Cyber-attack localisation and tolerant control for microgrid energy management system based on set-membership estimation

Abstract

This paper addresses the cyber-security issue of microgrid energy management system, where cyber-attacks, appearing in communication networks, corrupt the transmitted data and falsify the state estimates. This can potentially threaten the physical system and lead to severe physical consequences. Therefore, it is of great significance to detect, locate and tolerate cyber-attacks. To this end, set-membership estimation is employed to detect the occurrence and locate the position of DoS attacks. The model predictive control technique is utilised to schedule the energy management by using the forecasts of photovoltaic generation and load demand. It is shown that the cyber-attack localisation and the desired tolerant control performance against attacks can be both achieved. Simulation results are provided to demonstrate the effectiveness of the proposed strategy.

Keywords:

• Energy management system
• cyber security
• multi-microgrid system
• model predictive control
• set-membership estimation

Acknowledgments

This work was supported by the Griffith University Publication Assistance Scholarship (PAS), Australian Research Council Discovery Project (DP160103567), and Australian Research Council Linkage Project (LP190101251).

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Notes on contributors

Quanwei Qiu

Quanwei Qiu received the B.Eng. degree in electrical engineering and automation from East China University of Science and Technology, Shanghai, China in 2013. From 2013-2016, he was enrolled in a combined master's and Ph.D. program in control science and engineering with East China University of Science and Technology. In 2020, he obtained his Ph.D. degree in electrical and electronic engineering with Griffith University, Gold Coast, Australia. His research interests include networked control systems, model predictive control, power electronics and energy storage management in microgrids.

Fuwen Yang

Fuwen Yang received the Ph.D. degree in control engineering from Huazhong University of Science and Technology, China, in 1990. He is currently an Associate Professor at Griffith University, Australia. Before joining Griffith, he was a Research Fellow at Brunel University and King's College London, UK, a Professor at Fuzhou University and East China University of Science and Technology, China, and an Associate Professor at Central Queensland University, Australia. He also held a Visiting Professor at the University of Manchester, UK, and the University of Hong Kong, Hong Kong. His current research interests include networked control systems, distributed filtering and sensing, reliable fault detection and diagnosis, distributed control and filtering, microgrids with renewable energy integration, and robot imitation learning for healthcare. He is an Associate Editor of IEEE Industrial Electronics Magazine, Frontiers in Energy Research-Smart Grids, the Journal of the Franklin Institute, and the IEEE CSS Conference Editorial Board.

Yong Zhu

Yong Zhu received a Ph.D. degree in Microelectronics from the Peking University, Beijing, China, in 2005. He worked as a Research Associate in the Department of Engineering, University of Cambridge, UK, in 2006 and 2007. From 2008 to 2011, he was a Research Academic in the School of Electrical Engineering and Computer Science, the University of Newcastle, Australia. Currently he holds a Senior Lecturer position at the School of Engineering and Built Environment, Griffith University, Australia. His research interests include Nano/Microelectromechanical Systems (N/MEMS) analysis and design, micro-fabrication, robust control of micro-actuators, as well as interface circuits design for micro-sensors.