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This paper describes a stochastic “Random Chemistry” (RC) algorithm to identify multiple (n− k) contingencies that initiate large cascading failures in a simulated power system. The method requires only O(log(n)) simulations per contingency identified, which is orders of magnitude faster than random search of this combinatorial space. We applied the method(More)
We derive a measure of “electrical centrality” for AC power networks, which describes the structure of the network as a function of its electrical topology rather than its physical topology. We compare our centrality measure to conventional measures of network structure using the IEEE 300bus network. We find that when measured electrically, power networks(More)
In order to identify the extent to which results from topological graph models are useful for modeling vulnerability in electricity infrastructure, we measure the susceptibility of power networks to random failures and directed attacks using three measures of vulnerability: characteristic path lengths, connectivity loss, and blackout sizes. The first two(More)
Numerous recent reports have assessed the adequacy of current generating capacity to meet the growing electricity demand from Plug-in Hybrid Electric Vehicles (PHEVs) and the potential for using these vehicles to provide grid support (Vehicle to Grid, V2G) services. However, little has been written on how these new loads will affect the medium and(More)
The topological (graph) structure of complex networks often provides valuable information about the performance and vulnerability of the network. However, there are multiple ways to represent a given network as a graph. Electric power transmission and distribution networks have a topological structure that is straightforward to represent and analyze as a(More)
This paper describes results from the analysis of two approaches to blackout risk analysis in electric power systems. In the first analysis, we compare two topological (graph-theoretic) methods for finding vulnerable locations in a power grid, to a simple model of cascading outage. This comparison indicates that topological models can lead to misleading(More)
Identifying coherent sub-graphs in networks is important in many applications. In power systems, large systems are divided into areas and zones to aid in planning and control applications. But not every partitioning is equally good for all applications; different applications have different goals, or attributes, against which solutions should be evaluated.(More)
Opinion article + supporting information Charles D. Brummitt1,2, Paul D. H. Hines3, Ian Dobson4, Cristopher Moore5, and Raissa M. D’Souza2,5,6 1Department of Mathematics, University of California, Davis, CA 95616 USA 2Complexity Sciences Center, University of California, Davis, CA 95616 USA 3School of Engineering, University of Vermont, Burlington, VT 05405(More)
Prior research has shown that autocorrelation and variance in voltage measurements tend to increase as power systems approach instability. This paper seeks to identify the conditions under which these statistical indicators provide reliable early warning of instability in power systems. First, the paper derives and validates a semi-analytical method for(More)
Numerous recent papers have found important relationships between network structure and risks within networks. These results indicate that network structure can dramatically affect the relative effectiveness of risk identification and mitigation methods. With this in mind this paper provides a comparative analysis of the topological and electrical structure(More)