TY - GEN
T1 - Enhancing Power System Resilience with False Data Injection-Resistant Model Predictive Control
AU - Li, Pandeng
AU - Yang, Yiwei
AU - Liang, Zhihong
AU - Sun, Jun
AU - Xiao, Yuzhou
AU - Cui, Lingguo
N1 - Publisher Copyright:
© 2023 IEEE.
PY - 2023
Y1 - 2023
N2 - This paper proposes a resilient control scheme based on the set theory and model for cyber power systems subjected to network deception attacks. For the problem of deception attacks through false data injection (FDI) in the power system, this paper studies the model predictive control scheme that makes use of tube. Based on the characteristics of the robust positive invariant set that has been defined, an optimization problem (referred to as OP) is formulated to design the controller. The feasibility of this optimization problem and the practical stability of the controlled system are ensured. To demonstrate the efficacy of the proposed approach, a numerical simulation on cyber system is conducted on a power system. The results of the simulation serve as verification of the effectualness of the proposed scheme.
AB - This paper proposes a resilient control scheme based on the set theory and model for cyber power systems subjected to network deception attacks. For the problem of deception attacks through false data injection (FDI) in the power system, this paper studies the model predictive control scheme that makes use of tube. Based on the characteristics of the robust positive invariant set that has been defined, an optimization problem (referred to as OP) is formulated to design the controller. The feasibility of this optimization problem and the practical stability of the controlled system are ensured. To demonstrate the efficacy of the proposed approach, a numerical simulation on cyber system is conducted on a power system. The results of the simulation serve as verification of the effectualness of the proposed scheme.
KW - False data injection
KW - bounded disturbances
KW - input-to-state practical stability
KW - resilient model predictive control
UR - http://www.scopus.com/inward/record.url?scp=85189330465&partnerID=8YFLogxK
U2 - 10.1109/CAC59555.2023.10450173
DO - 10.1109/CAC59555.2023.10450173
M3 - Conference contribution
AN - SCOPUS:85189330465
T3 - Proceedings - 2023 China Automation Congress, CAC 2023
SP - 6707
EP - 6712
BT - Proceedings - 2023 China Automation Congress, CAC 2023
PB - Institute of Electrical and Electronics Engineers Inc.
T2 - 2023 China Automation Congress, CAC 2023
Y2 - 17 November 2023 through 19 November 2023
ER -