基于融合容积卡尔曼滤波的直流微电网虚假数据检测

False Data Detection in DC Microgrids Based on Fusion of Cubature Kalman Filters

随着信息技术在微电网中的广泛应用,微电网正发展为一类物理系统与信息系统深度融合的电力信息物理系统(CPS)。由于微电网的分布式协同控制对即时通信和系统状态信息依赖程度高,使其受到虚假数据注入攻击(FDIA)的风险加大。针对直流微电网中的虚假数据注入攻击,提出一种基于融合容积卡尔曼滤波(CKF)的虚假数据注入攻击检测方法。首先,建立存在虚假数据攻击的直流微电网模型,对攻击下的直流微电网系统进行分析;其次,提出一种融合容积卡尔曼滤波的方法对攻击进行检测,可以精确检测到直流微电网中的攻击并确定攻击注入的量测单元;最后,在不同直流微电网模型工况下进行了仿真验证。仿真结果表明,所提方法在不同工况下的准确性和有效性均高于传统的容积卡尔曼滤波检测方法。

With the extensive application of information technology in a microgrid,the microgrid is developing into a kind of power cyber-physical system(CPS),deeply integrating the physical system and the information system.However,the distributed cooperative control of the microgrid relies heavily on instant communication and system status information,and therefore increases the risk of false data injection attack(FDIA).Aiming at FDIA in the DC microgrid,the paper proposes a method based on the fusion of cubature Kalman filter(CKF)to detect FDIAs.Firstly,a DC microgrid model with false data attack is established to analyze the DC microgrid system under the attacks.Secondly,the fusion of cubature Kalman filter based method is proposed to accurately detect the attacks in the DC microgrid and determine the measuring unit for injecting the attacks.Finally,the simulation results under different DC microgrid model conditions show that the proposed method is more accurate and effective than the traditional CKF detection method under different working conditions.