虚假数据注入攻击(false data injection attack,FDIA)是威胁电网运行安全的主要因素之一,其主要通过攻击电网中的一些通信环节,误导电力系统的状态估计结果,给电网安全运行带来巨大威胁.针对FDIA难以有效检测及电力系统状态估计中过程噪声与量测噪声两者协方差矩阵非正定问题,将向量自回归(vector auto regression,VAR)模型引入电力系统状态估计,提出一种基于VAR和加权最小二乘法(weighted least squares,WLS)的FDIA检测方法.首先,建立VAR状态估计模型,将量测噪声视为稳定量,只对过程噪声进行估计,解决两者协方差矩阵的非正定问题;其次,分别采用VAR与WLS对电力系统进行状态估计,采用一致性检验与量测量残差检验对2种方法的结果进行检测,以判定是否存在FDIA;最后,IEEE 14节点和IEEE 30节点仿真结果表明,本文所提检测方法能够成功检测到FDIA,且检测成功率较高,从而验证了该方法的可行性及有效性.
Abstract
False data injection attack (FDIA) is one of the major factors threatening the operational security of power grids. It primarily targets communication links within power grids,misleading the state estimation results of the power system and posing significant risks to grid security. Addressing the challenges of effectively detecting FDIA and the non-positive definite covariance matrix of process noise and measurement noise in power system state estimation,this paper introduces the vector auto-regression (VAR) model into power system state estimation and proposes an FDIA detection method based on VAR and weighted least squares (WLS). Firstly,a VAR state estimation model is established,treating measurement noise as a stable quantity and estimating only process noise,thereby resolving the non-positive definite issue of the covariance matrix. Secondly,both VAR and WLS are used for power system state estimation,and the results of the two methods are detected using consistency checks and measurement residual tests to determine the presence of FDIA. Finally,simulation results from IEEE 14-bus and IEEE 30-bus systems demonstrate that the proposed detection method can successfully detect FDIA with a high success rate,verifying the feasibility and effectiveness of the method.
关键词
虚假数据注入攻击/向量自回归/加权最小二乘法/状态估计/攻击检测
Key words
false data injection attack/vector auto-regression/weighted least squares/state estimation/attack detection
维普
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