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A Robust Policy for Automatic Generation Control Cyber Attack in Two Area Power Network


K. Margellos

IEEE Conference on Decision and Control, Atlanta, Georgia, USA

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. We demonstrate by simulations that, even though the resulting signals can indeed destabilize the system if the model and state information are perfect, the results are extremely sensitive to uncertainty. Motivated by this we then 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 potential disruption that the resulting policy can cause, as well as its robustness with respect to modeling uncertainty and imperfect state information.


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J. Lygeros

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