Secure State Estimation of DC Microgrid System Under False Data Injection Attack

Abstract

In DC microgrids, distributed secondary control plays an important role in maintaining power distribution and voltage recovery. However, distributed control architecture is vulnerable to external attacks, especially false data injection (FDI) attacks. To solve the problem of the controller being attacked, a distributed Kalman filter is proposed to estimate the attack signals and states. In addition, a compensation mechanism is adopted to defend against attacks and improve system resilience. Finally, the effectiveness of the proposed method is verified in the scenario of time-varying attack and load switching. The results show that the proposed method can effectively suppress potential external attacks and ensure the system’s stability.

Keywords

• DC microgrid
• distributed Kalman filter
• discrete attack modeling
• attack compensation