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

Journal article (2022)

Authors

Shibin Gao Southwest Jiaotong University
Jieyu Lei Southwest Jiaotong University
Xiaoguang Wei Southwest Jiaotong University
Y. Liu Intelligent Electrical Power Grids - EEMCS
Tao Wang Xihua University
Research Group
Intelligent Electrical Power Grids (EEMCS) (TU Delft)
Copyright: © 2022 Shibin Gao, Jieyu Lei, Xiaoguang Wei, Y. Liu, Tao Wang
DOI: https://doi.org/10.1109/TSG.2022.3156445
More Info
expand_more

Published Date

2022

Language

English

Reuse Rights

Other than for strictly personal use, it is not permitted to download, forward or distribute the text or part of it, without the consent of the author(s) and/or copyright holder(s), unless the work is under an open content license such as Creative Commons.

Faculty

Electrical Engineering, Mathematics and Computer Science

Department

Electrical Sustainable Energy

Research Group

Intelligent Electrical Power Grids

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.

Files

A_Novel_Bilevel_False_Data_Inj... (pdf)
(pdf | 1.17 Mb)
- Embargo expired in 01-07-2023
Unknown license