全球能源互联网（英文）2021，Vol.4Issue(2)：184-192,9.DOI:10.14171/j.2096-5117.gei.2021.02.007
电力系统中基于自适应衰落卡尔曼滤波器的动态负载变化攻击检测
Dynamic load-altering attack detection based on adaptive fading Kalman filter in power systems
摘要
Abstract
This paper presents an effective and feasible method for detecting dynamic load-altering attacks (D-LAAs) in a smart grid. First, a smart grid discrete system model is established in view of D-LAAs. Second, an adaptive fading Kalman filter (AFKF) is designed for estimating the state of the smart grid. The AFKF can completely filter out the Gaussian noise of the power system, and obtain a more accurate state change curve (including consideration of the attack). A Euclidean distance ratio detection algorithm based on the AFKF is proposed for detecting D-LAAs. Amplifying imperceptible D-LAAs through the new Euclidean distance ratio improves the D-LAA detection sensitivity, especially for very weak D-LAA attacks. Finally, the feasibility and effectiveness of the Euclidean distance ratio detection algorithm are verified based on simulations. Keywords: Adaptive fading Kalman filter, Dynamic load, Attack detection.关键词
自适应衰落卡尔曼滤波/动态负载/攻击检测Key words
Adaptive fading Kalman filter/Dynamic load, Attack detection引用本文复制引用
Qiang Ma,Zheng Xu,Wenting Wang,Lin Lin,Tiancheng Ren,Shuxian Yang,Jian Li..电力系统中基于自适应衰落卡尔曼滤波器的动态负载变化攻击检测[J].全球能源互联网（英文）,2021,4(2):184-192,9.基金项目
This work was supported by the Science and Technology Project of the State Grid Shandong Electric Power Company:Research on the vulnerability and prevention of the electrical cyber-physical monitoring system based on interdependent networks （）
the National Natural Science Foundation of China(61873057) （61873057）
and the Education Department of Jilin Province(JJKH20200118KJ). （JJKH20200118KJ）
