A Secure Time-Based Bad Data Detection Algorithm for State Estimation

Conventional state estimation (SE), which is essential for energy management systems (EMS), has been proven vulnerable to a crafted false data injection attack (FDIA). This research investigates the formulation of FDIA and shows that the attack utilizes the fact that the exact measurements vector is used by the SE and bad data detector but at different time stamps (before and after the execution of the state estimation process). This paper proposes a time-based bad data detection (TB-BDD) algorithm that detects the FDIA. The proposed algorithm is validated in real-time environments to verify the algorithm's effectiveness, which can be deployed in the EMS without a significant change to the SE framework.