Visible to the public The sequential attack against power grid networks

TitleThe sequential attack against power grid networks
Publication TypeConference Paper
Year of Publication2014
AuthorsYihai Zhu, Jun Yan, Yufei Tang, Yan Sun, Haibo He
Conference NameCommunications (ICC), 2014 IEEE International Conference on
Date PublishedJune
Keywordscascading failure, failure analysis, Generators, IEEE 39 bus system, multiple failures, multiple network components, Power Grid Network, power grid networks, power grids, power system faults, Power system protection, sequential attack, sequential failure, Size measurement, Substations, test benchmark, time domain, time-domain analysis, vulnerability analysis
Abstract

The vulnerability analysis is vital for safely running power grids. The simultaneous attack, which applies multiple failures simultaneously, does not consider the time domain in applying failures, and is limited to find unknown vulnerabilities of power grid networks. In this paper, we discover a new attack scenario, called the sequential attack, in which the failures of multiple network components (i.e., links/nodes) occur at different time. The sequence of such failures can be carefully arranged by attackers in order to maximize attack performances. This attack scenario leads to a new angle to analyze and discover vulnerabilities of grid networks. The IEEE 39 bus system is adopted as test benchmark to compare the proposed attack scenario with the existing simultaneous attack scenario. New vulnerabilities are found. For example, the sequential failure of two links, e.g., links 26 and 39 in the test benchmark, can cause 80% power loss, whereas the simultaneous failure of them causes less than 10% power loss. In addition, the sequential attack is demonstrated to be statistically stronger than the simultaneous attack. Finally, several metrics are compared and discussed in terms of whether they can be used to sharply reduce the search space for identifying strong sequential attacks.

DOI10.1109/ICC.2014.6883387
Citation Key6883387