Detection of cyber attack in smart grid: A Comparative Study

• Published in: 2022 IEEE 20th International Power Electronics and Motion Control Conference (PEMC) pp. 48 - 54
• Main Authors: Xiao, Junjie, Wang, Lu, Qin, Zian, Bauer, Pavol
• Format: Conference Proceeding
• Language: English
• Published: IEEE 25-09-2022
• Subjects: Cyber attack detection; Detectors; Euclidean distance; Kalman filter; Kalman filters; Power electronics; Security; Sensor systems; smart grid; Smart grids; State estimate
• ISSN: 2473-0165
• DOI: 10.1109/PEMC51159.2022.9962902

Smart grid steady control relies heavily on the communication infrastructure among sensors, actuators, and control systems, which makes it vulnerable to cyber-attacks. Accurate acquisition of dynamic state information is deemed vital for efficient detection of these cyber-attacks on a smart grid. However, several popular state estimation methods at the present stage are restricted in practical use and require some assumptions. In this paper, we investigate the security of smart grid systems. We (1) identify and define the security problem in the smart grid, (2) compare the performance of several state estimate methods including Least Square, Kalman filter, Extend Kalman filter, in identifying smart grid dynamic information using measurements, and (3) investigate the Chi-square detector, Euclidean Distance, and Cosine similarity matching approaches for attack detection.