Cyber Attack Detection and Protection Control Technology for Smart Power Distribution and Utilization System：Developments and Challenges

doi:10.11985/2023.02.012

Abstract

Abstract:

The extensive application of advanced information technology in smart power distribution and utilization system(SPDUS) deepens the coupling degree between the information side of the system and the power physical side. Smart power distribution systems have been gradually transformed into smart power distribution and utilization cyber physical system(SPDU-CPS) with a high degree of integration of information-physical space. The research status at home and abroad from three perspectives of SPDU-CPS network attack intrusion detection, network attack defense and protection, and self-healing control is summarized and prospected. In the aspect of network attack intrusion detection, the detection ideas and implementation paths of network attack detection methods based on deviation class, feature class and hybrid class are summarized. In the aspect of network attack defense and protection, the information side protection method, the physical side protection method based on resource optimization allocation and data correction protection and the information physical cooperative protection method combining the information and protection functions of both sides are introduced. In the aspect of self-healing control, the existing researches on the traditional power physics self-healing control and the self-healing control based on information physics coordination are summarized and sorted out. Finally, the future research direction is prospected.

Key words: Smart power distribution and utilization system, cyber physical system, network attack intrusion detection, cyber attack defense protection, self-healing control

CLC Number:

TM561

ZENG Rong, LI Yong, CAO Yijia, XIE Liwei, SHAO Xia. Cyber Attack Detection and Protection Control Technology for Smart Power Distribution and Utilization System：Developments and Challenges[J]. Journal of Electrical Engineering, 2023, 18(2): 125-141.

Figures/Tables 5

References 114

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类型	优点	不足	未来研究方向	相关文献
AIDM	对已知或未知的网络攻击均具备较好的检测效果，漏报率低	需要针对特定系统进行调制，不便于规模化推广应用；具备相对高的误报率	AIDM检测阈值的一般化计算方法；无需人工定义检测阈值的AIDM	[49⇓⇓⇓⇓⇓⇓-56]
SIDM	对已记录行为特征的网络攻击具备较好的识别能力；不需要复杂的系统建模过程	需要相当数量与质量的电气数据进行训练；对未知网络攻击的识别能力存在局限，需要频繁手动更新数据特征库	小样本训练数据下的人工智能网络攻击检测技术；网络攻击特征库自动更新技术	[57⇓⇓⇓⇓⇓⇓⇓-65]
HIDM	对已知攻击的低误报率、对未知攻击的高检测准确率	未充分发挥不同类检测方法混合带来的检测能力提升	协调优化不同类型IDM的混合方式，挖掘HIDM潜在能力；研究匹配配电网与微电网系统特点的HIDM	[66⇓-68]