A Novel Bilevel False Data Injection Attack Model Based on Pre-and Post-Dispatch

Journal Article (2022)
Author(s)

Shibin Gao (Southwest Jiaotong University)

Jieyu Lei (Southwest Jiaotong University)

Xiaoguang Wei (Southwest Jiaotong University)

Y. Liu (TU Delft - Intelligent Electrical Power Grids)

Tao Wang (Xihua University)

Research Group
Intelligent Electrical Power Grids
Copyright
© 2022 Shibin Gao, Jieyu Lei, Xiaoguang Wei, Y. Liu, Tao Wang
DOI related publication
https://doi.org/10.1109/TSG.2022.3156445
More Info
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Publication Year
2022
Language
English
Copyright
© 2022 Shibin Gao, Jieyu Lei, Xiaoguang Wei, Y. Liu, Tao Wang
Research Group
Intelligent Electrical Power Grids
Bibliographical Note
Green Open Access added to TU Delft Institutional Repository 'You share, we take care!' - Taverne project https://www.openaccess.nl/en/you-share-we-take-care Otherwise as indicated in the copyright section: the publisher is the copyright holder of this work and the author uses the Dutch legislation to make this work public.@en
Issue number
3
Volume number
13
Pages (from-to)
2487-2490
Reuse Rights

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Abstract

This letter develops a new bilevel optimization model to construct false data injection attack based on pre- and post- dispatch. In order to enhance the attack concealment, the proposed bilevel model can minimize the variation of uploaded measurements between pre- and post-attack before dispatching, after which the attack can lead the system to an uneconomic and insecure operating state after dispatching. Simulation results validate the effectiveness of the proposed bilevel model in term of operating cost and network overloads.

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