are generic, idealized models of cascading failure of a large, but finite number of components. For suitable parameters, the distributions of the total number of failures from the branching process and CASCADE models are close enough to make the branching process a useful approximation.
    IEEE Transactions on Reliability 01/2011; DOI:10.1109/TR.2010.2055928 · 1.66 Impact Factor