A robust policy for Automatic Generation Control cyber attack in two area power network

This paper develops methodologies to robustly destabilize a two-area power system in the case of a cyber attack in the Automatic Generation Control (AGC). In earlier work reachability methods were used to establish conditions under which an attacker can cause undesirable behavior by interrupting the AGC signals and introducing an appropriate fake signal. In this paper we investigate how to robustify this approach to deal with practical situations where the attacker only has partial information about the parameters of the power system and the values of its states. We first propose an open loop procedure, based on Markov Chain Monte Carlo optimization, to identify an optimal attack signal. Motivated by the fact that the results are very sensitive to parameter uncertainty, we develop a systematic algorithm, based on feedback linearization, to construct a feedback policy that an intruder may use to disrupt the network. The numerical simulations demonstrate the effectiveness of the resulting policy, as well as its robustness with respect to modeling uncertainty and imperfect state information.