Cascading effects of targeted attacks on the power grid

Rounak Meyur, Anil Vullikanti, Madhav V. Marathe, Anamitra Pal, Mina Youssef, Virgilio Centeno

Research output: Chapter in Book/Report/Conference proceedingConference contribution

2 Scopus citations

Abstract

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.

Original languageEnglish (US)
Title of host publicationComplex Networks and Their Applications VII - Volume 1 Proceedings The 7th International Conference on Complex Networks and their Applications COMPLEX NETWORKS 2018
EditorsRenaud Lambiotte, Luis M. Rocha, Pietro Lió, Hocine Cherifi, Luca Maria Aiello, Chantal Cherifi
PublisherSpringer Verlag
Pages155-167
Number of pages13
ISBN (Print)9783030054106
DOIs
StatePublished - 2019
Event7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018 - Cambridge, United Kingdom
Duration: Dec 11 2018Dec 13 2018

Publication series

NameStudies in Computational Intelligence
Volume812
ISSN (Print)1860-949X

Other

Other7th International Conference on Complex Networks and their Applications, COMPLEX NETWORKS 2018
Country/TerritoryUnited Kingdom
CityCambridge
Period12/11/1812/13/18

ASJC Scopus subject areas

  • Artificial Intelligence

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