A Non-Parametric Aggregation Technique for Identifying Critical Nodes in a Network, using Three Topology-Based Cascade Models

摘要

Several approaches have been used for assessing the importance of network components, during an outage. For example, indicators based on network topology, such as node/links betweeness, allow ranking components from the most to the least important. Such models however do not consider specific aspects associated with network components outages that may trigger additional events. For example, the outage of a transmission line in an electric power system could produce a redistribution of the power flow and cause overload in nearby lines. To cope with such effects, several cascade models have been presented in the literature. These models, based on different assumptions could produce different importance rankings. In this paper, ranks of components derived from three simple cascade models are combined through a non-parametric technique, able to produce a unique ranking without considering decision-maker preferences. A version of the Italian high voltage power grid illustrates the proposed approach.