Selecting Wavelet Functions for Detection of Power Quality Disturbances

被引:0
|
作者
Vega, V. [1 ]
Duarte, C. [2 ]
Ordonez, G. [2 ]
Kagan, N. [1 ]
机构
[1] Univ Sao Paulo, BR-05508 Sao Paulo, Brazil
[2] Univ Ind Santander, Santander, Spain
关键词
Discrete Wavelet Transform; detection; biorthogonal wavelet; power quality; RMS; disturbances;
D O I
暂无
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
This paper considers Discrete Wavelet Transform (DWT) for the detection of power quality disturbances. Wavelet Function Biorthogonal 3.9 is used as a base function due to its frequency response and information time localization properties. A methodology is proposed in order to choose the wavelet function that holds the best characteristics. Disturbances considered are low frequency disturbances such as flicker and harmonies and high frequency disturbances such as transient and voltage sags. Due to time-frequency localization properties, Discrete Wavelet Transform permits decomposition of signals in different energy levels. The first level of decomposition allows for detecting the start or the end of a disturbance by convolving the high pass decomposition filter (HPDF) with the disturbance.
引用
收藏
页码:581 / +
页数:2
相关论文
共 50 条
  • [31] Wavelet-based measurement and classification of power quality disturbances
    Chen, XX
    2002 CONFERENCE ON PRECISION ELECTROMAGNETIC MEASUREMENTS, CONFERENCE DIGEST, 2002, : 38 - 39
  • [32] On the choice of wavelet based features in power quality disturbances classification
    Markovska, Marija
    Taskovski, Dimitar
    2017 1ST IEEE INTERNATIONAL CONFERENCE ON ENVIRONMENT AND ELECTRICAL ENGINEERING AND 2017 17TH IEEE INDUSTRIAL AND COMMERCIAL POWER SYSTEMS EUROPE (EEEIC / I&CPS EUROPE), 2017,
  • [33] Data reduction of power quality disturbances - a wavelet transform approach
    Hsieh, CT
    Huang, SJ
    Huang, CL
    ELECTRIC POWER SYSTEMS RESEARCH, 1998, 47 (02) : 79 - 86
  • [34] Analysis of Power Quality Disturbances Using Wavelet Packet Transform
    Naik, Chirag A.
    Kundu, Prasanta
    2014 IEEE 6TH INDIA INTERNATIONAL CONFERENCE ON POWER ELECTRONICS (IICPE), 2014,
  • [35] The detection of transient power disturbances based on complex wavelet transform
    Zhang, Rui
    Zhang, Chuan-Guang
    Zhu, Run-Xia
    International Journal of Signal Processing, Image Processing and Pattern Recognition, 2014, 7 (02) : 317 - 326
  • [36] Wavelet Transform and ANNs for Detection and Classification of Power Signal Disturbances
    Memon, Aslam Pervez
    Uqaili, Mohammad Aslam
    Memon, Zubair Ahmed
    MEHRAN UNIVERSITY RESEARCH JOURNAL OF ENGINEERING AND TECHNOLOGY, 2012, 31 (04) : 755 - 768
  • [37] Detection and classification of power quality disturbances using parallel neural networks based on discrete wavelet transform
    Garousi, Maryam Rahmati
    Shakarami, Mahmoud Reza
    Namdari, Farhad
    JOURNAL OF ELECTRICAL SYSTEMS, 2016, 12 (01) : 158 - 173
  • [38] Wavelet transform and fractal theory for detection and classification of self-extinguishing and fugitive power quality disturbances
    Lakrih S.
    Diouri J.
    1600, North Atlantic University Union NAUN (15): : 499 - 510
  • [39] New method for detection of power quality disturbances
    Wen, Ji-Feng
    Liu, Pei
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2002, 22 (12): : 17 - 20
  • [40] Novelty detection on power quality disturbances monitoring
    Gonzalez-Abreu A.D.
    Delgado-Prieto M.
    Saucedo-Dorantes J.J.
    Osornio-Rios R.A.
    Renewable Energy and Power Quality Journal, 2021, 19 : 211 - 216