Resilient control of multi-microgrids against false data injection attack. (April 2021)

• Record Type: Journal Article
• Authors: Yassaie, Negar; Hallajiyan, Mohammadreza; Sharifi, Iman; Talebi, H.A.
• Is Part Of: ISA transactions. Volume 110(2021)
• Page Start: 238
• Page End: 246
• Publication Date: 2021-04
• Subjects: Multi-microgrid -- Consensus -- Weighted mean subsequence reduced -- Multi-agent system -- Resilient control; Engineering instruments -- Periodicals; Engineering instruments; Periodicals; Electronic journals; 629.805
• DOI: 10.1016/j.isatra.2020.10.030
• Languages: English
• ISSNs: 0019-0578

Abstract

Abstract: A multi-microgrid system, including several microgrids and distributed energy resources, is always threatened by numbers of faults and attacks as a consequence of which malfunctioning can occur on a large scale. Thus, minimizing the effects of such disruptions is of paramount importance. This paper addresses the problem of mitigating a multi-microgrid system that faces false data injection and replay attacks by considering the multi-microgrid as a multi-agent system in which each microgrid as an agent represents a node in a weighted directed graph. The problem of consensus among normal agents is studied when microgrids and their communications are attacked. The malicious agents become isolated with the help of Weighted Mean Subsequence Reduced (W-MSR) algorithms in which all normal agents neglect the extreme values received from their neighbors. The proposed controller is able to maintain the system's desired performance when false data is injected into the system, or valid data is received with time-delays. Finally, numerical examples and simulation results are provided. Highlights: Multi-microgrid systems, including several microgrids and distributed energy resources are investigated. The proposed method considers numbers of faults and attacks as a consequence of which malfunctioning can occur on a large scale. False data injection and replay attack by considering the multi-microgrid as a multi-agent system is considered and the effects are minimized. The malicious agents become isolated with the help of Weighted Mean Subsequence Reduced (W-MSR) algorithms. The proposed controller is able to maintain the system's desired performance when false data is injected to the system or valid data is received with time-delays.