Comparative study on power quality disturbance magnitude characterization

被引:0
|
作者
Wang, ZQ [1 ]
Zhu, SZ [1 ]
机构
[1] Tsing Hua Univ, Dept Elect Engn, Beijing 100084, Peoples R China
关键词
magnitude characteristic; power quality; power quality disturbance; digital signal processing;
D O I
暂无
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Power quality disturbances (PQD) are normally monitored by dedicated PQ devices. The devices capture disturbances' waveform in real-time. Magnitude is accepted as a significant index for detection, general classification and later assessment analysis. To choose suitable way of magnitude characterization is a fundamental work of PQD measuring and monitoring. This study presents three different ways, RMS voltage, peak voltage and fundamental voltage component, to determine magnitude. The algorithms of the three approaches implemented in Matlab are introduced. The algorithms are FFT-based and wavelet transformation (WT) based. A voltage sag benchmark in a radial test system is used to verify and validate the study. The depth-duration characterization of voltage sags is illustrated. The most appropriate approach is suggested at the end of the paper according to the practical monitoring or,measuring requirements. The research result is applied to a new PQ monitor with DSP infrastructure being developed by us. The proper window length selection and technique to avoid oscillation is also discussed in the rest part of the paper. The information obtained from the magnitude characterization can be furthered to extract features for PQD detection and classification.
引用
收藏
页码:106 / 111
页数:6
相关论文
共 50 条
  • [41] A Hybrid Intelligent Model for Power Quality Disturbance Classification
    Malik, Hasmat
    Kaushal, Paras
    Srivastava, Smriti
    APPLICATIONS OF ARTIFICIAL INTELLIGENCE TECHNIQUES IN ENGINEERING, VOL 2, 2019, 697 : 55 - 63
  • [42] A new method for measurement and classification of power quality disturbance
    School of Electrical Engineering, Wuhan University, Wuhan 430072, China
    不详
    Zhongguo Dianji Gongcheng Xuebao, 31 (125-133):
  • [43] An Extensible, Open Framework for Power Quality Disturbance Events
    Min, Kyung Woo
    Bastos, Alvaro Furlani
    Santoso, Surya
    Karadkar, Unmil
    2018 IEEE/PES TRANSMISSION AND DISTRIBUTION CONFERENCE AND EXPOSITION (T&D), 2018,
  • [44] Based on SVM Power Quality Disturbance Classification Algorithm
    Jixiu
    Zhang Hongyan
    Jin Yue
    Yan Xuting
    Wang Hui
    2015 27TH CHINESE CONTROL AND DECISION CONFERENCE (CCDC), 2015, : 3618 - 3621
  • [45] A new method for detection and identification of power quality disturbance
    Wang, Chao
    Gao, Huimin
    Zhu, Taoxi
    2006 IEEE/PES POWER SYSTEMS CONFERENCE AND EXPOSITION. VOLS 1-5, 2006, : 1556 - +
  • [46] Review of Power Quality Disturbance Detection and Identification Methods
    Wang, Fei
    Quan, Xiaoqing
    Ren, Lintao
    Zhongguo Dianji Gongcheng Xuebao/Proceedings of the Chinese Society of Electrical Engineering, 2021, 41 (12): : 4104 - 4120
  • [47] The Application of Mathematical Morphology in the Disturbance Detection of Power Quality
    Hu, Yanqin
    Gao, Yin
    PROCEEDINGS OF THE 6TH INTERNATIONAL CONFERENCE ON ELECTRONIC, MECHANICAL, INFORMATION AND MANAGEMENT SOCIETY (EMIM), 2016, 40 : 1011 - 1019
  • [48] A Combination Approach for Transient Power Quality Disturbance Recognition
    Xu Tongyu
    Zheng Wei
    2012 ASIA-PACIFIC POWER AND ENERGY ENGINEERING CONFERENCE (APPEEC), 2012,
  • [49] Research on power quality disturbance automatic recognition and location
    Li, GY
    Zhou, M
    Zhang, ZY
    2003 IEEE POWER ENGINEERING SOCIETY GENERAL MEETING, VOLS 1-4, CONFERENCE PROCEEDINGS, 2003, : 687 - 691
  • [50] An Online Electric Power Quality Disturbance Detection System
    Yildirim, Ozal
    Eristi, Belkis
    Eristi, Huseyin
    Unal, Sencer
    Erol, Yavuz
    Demir, Yakup
    2016 51ST INTERNATIONAL UNIVERSITIES POWER ENGINEERING CONFERENCE (UPEC), 2016,