Intelligent Anomaly Mitigation in Cyber-Physical Inverter-based Systems

被引:1
|
作者
Khan, Asad Ali [1 ]
Ahmed, Sara [1 ]
Beg, Omar A. [2 ]
机构
[1] Univ Texas San Antonio, Dept Elect Engn, San Antonio, TX 78249 USA
[2] Univ Texas Permian Basin, Dept Elect Engn, Odessa, TX 79762 USA
来源
2021 IEEE ENERGY CONVERSION CONGRESS AND EXPOSITION (ECCE) | 2021年
关键词
Artificial neural networks; cyber anomaly mitigation; distributed cooperative control; false data injection; microgrids; NEURAL-NETWORKS; MICROGRIDS;
D O I
10.1109/ECCE47101.2021.9595599
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The distributed cooperative controllers for inverter-based systems rely on communication networks that make them vulnerable to cyber anomalies. In addition, the distortion effects of such anomalies may also propagate throughout inverter-based cyber-physical systems due to the cooperative cyber layer. In this paper, an intelligent anomaly mitigation technique for such systems is presented utilizing data driven artificial intelligence tools that employ artificial neural networks. The proposed technique is implemented in secondary voltage control of distributed cooperative control-based microgrid, and results are validated by comparison with existing distributed secondary control and real-time simulations on real-time simulator OPAL-RT.
引用
收藏
页码:1301 / 1306
页数:6
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