Skip to main content
Article thumbnail
Location of Repository

Towards Efficient N-x Contingency Selection Using Group Betweenness Centrality

By Yousu Chen, Robert Adolf, David Haglin, Zhenyu Huang and Mark Rice

Abstract

Abstract—The goal of N − x contingency selection is to pick a subset of critical cases to assess their potential to initiate a severe crippling of an electric power grid. Even for a moderatesized system there can be an overwhelmingly large number of contingency cases that need to be studied. The number grows exponentially with x. This combinatorial explosion renders any exhaustive search strategy computationally infeasible, even for small to medium sized systems. We propose a novel method for N − x contingency selection for x ≥ 2 using group betweenness centrality and show that computation can be relatively decoupled from the problem size. Thus, making contingency analysis feasible for large systems with x ≥ 2. Consequently, it may be that N − x (for x ≥ 2) contingency selection can be effectively deployed despite the combinatorial explosion of the number of potential N − x contingencies. Keywords-Contingency analysis, group betweenness centrality, graph centrality I

Year: 2013
OAI identifier: oai:CiteSeerX.psu:10.1.1.352.3168
Provided by: CiteSeerX
Download PDF:
Sorry, we are unable to provide the full text but you may find it at the following location(s):
  • http://citeseerx.ist.psu.edu/v... (external link)
  • http://cass-mt.pnnl.gov/docs/p... (external link)
  • Suggested articles


    To submit an update or takedown request for this paper, please submit an Update/Correction/Removal Request.