|Table of Contents|

Transient power quality disturbances location method using improved HilbertHuang transform

《南京理工大学学报》(自然科学版)[ISSN:1005-9830/CN:32-1397/N]

Issue:
2013年01期
Page:
65-
Research Field:
Publishing date:

Info

Title:
Transient power quality disturbances location method using improved HilbertHuang transform
Author(s):
Yang Hansheng
Department of Automation,Chaohu College,Chaohu 238000,China
Keywords:
HilbertHuang transforminstantaneous frequencytransient power qualitydisturbance location
PACS:
TM76
DOI:
-
Abstract:
Aiming at the reduction of excessively sifting,a modified sifting stop criterion is proposed here,and a method based on the improved HilbertHuang Transform is introduced for detection and analysis of power quality disturbances.The signal is decomposed into Intrinsic Mode Function by the improved empirical mode decomposition method,and the disturbance amplitude and frequency of corresponding time can be detected accurately and quantitatively.The experimental results show that this method can precisely localize the disturbance starting and ending time,lasting time and amplitude and is suitable for the monitoring system of power quality disturbance.

References:

[1]林海雪.现代电能质量的基本问题[J].电网技术,2001,25(10):5-12. Nin Haixue.Main problems of modern power quality[J].Power System Technology,2001,25(10):5-12.
[2]覃思师.基于STFT变换和DAGSVMs的电能质量扰动识别[J].电力系统保护与控制,2011,39(1):5-12. Qin Sishi.Power quality disturbances detection and identification based on STFT transform and DAGSVMs[J].Power System Protection and Control,2011,39(1):5-12.
[3]Poisson O,Rioual P,Meunier M.Detection and measurement of power quality disturbances using wavelet transform[J].IEEE Transactions on Power Delivery,2000,15(3):1039-1044.
[4]张杨,刘志刚.一种基于时频域多特征量的电能质量混合扰动分类新方法[J].中国电机工程学报,2012,32(34):26-30. Zhang Yang,Liu Zhigang.A new method for power quality mixed disturbance classification based on timefrequency domain multiple features[J].Proceedings of the CSEE,2012,32(34):26-30.
[5]Santoso S,Grady W M,et al.Characterization of distribution power quality events with Fourier and wavelet transforms[J].IEEE Transactions on Power Delivery,2000,15(1):247-251.
[6]黄南天,徐殿国.基于S变换与SVM的电能质量复合扰动识别[J].电工技术学报,2011,26(10):23-30. Huang Nantian,Xu Dianguo.Identification of power quality complex disturbances based on STransform and SVM[J].Transactions of China Electrotechnical Society,2011,26(10):23-30.
[7]曾纪勇,丁洪发,段献忠.基于数学形态学的谐波检测与电能质量扰动定位方法[J].中国电机工程学报,2005,25(21):57-62. Zeng Jiyong,Ding Hongfa,Duan Xianzhong.Harmonics detection and disturbance location methods based on mathematical morphology[J].Proceedings of the CSEE,2005,25(21):57-62.
[8]魏磊,张伏生,耿中行,等.基于瞬时无功功率理论的电能质量扰动检测、定位与分类方法[J].电网技术,2004,28(6):53-58. Wei Lei,Zhang Fusheng,Geng Zhongxing,et al.Detection,localization and identification of power quality disturbance based on instantaneous reactive power theory[J].Power System Technology,2004,28(6):53-58.
[9]王晶,束洪春,陈学允.动态电能质量的分形指数小波分析方法[J].中国电机工程学报,2004,24(5):40-45. Wang Jing,Shu Hongchun,Chen Xueyun.Fractal exponent wavelet analysis of dynamic power quality[J].Proceedings of the CSEE,2004,24(5):40-45.
[10]张扬,刘志刚.EEMD在电能质量扰动检测中的应用[J].电力自动化设备,2011,31(12):86-91. Zhang Yang,Liu Zhigang.Application of EEMD in power quality disturbance detection[J].Electric Power Automation Equipment,2011,31(12):86-91.
[11]李天云,赵妍.基于HHT的电能质量检测新方法.中国电机工程学报[J].2005,25(17):52-56. Li Tianyun,Zhao Yan.A new method for power quality detectionbased on HHT[J].Proceedings of the CSEE,2005,25(17):52-56.
[12]杨汉生.基于自适应提升格式的暂态电能质量扰动检测及定位[J].南京理工大学学报,2011,35(1):21-25. Yang Hansheng.Detection and location of transient power quality disturbances based on adaptive lifting scheme[J].Journal of Nanjing University of Science and Technology,2011,35(1):21-25.
[13]毛炜,金荣洪,耿军平,等.一种基于改进HilbertHuang变换的非平稳信号时频分析法及其应用[J].上海交通大学学报,2006,40(5):724-729. Mao Wei,Jin Ronghong,Geng Junping,et al.A timefrequency analysis method for nonstationary signals based on improved HilbertHuang transform and its application[J].Journal of Shanghai Jiaotong University,2006,40(5):724-729.

Memo

Memo:
-
Last Update: 2013-02-15