【摘要】 精确、可靠的发电机动态状态量对电力系统的实时监测和控制至关重要。信息攻击的出现给发电机状态估计带来了新的挑战。其中,虚假数据注入(FDI)攻击通过对量测装置注入虚假数据,恶化了状态估计的精度。为此,该文提出一种针对发电机动态状态估计的FDI攻击模型。首先,采用泰勒公式将发电机量测方程线性化;其次,根据FDI攻击前后量测残差不变的原理,建立攻击向量的表达式,将其施加在量测量中,从而躲避常规的不良数据检测,成功实施FDI攻击;然后,根据攻击程度分别设定三种攻击情形,通过容积卡尔曼滤波(CKF)和抗差容积卡尔曼滤波(RCKF)对所提的三种不同情形的FDI攻击进行验证;最后,IEEE9节点系统和新英格兰16机68节点系统的仿真结果验证了所提FDI攻击的有效性。更多还原

【Abstract】 Accurate and reliable dynamic state quantities of generators are very important for real-time monitoring and control of the power system. The emergence of cyber attacks has brought new challenges to the state estimation of generators. Especially, false data injection(FDI) attacks deteriorate the accuracy of state estimation by injecting the false data into the measurement device. In this regard, this paper proposes for the first time an FDI attack model based on the dynamic state estimation of generators. Firstly, Taylor’s formula was used to linearize the generator’s measurement equation. Secondly, according to the principle that the measurement residuals before and after the FDI attack are equal, the expressions of the attack vectors were established, and they were applied to the measurement quantities to avoid the conventional bad data detection. Thereby, the FDI attacks were successfully implemented. Then, three attack scenarios were set according to the degree of the FDI attacks, and they were tested by the cubature Kalman filter(CKF) and the robust cubature Kalman filter(RCKF). Finally, the simulation results of the IEEE 9-bus system and the New England 16-machine 68-bus system verify the effectiveness of the proposed FDI attacks.更多还原