基于SVD的复数UKF及电力系统对称分量估计

SVD based adaptive complex UKF algorithm and its application to estimate symmetrical components of power system

电力系统对称分量的检测对于电力系统安全稳定的运行具有很重要的意义。利用复数域无迹卡尔曼滤波算法,对三相电压系统的正负序分量及频率进行了估计。为了提高复数无迹卡尔曼滤波的参数估计精度及算法稳定性,引入最优自适应因子并对预测协方差矩阵进行SVD分解,提出了基于SVD的自适应CUKF算法。为消除零序分量,对三相电压分量进行αβ变换,定义了复数形式的状态变量,建立了非线性状态方程及观测方程,实现了正序、负序对称分量估计。通过与普通复数域无迹卡尔曼滤波算法对比,所提研究方法在估计精度及收敛速度等方面优于传统无迹卡尔曼滤波方法。

To ensure power system works safely and steadily,the detection of symmetrical components of power system is significant.In this paper,the complex unscented Kalman filter(CUKF)algorithm was used to estimate the positive and negative sequence components and frequency of a three-phase voltage system were estimated by this algorithm.To improve the estimation accuracy and algorithm stability,an optimal adaptive factor is adopted,the prediction covariance matrix is decomposed based on singular value decomposition(SVD)method,and an adaptive complex UKF algorithm based on SVD(ASCUKF)is proposed.To eliminate zero sequence of symmetrical component,αβtransformation is used to transform three-phase voltages into theαβreference frames,complex state variables are defined,the nonlinear state space and observation equations are built,and positive sequence and negative sequence of symmetrical components are estimated.Compared with the estimates with conventional CUKF,the algorithm proposed in the paper have great advantages in estimation accuracy and convergence speed.