电力系统保护与控制2016，Vol.44Issue(13)：79-84,6.DOI:10.7667/PSPC151333
基于无迹Kalman滤波的基波分量提取
Fundamental component extraction based on unscented Kalman filter
摘要
Abstract
Aiming at the full-wave Fourier and Kalman filter algorithms’ shortcomings of sensitive to frequency changes and poor ability of DC offset component reductionin the extraction of the fundamental component, a newfundamental component extraction algorithm is presented. First of all, this paper defines the DC offset component, fundamental angular frequency, fundamental component of the fault signal as statevariables, and establishes the nonlinear state space model. Then, the Unscented Kalman Filter (UKF) is adopted to estimate the fundamentalcomponent based on the nonlinear model of signal. In addition, the filter algorithm is able to estimate theDC offset component and fundamental frequency in real-time. Several numerical simulations are carried out to testify the proposed algorithm andthe results validatethealgorithm'sfeasibilityandeffectiveness. The simulation results show that the algorithm is adaptive to the sudden changes of frequency and DC offset component, and it can extract the fundamental component quickly and accurately.关键词
基波分量提取/直流偏移量/基波角频率/非线性状态空间模型/无迹Kalman滤波Key words
fundamental component extraction/DC offset component/fundamental angular frequency/nonlinear state space model/UKF引用本文复制引用
吕思颖,黎丹,要航,裴旵..基于无迹Kalman滤波的基波分量提取[J].电力系统保护与控制,2016,44(13):79-84,6.基金项目
广西研究生教育创新计划项目(YCSZ2014041) （YCSZ2014041）
