Real-Time Detection and Location of Sensor FDI Attacks in DC Networked Microgrids under Distributed Layered Control Architecture

A networked microgrid (NMG) system can integrate individual microgrids (MGs) to further enhance system resilience against extreme events. However, due to the widespread use of sensors and the close interaction between cyber and physical layers, the NMG system is vulnerable to sensor attacks. This paper proposes a new detection and location scheme for sensor false data injection (FDI) attacks in DC NMG. Firstly, a DC NMG system and the adopted layered control are introduced. Then, the sensor FDI attack model is developed, and the attack impact is systematically analyzed by time-domain simulation. Based on a dynamic watermarking-based Kalman filter detection method, a real-time detection and location scheme that contains two-layer detectors is proposed. The upper-layer MG detector is implemented in each MG, enabling each MG to judge whether there is a sensor FDI attack within the MG, and the lower-layer DG detector is implemented in each DG, which can further locate the malicious sensor FDI attack. The proposed scheme utilizes the NMG dynamic characteristics to design the detectors by selecting a certain sub-module model as the plant. Through theoretical analysis, the detection effectiveness is validated and improved over the existing method. The controller-hardware-inloop experiment based on the OPAL-RT platform fully validates the designed scheme's effectiveness and superiority.