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| Content Provider | IEEE Xplore Digital Library |
|---|---|
| Author | Zhifang Wang Scaglione, A. Thomas, R.J. |
| Copyright Year | 2010 |
| Description | Author affiliation: Department of Electrical and Computer Engineering, University of California, Davis, 95616 USA (Scaglione, A.) || Information Trust Institute, University of Illinois at Urbana-Champaign, 61801 USA (Zhifang Wang) || School of Electrical and Computer Engineering, Cornell University, Ithaca, NY 14850 USA (Thomas, R.J.) |
| Abstract | Centrality measures are used in network science to rank the relative importance of nodes and edges of a graph. Here we define new measures of centrality for power grid structure that are based on its functionality. We show that the relative importance analysis based on centrality in graph theory can be generalized to power grid network with its electrical parameters taken into account. In the paper we experiment with the proposed electrical centrality measures on the NYISO-2935 system and the IEEE 300-bus system. We analyze the centrality distribution in order to identify important nodes or branches in the system which are of essential importance in terms of system vulnerability. We also present and discuss a number of interesting discoveries regarding the importance rank of power grid nodes and branches. |
| Starting Page | 5792 |
| Ending Page | 5797 |
| File Size | 730662 |
| Page Count | 6 |
| File Format | |
| ISBN | 9781424477456 |
| ISSN | 07431546 |
| e-ISBN | 9781424477463 |
| DOI | 10.1109/CDC.2010.5717964 |
| Language | English |
| Publisher | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Publisher Date | 2010-12-15 |
| Publisher Place | USA |
| Access Restriction | Subscribed |
| Rights Holder | Institute of Electrical and Electronics Engineers, Inc. (IEEE) |
| Subject Keyword | Power grids Correlation Admittance Laplace equations Topology Network topology Power measurement |
| Content Type | Text |
| Resource Type | Article |
| Subject | Control and Optimization Control and Systems Engineering Modeling and Simulation |
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