东北大学学报（自然科学版）

东北大学学报:自然科学版 ›› 2014, Vol. 35 ›› Issue (12): 1682-1686.DOI: 10.12068/j.issn.1005-3026.2014.12.003

• 信息与控制 • 上一篇    下一篇

精确消除衰减直流分量误差的改进算法

吴贤规， 王安娜， 王浩   

  1. (东北大学 信息科学与工程学院， 辽宁 沈阳110819)
  • 收稿日期:2014-03-21 修回日期:2014-03-21 出版日期:2014-12-15 发布日期:2014-09-12
  • 通讯作者: 吴贤规
  • 作者简介:吴贤规(1980-)，男，朝鲜平壤人，东北大学博士研究生； 王安娜(1956-)，女，辽宁鞍山人，东北大学教授，博士生导师.
  • 基金资助:
    国家自然科学基金资助项目(61050006).

An Improved Algorithm for Exactly Eliminate the Decaying DC Component Error

WU Xian-gui， WANG An-na， WANG Hao   

  1. School of Information Science & Engineering， Northeastern University， Shenyang 110819， China.
  • Received:2014-03-21 Revised:2014-03-21 Online:2014-12-15 Published:2014-09-12
  • Contact: WU Xian-gui
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摘要： 传统全周傅氏算法在直接处理含有指数衰减直流分量的电力系统故障信号时会产生较大误差，针对这个问题，提出了消除其误差的改进傅氏算法.该算法基于包含衰减分量的输入信号在一个周期内积分值及采样数据的求和不为零的原理，在计算衰减分量误差的过程中不需要增加采样点和任何近似计算，就可以求出衰减直流分量对傅氏算法带来的误差及衰减参数，将衰减分量造成的误差从故障输入信号的傅氏算法结果值中减去.仿真结果表明，该算法可以获得精确的基波及各次谐波相关参数，可应用于电力系统谐波在线分析.

关键词: 衰减直流分量, 全周傅氏算法, 谐波分量, 采样数据, 拉格朗日插值

Abstract: When the traditional full-cycle Fourier algorithm is directly used to process the power system fault signal including the decaying DC component， some errors will be produced. Thus， an improved Fourier algorithm which could eliminate the errors was proposed. This algorithm was based on the principle that integration of the input signal including the decaying DC component and summation of the sampled data were not zero in a full-cycle. This algorithm did not need addition of the sampled data and the approximation calculation in its derivation process， and could calculate the errors caused by the decaying DC component and its parameters. The errors caused by the decaying DC component could be eliminated from the results of the input fault signal. The simulation results showed that the parameters of fundamental frequency component and every harmonics can be accurately obtained， and the proposed algorithm can be used in power system on-line harmonic analysis.

Key words: decaying DC component, full-cycle Fourier algorithm, harmonic component, sampled data, Lagrange interpolation

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