摘要
动态状态估计是电力系统分析、监视和规划的重要工具。针对传统扩展卡尔曼滤波(extend Kalman filter,EKF)需要计算雅可比矩阵会产生线性化误差的不足。选用可非线性化计算的无迹卡尔曼滤波(unscented Kalman filter,UKF)进行状态估计。以IEEE33节点系统为例进行状态估计,仿真结果表明,无迹卡尔曼滤波算法具有良好的估计性能。
Dynamic state estimation is an important tool for power system analysis,monitoring,and planning.For the traditional extended Kalman filter(EKF),the linearization error is generated when calculating the Jacobian matrix.The unscented Kalman filter(UKF)which can be nonlinearly calculated is used for state estimation.The IEEE33 node system is used as an example for state estimation.The simulation results show that the unscented Kalman filter algorithm has good estimation performance.
作者
张宏伟
刘磊
刘源
张开元
Zhang Hong-wei;Liu Lei;Liu Yuan;Zhang Kai-yuan(State Grid Qingdao Power Supply Company,Shandong Qingdao 266002;College of Electrical Engineering and Automation, Shandong University of Science and Technology,Shandong Qingdao 266590)
出处
《电子质量》
2019年第2期66-69,共4页
Electronics Quality
关键词
配电网
状态估计
无迹卡尔曼滤波
Distribution network
State estimation
Unscented Kalman filter