Volume 16, Issue 3 (September 2020)
IJEEE 2020, 16(3): 279-291 |
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Abstract: (2482 Views)
Kalman filtering has been widely considered for dynamic state estimation in smart grids. Despite its unique merits, the Kalman Filter (KF)-based dynamic state estimation can be undesirably influenced by cyber adversarial attacks that can potentially be launched against the communication links in the Cyber-Physical System (CPS). To enhance the security of KF-based state estimation, in this paper, the basic KF-based method is enhanced by incorporating the dynamics of the attack vector into the system state-space model using an observer-based preprocessing stage. The proposed technique not only immunizes the state estimation against cyber-attacks but also effectively handles the issues relevant to the modeling uncertainties and measurement noises/errors. The effectiveness of the proposed approach is demonstrated by detailed mathematical analysis and testing it on two well-known IEEE cyber-physical test systems.
Keywords: Cyber Attack (CA) , Cyber-Physical System (CPS) , Kalman Filter (KF) , Smart Grid , Synchronous Machine
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- The problem of the power system dynamic state estimation under cyber-attacks is studied in this paper.
- A unique feature of the proposed method is its ability in the estimation of the attack vector.
- By obtaining the dynamics of the attack vector using an unknown input observer, a new augmented system model is derived in this paper.
- The effects of cyber-attacks, modeling uncertainties, and modeling noises are decoupled and separately considered in the proposed approach, which increases the estimation accuracy.
- Detail mathematical analysis and several simulations demonstrate the effectiveness of the proposed method.
Type of Study: Research Paper |
Subject:
Phasor Measurement Unit (PMU) Systems
Received: 2019/09/25 | Revised: 2020/02/19 | Accepted: 2020/02/28
Received: 2019/09/25 | Revised: 2020/02/19 | Accepted: 2020/02/28
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