| 引用本文: | 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.[点击复制] |
| Lü Siying,LI Dan,YAO Hang,PEI Chan.Fundamental component extraction based on unscented Kalman filter[J].Power System Protection and Control,2016,44(13):79-84[点击复制] |
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| 摘要: |
| 针对全波Fourier和Kalman滤波算法在提取基波分量时对频率偏移敏感和直流偏移量抑制能力差的缺点，提出了一种新的基波分量提取算法。首先以故障信号的直流偏移量、基波角频率和基波分量作为状态变量，建立信号的非线性状态空间模型。然后采用无迹Kalman滤波(Unscented Kalman Filter，UKF)在信号的非线性模型基础上估计出基波分量。此外，滤波算法还能够实时估计出信号的直流偏移量和基波频率。通过多个算例仿真对算法进行验证与测试，仿真结果证实了算法的可行性和有效性。仿真结果表明，算法对频率突变和直流偏移量突变具有良好的适应性，能快速准确地提取出基波分量。 |
| 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 |
| DOI：10.7667/PSPC151333 |
| 投稿时间：2015-07-31修订日期：2015-09-13 |
| 基金项目:广西研究生教育创新计划项目(YCSZ2014041) |
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| Fundamental component extraction based on unscented Kalman filter |
| LÜ Siying,LI Dan,YAO Hang,PEI Chan |
| (School of Electrical Engineering, Guangxi University, Nanning 530004, China) |
| Abstract: |
| Aiming at the full-wave Fourier and Kalman filter algorithms’ shortcomings of sensitive to frequency changes and poor ability of DC offset component reduction in the extraction of the fundamental component, a new fundamental 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 state variables, and establishes the nonlinear state space model. Then, the Unscented Kalman Filter (UKF) is adopted to estimate the fundamental component based on the nonlinear model of signal. In addition, the filter algorithm is able to estimate the DC offset component and fundamental frequency in real-time. Several numerical simulations are carried out to testify the proposed algorithm and the results validate the algorithm''s feasibility and effectiveness. 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. |
| Key words: fundamental component extraction DC offset component fundamental angular frequency nonlinear state space model UKF |
