电力科学与技术学报2024,Vol.39Issue(3) :10-18.DOI:10.19781/j.issn.1673-9140.2024.03.002

虚假数据注入攻击下基于容积卡尔曼滤波的电力系统状态估计

State estimation of power system based on cubature Kalman filter under false data injection attacks

常梦言 刘永慧
电力科学与技术学报2024,Vol.39Issue(3) :10-18.DOI:10.19781/j.issn.1673-9140.2024.03.002

虚假数据注入攻击下基于容积卡尔曼滤波的电力系统状态估计

State estimation of power system based on cubature Kalman filter under false data injection attacks

常梦言 1刘永慧2
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作者信息

  • 1. 上海电机学院电气学院,上海 201306
  • 2. 上海第二工业大学智能制造与控制工程学院,上海 201209
  • 折叠

摘要

针对虚假数据注入攻击下系统状态估计的问题,以电力信息物理系统为研究对象,根据发电机三阶模型和自动电压调节器模型,建立电力系统的数学模型.采用指数平滑法预测测量值,通过对比预测值与真实测量值,检测系统是否发生虚假数据注入攻击.若检测结果判定系统遭受虚假数据注入攻击,用预测值替代不良数据输入状态估计算法,实现虚假数据注入攻击下不良数据的恢复.将指数平滑法与容积卡尔曼滤波算法结合,提出一种改进的容积卡尔曼滤波算法对系统进行状态估计.以典型的五机电力系统为例进行仿真,仿真结果表明提出的方法能有效抵御虚假数据对系统状态估计造成的不良影响.

Abstract

Aiming at the problem of system state estimation under false data injection attacks,the mathematical model of power system was established according to the third-order model of generator and the model of automatic voltage regulator,taking the cyber-physical power system as the research object. The exponential smoothing method was used to predict the measured value,and by comparing the predicted value with the actual measured value,it detected whether there were false data injection attacks in the system. If the detection results determine that the system being subjected to false data injection attacks,the predicted value is used instead of the bad data input state estimation algorithm to restore corrupted data cansed by these attacks. Combining the exponential smoothing method with the cubature Kalman filter algorithm,an improved cubature Kalman filter algorithm was proposed to estimate the state of the system. Taking a typical five-machine power system as an example,the simulation results show that the proposed method can effectively prevent the adverse effects of false data on system state estimation.

关键词

电力信息物理系统/状态估计/容积卡尔曼滤波/虚假数据注入攻击/指数平滑法

Key words

cyber-physical power system/state estimation/cubature Kalman filter/false data injection attacks/exponential smoothing method

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基金项目

国家自然科学基金(61803253)

出版年

2024
电力科学与技术学报
长沙理工大学

电力科学与技术学报

CSTPCD北大核心
影响因子:0.85
ISSN:1673-9140
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