Euclidean Detector Based Cyber Attack Detection in Automatic Generation Control

Automatic Generation Control (AGC) system is employed in power system to keep the system frequency within specified limits. Change in system frequency out of the prescribed range may interrupt the operation of the grid and cause damage to electrical equipment. Todays' grid consists of smart cyber physical system. The coordination of the constituent parts of the smart grid may be disturbed by manipulating the communication among the control system, actuators and sensors through cyber attacks. Denial-of-service and false data injection attacks may be employed to compromise the security of smart grids. Therefore, it is necessary to protect the AGC from such attacks in order to maintain the security and reliability of the power system. This paper proposes an approach employing Kalman filter along with Euclidean detector to detect such attacks. The Kalman filter is applied to estimate the state variables of the system. The state estimates and the system measurements are then utilized by the Euclidean detector to discern cyber attacks.