|本期目录/Table of Contents|

[1]金涛,刘对.基于改进去噪性能的Prony算法电网低频振荡模态辨识研究[J].电机与控制学报,2017,21(05):33-41.[doi:10.15938/j. emc.2017.05.005]
 JIN Tao,LIU Dui.Power grid low frequency oscillation recognition based on advanced Prony algorithm with improved demising feature[J].,2017,21(05):33-41.[doi:10.15938/j. emc.2017.05.005]
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基于改进去噪性能的Prony算法电网低频振荡模态辨识研究(PDF)
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《电机与控制学报》[ISSN:1007-449X/CN:23-1 408/TM]

卷:
21
期数:
2017年05
页码:
33-41
栏目:
出版日期:
2017-04-20

文章信息/Info

Title:
Power grid low frequency oscillation recognition based on advanced Prony algorithm with improved demising feature
作者:
金涛刘对
(福州大学电气工程与自动化学院,福建福州350116)
Author(s):
JIN TaoLIU Dui
 (College of Electrical Engineering and Automation,Fuzhou University,Fuzhou 350116,China)
关键词:
 关键词%Prny算法低频振荡小波去噪模态辨识电力系统
Keywords:
 Prony algoritiimlow frequency oscillation wavelet denoise modal identification power system
分类号:
TM 712
DOI:
10.15938/j. emc.2017.05.005
文献标志码:
A
摘要:
针对电网低频振荡Prony辨识算法对噪声较为敏感、对输入信号要求较高的问题,提出了 一种基于小波去嗓与扩展Prony算法相结合的高精度低频振荡模态辨识方法。在小波去嗓的基础 上通过对阈值进行改进,使得小波去噪的阈值随着小波的分解而发生变化,从而对低频振荡信号达 到较好的滤波效果,并在此基础上研究扩展Prny算法,对构建的仿真信号运用IEEE4机2区域系 统产生低频振荡信号以及实际PMU监测的低频振荡信号进行算法验证。仿真和实验表明提出的 方法能够比较准确和快速的辨识电力系统低频振荡信号,且具有较高的精度和较好的鲁棒性,为电 力系统低频振荡模态辨识提供了一种行之有效的方法。
Abstract:
Amethod based on wavelet denoise and improved Prony algorithm were proposed to identify low frequency oscillation modes,in view of tlie fact tlie Prony algoritlim is very sensitive for the input signal. On the basis of wavelet denoising analysis,the thresliold technique was
improved,and the wavelet threshold was made changing with wavelet decomposition. Then an improved Prony algorit!im were researched to recognize the mode of low-frequency oscillation. Through building signal ,IEEE 4 machine 2 area system simulation and experiments,the proposed wavelet denoising met!iod and Prony algorithm were proved to have a high accuracy and good robust performance. It is very feasibility to deal wit!i the noise of power system and can identify low frequency oscillation modes rapidly and accurately
in a certain noise environment,and provide an efective met!iod to power system low-frequency oscillation.

参考文献/References:

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备注/Memo

备注/Memo:
收稿日期:2016 -03 -11
基金项目:欧盟FP7国际科技合作基金(909880);国家自然科学基金(61304260);福建省杰出青年科学基金(2012J06012)
作者简介:金涛(1976—$,男,博士,研究员,博士生导师,研究方向为电力系统稳定性分析、在线测量与信号处理、新能源技术;
刘对(1990—),男,硕士研究生,研究方向为电力系统广域监测与故障分析
更新日期/Last Update: 2017-07-14