This paper addresses a set-theoretic method for the detection of data corruption cyber-attacks on the load frequency control loop of a networked power system. The system consists of several interconnected control areas forming a power grid. Based on the overall discrete-time network dynamics, a convex and compact polyhedral robust invariant set is extracted and is used as a set-induced anomaly detector. If the state vector exits the invariant set, then an alarm will be activated, and the potential threat is considered disclosed. The attack scenario used to assess the efficiency of the proposed anomaly detector concerns corrupted frequency sensor measurements transmitted to the automatic generation control unit of a compromised control area. Simulation studies highlight the ability of a set-theoretic approach to disclose persistent and intermittent attack patterns even when they occur at the same time with changes in the power load demand.

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This article is concerned with modelling, controllability analysis and the design of aggressive robust controllers for interconnected electric power systems. The load/frequency controller relies on a pole clustering scheme and provides the fastest transient response despite any disturbance load application. The inherent saturation constraints are handled by the combination of a controller gain minimization scheme and an anti-windup enhanced controller design which provides stability guarantees, while avoiding frequency and tie-line power oscillations. For this scheme, particular attention should be paid on the modeling aspects of the power system. It is shown that due to the positive semidefinite graph-connection Laplacian of the system, a reduction of the state vector is necessary. Simulation studies are offered to illustrate the effectiveness of the suggested scheme.