DocumentCode :
1735842
Title :
The Topological and Electrical Structure of Power Grids
Author :
Hines, P. ; Blumsack, S. ; Sanchez, E. Cotilla ; Barrows, C.
fYear :
2010
Firstpage :
1
Lastpage :
10
Abstract :
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 of the IEEE 300 bus and the Eastern United States power grids. Specifically we compare the topology of these grids with that of random, preferential-attachment and small-world networks of equivalent sizes and find that power grids differ substantially from these abstract models in degree distribution, clustering, diameter and assortativity, and thus conclude that these abstract models do not provide substantial utility for modeling power grids. To better represent the topological properties of power grids we introduce a new , the minimum distance graph, that produces networks with properties that more nearly match those of known power grids. While these topological comparisons are useful, they do not account for the physical laws that govern flows in electricity networks. To elucidate the electrical structure of power grids, we propose a new method for representing electrical structure as a weighted graph. This analogous representation is based on electrical distance rather than topological connections. A comparison of these two representations of the test power grids reveals dramatic differences between the electrical and topological structure of electrical power systems.
Keywords :
graph theory; power grids; risk analysis; Eastern United States power grids; IEEE 300 bus; electrical distance; graph generating algorithm; minimum distance graph; power grid electrical structure; power grid modelling; power grid topological structure; preferential-attachment network; random network; risk identification method; risk mitigation method; small-world network; weighted graph; Clustering algorithms; Complex networks; Diseases; IP networks; Mesh generation; Network topology; Power generation; Power grids; Power measurement; System testing;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
System Sciences (HICSS), 2010 43rd Hawaii International Conference on
Conference_Location :
Honolulu, HI
ISSN :
1530-1605
Print_ISBN :
978-1-4244-5509-6
Electronic_ISBN :
1530-1605
Type :
conf
DOI :
10.1109/HICSS.2010.398
Filename :
5428366
Link To Document :
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