Title
Joint Substation-Transmission Line Vulnerability Assessment Against the Smart Grid
Abstract
Power grids are often run near the operational limits because of increasing electricity demand, where even small disturbances could possibly trigger major blackouts. The attacks are the potential threats to trigger large-scale cascading failures in the power grid. In particular, the attacks mean to make substations/transmission lines lose functionality by either physical sabotages or cyber attacks. Previously, the attacks were investigated from substation-only/transmission-line-only perspectives, assuming attacks can occur only on substations/transmission lines. In this paper, we introduce the joint substation-transmission line perspective, which assumes attacks can happen on substations, transmission lines, or both. The introduced perspective is a nature extension to substation-only and transmission-line-only perspectives. Such extension leads to discovering many joint substation-transmission line vulnerabilities. Furthermore, we investigate the joint substation-transmission line attack strategies. In particular, we design a new metric, the component interdependency graph (CIG), and propose the CIG-based attack strategy. In simulations, we adopt IEEE 30 bus system, IEEE 118 bus system, and Bay Area power grid as test benchmarks, and use the extended degree-based and load attack strategies as comparison schemes. Simulation results show the CIG-based attack strategy has stronger attack performance.
Year
DOI
Venue
2015
10.1109/TIFS.2015.2394240
IEEE Trans. Information Forensics and Security
Keywords
Field
DocType
The smart grid, security, attack, cascading failures, vulnerability analysis
Interdependence,Smart grid,Transmission line,Computer science,Computer security,Vulnerability assessment,Electric power transmission,Cascading failure,Power-system protection,Vulnerability
Journal
Volume
Issue
ISSN
10
5
1556-6013
Citations 
PageRank 
References 
8
0.50
18
Authors
5
Name
Order
Citations
PageRank
Yihai Zhu119511.74
Jun Yan217913.72
Yufei Tang320322.83
Yan Sun41124119.96
Haibo He53653213.96