Forecasting-Aided Imperfect False Data Injection Attacks Against Power System Nonlinear State Estimation

This letter proposes an imperfect false data injection attack model and its corresponding forecasting-aided implementation method against the nonlinear power system state estimation by introducing an attack vector relaxing error. The upper bound of the relaxing error within the method is presented through theoretical analysis. Simulation experiments on the IEEE 30-bus system show that the proposed method works well both to the nonlinear model and to the dc model. In this letter, both single and multiple state variables attacks are considered.