Dynamic State Estimation of Smart Grid Based on UKF Under Denial of Service Attacks

被引：0
|
作者：
Li X. [1 ]
Li W.-T. [1 ]
Du D.-J. [1 ]
Sun Q. [1 ]
Fei M.-R. [1 ]
机构：
[1] Shanghai Key Laboratory of Power Station Automation Technology, School of Mechatronics Engineering and Automation, Shanghai University, Shanghai
来源：
Zidonghua Xuebao/Acta Automatica Sinica | 2019年 / 45卷 / 01期
基金：
中国博士后科学基金; 中国国家自然科学基金;
关键词：
Denial of service(DoS) attacks; Dynamic state estimation; Smart grid; Unscented Kalman filter (UKF);
D O I：
10.16383/j.aas.2018.c180431
中图分类号：
学科分类号：
摘要：
When continuous denial of service (DoS) attacks cause measurement data losses in smart grid, the traditional dynamic state estimation is useless, destroying the running safety of smart grid seriously. To solve the problem, an improved unscented Kalman filter (UKF) is proposed, which can estimate the dynamic state of smart grid under DoS attacks. Firstly, the characteristics of data packet losses resulting from DoS attacks are analyzed and data compensation strategy is designed to reconstruct the dynamic model of power system. Integrating Holt's two-parameter exponential smoothing and unscented Kalman filter algorithms, a new state estimation equation including the compensation information is then constructed. Furthermore, a state gain updating method is derived from the estimated error covariance matrix, which produces a new enhanced UKF dynamic state estimation algorithm. Finally, simulations on IEEE 30-bus and 118-bus system confirm the feasibility and effectiveness of the proposed method. Copyright © 2019 Acta Automatica Sinica. All rights reserved.
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页码：120 / 131
页数：11
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