Measuring Cascading Failures in Smart Grid Networks

Measuring Cascading Failures in Smart Grid Networks

Sotharith Tauch (Auckland University of Technology, New Zealand), William Liu (Auckland University of Technology, New Zealand) and Russel Pears (Auckland University of Technology, New Zealand)
Copyright: © 2016 |Pages: 18
DOI: 10.4018/978-1-5225-0072-8.ch009
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Smart Grid is the next generation of the electrical power systems that form from interdependent networks. Cascading failures in such interdependent critical infrastructure is very crucial which can cause wide spread disruption. This chapter is intended to evaluate four different topological metrics in which can be best described and approximated the behavior of cascading failures in interdependent networks by employing two interlinks strategies such as random interlinks addition and degree-degree correlation interlinks. The four chosen topological metrics are algebraic connectivity, effective graph resistance, average betweenness centrality, and average distance. Throughout the chapter, analytical study of each metric are discussed and also compared with numerical simulation based on sandpile dynamics load distribution.
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The network of interconnected critical infrastructures such as electricity, telecommunications, transportation, and water-supply networks, are essential for the minimal functioning of contemporary societies and economies. As of today advancement in information and communications technology (ICT), the interdependencies among human engineered networks have open up a new vulnerability to the network of networks. The fact that failures of a small fraction of nodes and links cause local failures and may potentially lead to a widespread of an avalanche of cascading and escalating disruption to the whole network. Recent disasters ranging from hurricanes to large-scale power blackout have shown a significant vulnerability arises across different infrastructures (Gao et al., 2012). For example, a large blackout happened in north eastern United State and south eastern Canada left 5 million people without power for several day (Andersson et al., 2005). The case of large-scale power outage reveals the vulnerability of network topological structure and the operational state of the network. This outage is often caused by an initial disturbance of a small fraction of dependent components. Consequently, this failure propagates throughout the network until reaching a stage where failures stop. To counter this effect, the problem of cascading failures has to be analyzed from the perspective of network topological structure as well as flow dynamics of load in the networks. Existing studies have taken steps into modeling and analyzing the effects of cascading failures. Modeling and analyzing cascading failures of interdependent networks are relying on graph theory and various topological metrics. Topological metrics can be used to describe and quantify the properties of network structures and can also be used to optimize the robustness of networks.

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