Kalman Filters Based Distributed Cyber-Attack Mitigation Layers for DC Microgrids

El-Ebiary, Ahmed H.; Attia, Mahmoud A.; Awad, Fathy H.; Mostafa Ibrahim Mohamed Marei; Mokhtar, Mohamed;

Abstract


The use of communication links between microgrid components has made the transmitted data vulnerable to cyber-attacks. This paper presents distributed cyber-attack detection and mitigation layers integrated with the primary and secondary control loops of a meshed DC microgrid. Voltage and current cyber-attacks mitigation layers based on the Kalman Filter (KF), as a robust state estimator, are proposed. The KF is utilized to estimate accurately the actual authentic terminal voltage and current from the measurable system states. Using the discrepancies between the estimated data and the measurements under cyber-attack, controllers are assigned to set proper corrective actions. These actions secure the primary and secondary loops to achieve accurate terminal voltage regulation and current sharing, respectively, for all Distributed Generator Units (DGUs) in the microgrid. Not only accurate state estimation is required for perfect cyber-attack mitigation, but fast control response is crucial. Therefore, Adaptive Proportional Integral (API) and Fractional API (FAPI) controllers are proposed for cyber-attack mitigation layers. Simulation results are provided to evaluate the dynamic performance of the proposed strategy. Moreover, experimental work is conducted to verify the effectiveness of the proposed distributed layers and the superiority of the FAPI controller in terms of perfect compensation for different types of cyber-attacks.


Other data

Title Kalman Filters Based Distributed Cyber-Attack Mitigation Layers for DC Microgrids
Authors El-Ebiary, Ahmed H.; Attia, Mahmoud A.; Awad, Fathy H.; Mostafa Ibrahim Mohamed Marei ; Mokhtar, Mohamed 
Keywords Adaptive controllers;cyber-attack mitigation;DC microgrids;state estimation
Issue Date 1-Mar-2024
Journal IEEE Transactions on Circuits and Systems I: Regular Papers 
Volume 71
Issue 3
ISSN 15498328
DOI 10.1109/TCSI.2023.3348928
Scopus ID 2-s2.0-85184826643

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