Smart Cyber-Attack Diagnosis and Mitigation in a Wind Farm Network Operator

被引:8
|
作者
Badihi, Hamed [1 ]
Jadidi, Saeedreza [2 ]
Yu, Ziquan [1 ]
Zhang, Youmin [2 ]
Lu, Ningyun [1 ]
机构
[1] Nanjing Univ Aeronaut & Astronaut, Coll Automat Engn, Nanjing 211106, Peoples R China
[2] Concordia Univ, Dept Mech Ind & Aerosp Engn, Montreal, PQ H3G1M8, Canada
基金
中国国家自然科学基金; 加拿大自然科学与工程研究理事会;
关键词
Cyberattack; fuzzy modeling and identification (FMI); intrusion detection; wind farm; wind turbine; SECURITY; MODEL;
D O I
10.1109/TII.2022.3228686
中图分类号
TP [自动化技术、计算机技术];
学科分类号
0812 ;
摘要
With the rise of wind energy production in global power generation, wind farm facilities are becoming increasingly attractive targets for malicious attacks, in particular those affecting wind farm network operators' cybersubsystems and functionalities. Given the significance of this problem, this article proposes a novel anomaly-based intrusion detection and diagnosis system to carry out in-line monitoring as with firewalls. Also, an innovative cyberattack-resilient active power control is designed to responsively mitigate the impacts of cyberattacks on the safe regulation of active power from wind farms. An offshore wind farm benchmark is used to implement and demonstrate the effectiveness of the proposed solutions in the presence of wind turbulences, measurement noises and realistic smart cyberattack scenarios.
引用
收藏
页码:9468 / 9478
页数:11
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