考虑假数据攻击检测的动态相量估计方法

Dynamic Phasor Estimation Method Considering False Data Attack Detection

提出一种考虑假数据攻击的动态相量估计方法。首先,通过对包含谐波、噪声等条件的电气信号进行泰勒级数展开,建立了适用于动态条件下的电气信号模型;然后,使用双次优渐消因子强跟踪卡尔曼算法(DSTKF)与基于欧几里得距离的假数据攻击检测方法对相量进行检测、跟踪和估计;最后,用所提的估计方法对含有噪声和假数据攻击的电气信号以及IEEE39节点故障信号进行仿真验证。结果表明该方法不仅可以检测出电气信号中的假数据攻击与突变,而且对动态相量具有较高的估计精度与跟踪能力。

In this paper proposed was a dynamic phasor estimation method considering false data attack. First, an electrical signal model for dynamic conditions is established by Taylor series expansion of electrical signals with harmonic and noise conditions. Then, the phasor is detected, tracked, and estimated by using double suboptimal-scaling factor adaptive strong tracking Kalman filter(DSTKF) and false data attack detection method based on Euclidean distance. Finally, the proposed estimation method is used to simulate the electrical signal with noise and false data attack and the fault signal of IEEE39 node. The results show that the method not only detects the false data injection attack and mutation in the electrical signal, but also has high estimation accuracy and tracking ability for the dynamic phasor.