期刊论文详细信息
IEEE Access
Dynamic State Estimation of Generators Under Cyber Attacks
Liang Chen1  Yang Li2  Zhi Li2 
[1] School of Automation, Nanjing University of Information Science and Technology, Nanjing, China;School of Electrical Engineering, Northeast Electric Power University, Jilin City, China;
关键词: Dynamic state estimation;    cyber attacks;    false data injection;    denial of service;    generator;    robust cubature Kalman filter;   
DOI  :  10.1109/ACCESS.2019.2939055
来源: DOAJ
【 摘 要 】

Accurate and reliable estimation of generator's dynamic state vectors in real time are critical to the monitoring and control of power systems. A robust Cubature Kalman Filter (RCKF) based approach is proposed for dynamic state estimation (DSE) of generators under cyber attacks in this paper. First, two types of cyber attacks, namely false data injection and denial of service attacks, are modelled and thereby introduced into DSE of a generator by mixing the attack vectors with the measurement data; Second, under cyber attacks with different degrees of sophistication, the RCKF algorithm and the Cubature Kalman Filter (CKF) algorithm are adopted to the DSE, and then the two algorithms are compared and discussed. The novelty of this study lies primarily in our attempt to introduce cyber attacks into DSE of generators. The simulation results on the IEEE 9-bus system and the New England 16-machine 68-bus system verify the effectiveness and superiority of the RCKF.

【 授权许可】

Unknown   

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