基于卡尔曼滤波的新型电力系统电气参数估算方法研究  

Research on Electrical Parameter Estimation Method for New Power Systems Based on Kalman Filtering

作　　者：姚兵 申冉 YAO Bing;SHEN Ran(DC Division,State Grid Hubei Electric Power Company,Yichang 443000,Hubei Province,China;Yichang Power Supply Company,State Grid Hubei Electric Power Company,Yichang 443099,Hubei Province,China)

机构地区：[1]国网湖北省电力有限公司直流公司,湖北宜昌443000 [2]国网湖北省电力有限公司宜昌供电公司,湖北宜昌443099

出　　处：《电力与能源》2024年第5期559-562,共4页Power & Energy

摘　　要：新型电力系统中包含各类电力电子设备,高频噪声含量较大。当分布式电源在孤岛运行与并网运行间切换时,电气信号的频率、幅值、相位均会发生突变。传统的三相电气信号参数估计方法难以应对高频噪声与信号突变,导致估测时间长,估测结果精度低。为此,提出了一种改进的卡尔曼滤波器,通过引入两个渐消因子来修正卡尔曼滤波器中的先验估计协方差矩阵和表示过程噪声的方差矩阵,从而提高估测的动态响应速度与稳态精度。仿真结果表明,该方法有效提升了算法的收敛速度与估测精度。New power systems include various power electronic devices with high-frequency noise.During the transition between islanded and grid-connected modes for distributed power sources,abrupt changes occur in frequency,amplitude,and phase of electrical signals.Traditional three-phase electrical signal parameter estimation methods struggle with high-frequency noise and signal jumps,leading to longer estimation time and lower estimation accuracy.This proposes an improved Kalman filter that introduces two diminishing factors to correct the priori estimation covariance matrix and the variance matrix representing process noise,enhancing dynamic response speed and steady-state accuracy.Simulation results show that the method improves algorithm convergence speed and estimation accuracy.

关 键 词：卡尔曼滤波器 渐消因子 状态估计 

分 类 号：TM73[电气工程—电力系统及自动化]