Fast Screening of High-Risk Lines Under False Data Injection Attacks

False data injection attacks can compromise power system operational security by causing severe branch overloads. A set of transmission lines can be more vulnerable to the attack. These lines can be quickly identified by a high-risk line fast screening (HLFS) approach proposed in this paper. The HLFS has a high computational efficiency which facilitates its applications in large-scale systems. In the meantime, for an indepth security assessment, a critical-line identification tool is also presented to identify a subset of critical lines with simultaneous tripping risk under the attack. The effectiveness and efficiency of the proposed approach are verified by benchmarking its performance against a basic linear-programming checking method in the case study which includes simulations on multiple large-scale MATPOWER cases.