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Physical consequences to power systems of false data injection cyber-attacksare considered. Prior work has shown that the worst-case consequences of suchan attack can be determined using a bi-level optimization problem, wherein anattack is chosen to maximize the physical power flow on a target linesubsequent to re-dispatch. This problem can be solved as a mixed-integer linearprogram, but it is difficult to scale to large systems due to numericalchallenges. Three new computationally efficient algorithms to solve thisproblem are presented. These algorithms provide lower and upper bounds on thesystem vulnerability measured as the maximum power flow subsequent to anattack. Using these techniques, vulnerability assessments are conducted forIEEE 118-bus system and Polish system with 2383 buses.

Evaluating Power System Vulnerability to False Data Injection Attacks via Scalable Optimization