摘要
针对传统电力信息物理系统的虚假数据注入攻击(FDIA)检测精度低问题,提出了基于自适应SageHusa噪声无迹卡尔曼滤波(ASRUFK)和改进马尔科夫链(IMC)预测算法的电力信息物理系统FDIA检测方法。首先,通过加入随机插值调整状态区间,提出了一种改进马尔科夫链(IMC)预测算法;然后,利用ASRUKF和IMC预测算法分别对系统待测数据进行状态估计,根据2种预测算法状态估计结果的偏差值构建随机变量,利用Box-Cox将随机变量转换为服从正态分布的变量;最后,通过双边假设检验实现电力信息物理系统的FDIA检测。在IEEE-14节点和IEEE-30节点系统中验证了所提出方法的有效性和正确性。
To solve the problem of low accuracy of false data injection attack(FDIA)detection in traditional power information physical system,a new FDIA detection method based on adaptive Sage-Husa unscented Kalman filter(ASRUFK)and improved Markov chain(IMC)prediction algorithm is proposed.Firstly,an improved Markov chain(IMC)prediction algorithm is proposed by adding random interpolation to adjust the state interval.Secondly,ASRUKF and IMC prediction algorithms are used to estimate the state of the data to be measured in the system,and random variables are constructed according to the deviation values of the state estimation results of the two prediction algorithms.Box-Cox is used to convert random variables into variables with normal distribution.Finally,the FDIA detection of the power information physical system is realized through bilateral hypothesis testing.The validity and correctness of the proposed method are verified in IEEE-14 node and IEEE-30 node systems.
作者
庞清乐
韩松易
周泰
张峰
焦绪国
王言前
PANG Qingle;HAN Songyi;ZHOU Tai;ZHANG Feng;JIAO Xuguo;WANG Yanqian(School of Information and Control Engineering,Qingdao University of Technology,Qingdao 266520,China)
出处
《智慧电力》
北大核心
2024年第7期111-118,共8页
Smart Power
基金
国家自然科学基金资助项目(62203249)
山东省自然科学基金资助项目(ZR2021QF115)。
