Vulnerability and co-susceptibility determine the size of network cascades

Abstract

In a network, a local disturbance can propagate and eventually cause a substantial part of the system to fail, in cascade events that are easy to conceptualize but extraordinarily difficult to predict. Here, we develop a statistical framework that can predict cascade size distributions by incorporating two ingredients only: the vulnerability of individual components and the co-susceptibility of groups of components (i.e., their tendency to fail together). Using cascades in power grids as a representative example, we show that correlations between component failures define structured and often surprisingly large groups of co-susceptible components. Aside from their implications for blackout studies, these results provide insights and a new modeling framework for understanding cascades in financial systems, food webs, and complex networks in general.

5 pages, 4 figures, to appear in PRL http://journals.aps.org/prl/issues/118/4

References in corpus (4)

• Cascade control and defense in complex networks
• Sandpile on Scale-Free Networks
• Systemic delay propagation in the US airport network
• Rescuing ecosystems from extinction cascades through compensatory perturbations

Cited by in corpus (8)

• Cascading Failures in Complex Networks
• Cascading failures in scale-free interdependent networks
• Data-Driven Interaction Analysis of Line Failure Cascading in Power Grid Networks
• Limits of Predictability of Cascading Overload Failures in Spatially-Embedded Networks with Distributed Flows
• Improving power-grid systems via topological changes, or how self-organized criticality can help stability
• Dynamical heterogeneity and universality of power-grids
• The Waiting-Time Distribution for Network Partitions in Cascading Failures in Power Networks
• Identification of pressure points in modern power systems using transfer entropy