LAUSR

The safe operation, control, and stability of standalone microgrids (MGs) are highly dependent on their coordination with the MG control center (MGCC). Due to the open communication channel between the MG and the MGCC, the measurement signals are vulnerable to cyber attacks that can compromise the stability of the system. In this article, a false data injection (FDI) attack on the frequency measurement of a standalone MG is considered to disrupt the stable operation of the MG. Therefore, an attack detection and identification method are proposed to protect the MG against the impacts of this attack. The proposed method is based on a dynamic state estimation technique that uses an unknown input observer (UIO) to estimate the MG states and generate a residual function that detects the presence of an FDI attack and triggers a detection alarm for attack isolation and mitigation. The robustness and practicability of the proposed method are demonstrated with real-time simulation results of a real-world MG system.