Cyber-Physical Attack Conduction and Detection in Decentralized Power Systems
Abstract
The expansion of power systems over large geographical areas renders centralized processing inefficient. Therefore, the distributed operation is increasingly adopted. This work introduces a new type of attack against distributed state estimation of power systems, which operates on inter-area boundary buses. We show that the developed attack can circumvent existing robust state estimators and the convergence-based detection approaches. Afterward, we carefully design a deep learning-based cyber-anomaly detection mechanism to detect such attacks. Simulations conducted on the IEEE 14-bus system reveal that the developed framework can obtain a very high detection accuracy. Moreover, experimental results indicate that the proposed detector surpasses current machine learning-based detection methods.
Authors
Mostafa Mohammadpourfard, Yang Weng, Abdullah Khalili, Istemihan Genc, Alireza Shefaei, Behnam Mohammadi-Ivatloo
Keywords
Power systems, State estimation, Power measurement, Optimization, Area measurement, Microgrids, Real-time systems
Publication Type
Journal Article
Digital Object Identifier
https://doi.org/10.1109/ACCESS.2022.3151907
Full Citation
Mohammadpourfard, M., Weng, Y., Khalili, A., Genc, I., Shefaei, A., & Mohammadi-Ivatloo, B. (2022). Cyber-physical attack conduction and detection in decentralized power systems. IEEE Access, 10, 29277-29286.
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