TY - GEN
T1 - Cascading effects of targeted attacks on the power grid
AU - Meyur, Rounak
AU - Vullikanti, Anil
AU - Marathe, Madhav V.
AU - Pal, Anamitra
AU - Youssef, Mina
AU - Centeno, Virgilio
N1 - Funding Information:
We thank the reviewers for their constructive comments. We also thank members of the Network Dynamics and Simulation Science Laboratory at Virginia Tech and Professor Arun Phadke and late Professor James Thorp for their collaboration and their insightful suggestions on topics related to the paper. This work has been partially supported by DTRA CNIMS (Contract HDTRA1-11-D-0016-0001), NSF DIBBS Grant ACI-1443054, NSF BIG DATA Grant IIS-1633028, NSF EAGER Grant CMMI-1745207 and DOE Grant DE-EE0007660.
Funding Information:
Acknowoledgements. We thank the reviewers for their constructive comments. We also thank members of the Network Dynamics and Simulation Science Laboratory at Virginia Tech and Professor Arun Phadke and late Professor James Thorp for their collaboration and their insightful suggestions on topics related to the paper. This work has been partially supported by DTRA CNIMS (Contract HDTRA1-11-D-0016-0001), NSF DIBBS Grant ACI-1443054, NSF BIG DATA Grant IIS-1633028, NSF EAGER Grant CMMI-1745207 and DOE Grant DE-EE0007660.
Publisher Copyright:
© 2019, This is a U.S. government work and not under copyright protection in the U.S.; foreign copyright protection may apply.
PY - 2019
Y1 - 2019
N2 - We study the resilience of real world power grids to targeted adversarial attacks. Prior blackouts have shown that failures in the power grid can cascade, starting from a single failure, leading to a large number of failed nodes. In this paper, we study the problem of identifying a set of k critical nodes, whose failure/attack leads to the maximum number of tripped nodes. There has been a lot of work on this problem, but it has been mainly restricted to simple networks and failure models with either steady state analysis or DC power flow. In this paper, we perform AC power flow based transient analysis on a detailed power grid model. We find that a simple greedy approach yields node sets with higher criticality than a degree based approach, which has been suggested in many prior works. Furthermore, we observe that the cascades exhibit a non-monotonic behavior as a function of k.
AB - We study the resilience of real world power grids to targeted adversarial attacks. Prior blackouts have shown that failures in the power grid can cascade, starting from a single failure, leading to a large number of failed nodes. In this paper, we study the problem of identifying a set of k critical nodes, whose failure/attack leads to the maximum number of tripped nodes. There has been a lot of work on this problem, but it has been mainly restricted to simple networks and failure models with either steady state analysis or DC power flow. In this paper, we perform AC power flow based transient analysis on a detailed power grid model. We find that a simple greedy approach yields node sets with higher criticality than a degree based approach, which has been suggested in many prior works. Furthermore, we observe that the cascades exhibit a non-monotonic behavior as a function of k.
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U2 - 10.1007/978-3-030-05411-3_13
DO - 10.1007/978-3-030-05411-3_13
M3 - Conference contribution
AN - SCOPUS:85059063457
SN - 9783030054106
T3 - Studies in Computational Intelligence
SP - 155
EP - 167
BT - Complex Networks and Their Applications VII - Volume 1 Proceedings The 7th International Conference on Complex Networks and their Applications COMPLEX NETWORKS 2018
A2 - Lambiotte, Renaud
A2 - Rocha, Luis M.
A2 - Lió, Pietro
A2 - Cherifi, Hocine
A2 - Aiello, Luca Maria
A2 - Cherifi, Chantal
PB - Springer Verlag
T2 - 7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018
Y2 - 11 December 2018 through 13 December 2018
ER -