基于非负定自适应卡尔曼滤波的电力系统虚假数据攻击检测  

Nonnegative-definite Adaptive Kalman Filter-based Detection of False Data Attack in Power System

作　　者：许浩文 郭观凯 余玲玲 秦福元 陈佳佳[1] 刘伟[1] XU Hao-wen;GUO Guan-kai;YU Ling-ling;QIN Fu-yuan;CHEN Jia-jia;LIU Wei(School of Electrical and Electronic Engineering,Shandong University of Technology,Zibo 255049,China;Chinese Academy of Sciences,Chinese Academy of Engineering Zunyi Working Center,Zunyi 563000,China)

机构地区：[1]山东理工大学电气与电子工程学院,淄博255049 [2]中国科学院、中国工程院遵义院士工作中心,遵义563000

出　　处：《科学技术与工程》2020年第9期3611-3616,共6页Science Technology and Engineering

基　　金：山东省重点研发计划(2018GGX101049)。

摘　　要：虚假数据攻击(false data attack, FDA)是通过对电网中远程终端单元(remote terminal unit, RTU)、同步相量测量单元(phasor measurement unit, PMU)等通信环节的攻击,误导电力系统的状态估计,给电力系统的安全可靠运行带来巨大威胁。构建了电网虚假数据攻击检测架构、电压信号状态空间模型和虚假数据攻击模型,提出了非负定自适应卡尔曼滤波算法来估计模型中的状态量,旨在准确检测电力系统中的虚假数据。通过对3节点电力系统仿真,结果验证文中所提的算法在保证滤波稳定性的同时,提高了攻击检测的运算速度。False data attack(FDA) is an attack on communication links such as remote terminal unit(RTU) and phasor measurement unit(PMU) in power system. It will mislead the state estimation of power system and pose a great threat to the safe and reliable operation of power system. The power network false data attack detection framework, voltage signal state space model and false data attack model were constructed. Nonnegative-definite adaptive Kalman filter algorithm was proposed to estimate the state in the model, in order to accurately detect the false data in the power system. The simulation results of 3-node power system show that the proposed algorithm can improve the speed of attack detection while guaranteeing the stability of filtering.

关 键 词：电力系统 非负定滤波算法 虚假数据攻击 卡尔曼滤波器 状态估计 检测攻击 

分 类 号：TM273.1[一般工业技术—材料科学与工程]