Resilient Decentralized Frequency Regulation for Multi-Area Power Systems With Electric Vehicles Under Hybrid Cyber-Attacks

This paper proposes a resilient output-feedback frequency regulation mechanism for multi-area power systems, ensuring secure and stable operation. Firstly, the uncertainties introduced by state-of-charge (SOC) variations are considered for the addressed system involved electric vehicle (EV). Subsequently, the behavior of hybrid replay-DoS attacks is taken into account, where a non-homogeneous Markov jump framework is employed to capture both stochastic transitions and temporal dependencies of attack behaviors, and a decentrilized resilient controller is designed to mitigate these adverse effects. To facilitate controller synthesis, a refined model of the lossless power network is further developed by equivalently transforming tie-line power deviations in specific areas, ensuring compliance with tie-line power constraints while preserving system controllability. Based on this model, a comprehensive analysis of system dynamics is performed, and a set of delay-dependent, computationally tractable criteria is derived for controller gain selection. Finally, extensive simulations on three-area power systems validate the effectiveness of the proposed strategy in maintaining frequency stability, mitigating SOC uncertainties, and counteracting hybrid replay-DoS attacks.

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Publication Details

Journal
IEEE Transactions on Circuits and Systems I Regular Papers
Published
2025-05-14
DOI
https://doi.org/10.1109/tcsi.2025.3563209
Citations
5
Primary Topic
Smart Grid Security and Resilience
Type
article
Field-Weighted Citation Impact
6.07

Funders

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article

Resilient Decentralized Frequency Regulation for Multi-Area Power Systems With Electric Vehicles Under Hybrid Cyber-Attacks

Tieshan Li, Yue Long, Derui Ding, Qidong Liu
5 citations
IEEE Transactions on Circuits and Systems I Regular Papers
Smart Grid Security and Resilience
6.07
article

Resilient Decentralized Frequency Regulation for Multi-Area Power Systems With Electric Vehicles Under Hybrid Cyber-Attacks

Tieshan Li, Yue Long, Derui Ding, Qidong Liu
article en
5 citations

Abstract

This paper proposes a resilient output-feedback frequency regulation mechanism for multi-area power systems, ensuring secure and stable operation. Firstly, the uncertainties introduced by state-of-charge (SOC) variations are considered for the addressed system involved electric vehicle (EV). Subsequently, the behavior of hybrid replay-DoS attacks is taken into account, where a non-homogeneous Markov jump framework is employed to capture both stochastic transitions and temporal dependencies of attack behaviors, and a decentrilized resilient controller is designed to mitigate these adverse effects. To facilitate controller synthesis, a refined model of the lossless power network is further developed by equivalently transforming tie-line power deviations in specific areas, ensuring compliance with tie-line power constraints while preserving system controllability. Based on this model, a comprehensive analysis of system dynamics is performed, and a set of delay-dependent, computationally tractable criteria is derived for controller gain selection. Finally, extensive simulations on three-area power systems validate the effectiveness of the proposed strategy in maintaining frequency stability, mitigating SOC uncertainties, and counteracting hybrid replay-DoS attacks.

IEEE Transactions on Circuits and Systems I Regular PapersVol. 72(11)
University of Shanghai for Science and Technology (CN), University of Electronic Science and Technology of China (CN)
National Natural Science Foundation of China, Fundamental Research Funds for the Central Universities
Affordable and clean energy
Openalex Percentile: Top 4%
Smart Grid Security and Resilience
6.07
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Resilient Decentralized Frequency Regulation for Multi-Area Power Systems With Electric Vehicles Under Hybrid Cyber-Attacks — Tieshan Li, Yue Long, et al. · IEEE Transactions on Circuits and Systems I Regular Papers (2025) | TGRS Research Map | TGRS