Decentralized Resilient Finite-Time-Control for Large-Scale Power Systems via Dynamic Triggering Against Deception Attacks

• Published in: IEEE transactions on smart grid Vol. 14; no. 4; pp. 3210 - 3219
• Main Authors: Liu, Yuezhi, Chen, Yong
• Format: Journal Article
• Language: English
• Published: Piscataway IEEE 01.07.2023; The Institute of Electrical and Electronics Engineers, Inc. (IEEE)
• Subjects: Asymptotic stability; Closed loops; Control systems design; Controllers; Convergence; decentralized resilient finite-time control; deception attacks; dynamic event-triggered mechanism; Generators; Large-scale power system; Neural networks; Power system dynamics; Power system stability; Resilience; Synchronous generators; Synchronous machines; Vehicle dynamics
• ISSN: 1949-3053; 1949-3061
• DOI: 10.1109/TSG.2023.3249210

This paper investigates the decentralized resilient finite-time control with the dynamic event-triggered mechanism for the large-scale power systems subject to deception attacks. Firstly, to save the network resource of the interconnected synchronous generators, the decentralized dynamic event-triggered mechanism (DDETM) is formulated, with the aid of the internal variable, the conservatism of the triggering condition is reduced. Secondly, to improve the resilience of the large-scale power system with respect to the deception attacks, the decentralized resilient finite-time controller (DRFTC) is constructed, in which, the sign function is applied in the controller design and the neural-network adaptive law formulation, obtaining faster convergence rate and precision. It is shown moreover that fast finite-time stability of the closed-loop power system can be obtained. Finally, simulation results manifest the validity of the proposed decentralized resilient finite-time controller.