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Vulnerability assessment for cascading failures in electric power systems
Authors: David Hawkins; Juan Li; Kai Sun; Ian Dobson; Milorad Papic; Hongbin Sun; Fangxing Li; +24 Authors
David Hawkins; Juan Li; Kai Sun; Ian Dobson; Milorad Papic; Hongbin Sun; Fangxing Li; Robin Podmore; Janghoon Kim; Daniel S. Kirschen; Zhigang Wu; Xiaochuan Luo; Marvin K. Nakayama; Zhenyu Huang; Zhao Yang Dong; Stephen J. Miller; Chen-Ching Liu; Wenjie Zhang; Badrul H. Chowdhury; Lamine Mili; Bei Gou; Ross Baldick; Pei Zhang; Xiao-Ping Zhang; Kevin P. Schneider; Stephen T. Lee; David Wang; Liangzhong Yao; John Rossmaier; Zuyi Li; Manho Joung;
Abstract
Cascading failures present severe threats to power grid security, and thus vulnerability assessment of power grids is of significant importance. Focusing on analytic methods, this paper reviews the state of the art of vulnerability assessment methods in the context of cascading failures. These methods are based on steady-state power grid modeling or high-level probabilistic modeling. The impact of emerging technologies including phasor technology, high-performance computing techniques, and visualization techniques on the vulnerability assessment of cascading failures is then addressed, and future research directions are presented.
Related Organizations
- University of Queensland Australia
- The University of Texas at Austin United States
- University of Tennessee at Knoxville United States
- Iowa State University United States
- Tennessee State University United States
citations This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).78 popularity This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.Top 10% influence This indicator reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).Top 10% impulse This indicator reflects the initial momentum of an article directly after its publication, based on the underlying citation network.Top 10%

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citations
Citations provided by BIP!
This is an alternative to the "Influence" indicator, which also reflects the overall/total impact of an article in the research community at large, based on the underlying citation network (diachronically).
popularity
Popularity provided by BIP!
This indicator reflects the "current" impact/attention (the "hype") of an article in the research community at large, based on the underlying citation network.
78
Top 10%
Top 10%
Top 10%
Fields of Science (3) View all
Related to Research communities
Energy Research