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

作　　者：常梦言 刘永慧 CHANG Mengyan;LIU Yonghui(School of Electrical Engineering,Shanghai Dianji University,Shanghai 201306,China;School of Intelligent Manufacturing and Control Engineering,Shanghai Polytechnic University,Shanghai 201209,China)

机构地区：[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

出　　处：《电力科学与技术学报》2024年第3期10-18,共9页Journal of Electric Power Science And Technology

基　　金：国家自然科学基金(61803253)。

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。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 

分 类 号：TP273[自动化与计算机技术—检测技术与自动化装置]