Department of Electrical and Electronics Engineering, Shiraz University of Technology, Shiraz 71557-13876, Iran.
Department of Electrical and Computer Engineering, University of Windsor, Sunset Ave., Windsor, ON N9B 3P4, Canada.
Sensors (Basel). 2022 Mar 30;22(7):2644. doi: 10.3390/s22072644.
This paper investigates the problem of false data injection attack (FDIA) detection in microgrids. The grid under study is a DC microgrid with distributed boost converters, where the false data are injected into the voltage data so as to investigate the effect of attacks. The proposed algorithm uses a bank of sliding mode observers that estimates the states of the neighbor agents. Each agent estimates the neighboring states and, according to the estimation and communication data, the detection mechanism reveals the presence of FDIA. The proposed control scheme provides resiliency to the system by replacing the conventional consensus rule with attack-resilient ones. In order to evaluate the efficiency of the proposed method, a real-time simulation with eight agents has been performed. Moreover, a verification experimental test with three boost converters has been utilized to confirm the simulation results. It is shown that the proposed algorithm is able to detect FDI attacks and it protects the consensus deviation against FDI attacks.
本文研究了微电网中虚假数据注入攻击（FDIA）的检测问题。所研究的电网是一个带有分布式升压转换器的直流微电网，其中虚假数据被注入到电压数据中，以研究攻击的影响。所提出的算法使用了一组滑模观测器，用于估计邻居代理的状态。每个代理估计相邻状态，并根据估计和通信数据，检测机制揭示了 FDIA 的存在。所提出的控制方案通过用攻击弹性的共识规则代替传统的共识规则，为系统提供了弹性。为了评估所提出方法的效率，对八个代理进行了实时仿真。此外，还利用三个升压转换器进行了验证实验测试，以确认仿真结果。结果表明，所提出的算法能够检测到 FDI 攻击，并保护共识偏差免受 FDI 攻击。
