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arXiv 1909.01153eess.SYcs.SYeess.SP
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网络攻击下发电机动态状态估计

Dynamic State Estimation of Generators Under Cyber Attacks

Yang Li, Zhi Li, Liang Chen

摘要:

实时、准确、可靠地估计发电机的动态状态矢量是电力系统监测和控制的关键。针对网络攻击下发电机动态状态估计问题,提出了一种基于立方卡尔曼滤波器的鲁棒状态估计方法。首先,对虚假数据注入和拒绝服务攻击两种网络攻击进行建模,将攻击向量与测量数据混合引入发电机DSE中;其次,在不同复杂程度的网络攻击下,分别采用RCKF算法和立方卡尔曼滤波器(CKF)算法进行DSE,并对两种算法进行比较和讨论。这项研究的新颖性主要在于我们试图将网络攻击引入发电机的DSE。IEEE 9节点系统和新英格兰16机68节点系统的仿真结果验证了RCKF的有效性和优越性。

英文摘要:

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.

机构、总结、中文摘要均由AI分析而来,可能存在错误,请以论文正文为准。

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