Intelligent Identification System of Power Quality Disturbance

被引:5
|
作者
Zang, Hongzhi [1 ]
Zhao, Yishu [1 ]
机构
[1] Shandong Elect Power Res Inst, Jinan, Peoples R China
关键词
Power Quality disturbance; intelligent identification system; wavelet transform; support vector machine;
D O I
10.1109/GCIS.2009.314
中图分类号
TP18 [人工智能理论];
学科分类号
081104 ; 0812 ; 0835 ; 1405 ;
摘要
Studies of power quality phenomena have emerged as an important subject in recent years due to renewed interest in improving the quality of the electricity supply Because the wide application of high-power electronics switchgear, problems of power quality are becoming more serious as each passing day. How to identify power quality disturbances from large number of power signals and how to recognize them automatically are important for further understanding and improving of power quality. In this work, we propose an intelligent system for detection and classification of Power quality disturbance using wavelet transform and multi-lay support vector machines. The proposed technique allows creating such expert systems with the extensible knowledge base, which can be used for identification of power quality disturbances. The simulation result verifies its validity to classify power quality disturbances
引用
收藏
页码:258 / 261
页数:4
相关论文
共 50 条
  • [1] A Novel Intelligent System for Analysis and Recognition of Power Quality Disturbance Signal
    Wang Huaying
    Liu Jingbo
    Song Xiufa
    CCDC 2009: 21ST CHINESE CONTROL AND DECISION CONFERENCE, VOLS 1-6, PROCEEDINGS, 2009, : 3915 - 3918
  • [2] Wavelet-based intelligent system for recognition of power quality disturbance signals
    Kaewarsa, Suriya
    Attakitmongcol, Kitti
    Krongkitsiri, Wichai
    ADVANCES IN NEURAL NETWORKS - ISNN 2006, PT 2, PROCEEDINGS, 2006, 3972 : 1378 - 1385
  • [3] 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
  • [4] S-Transform-Based intelligent system for classification of power quality disturbance signals
    Lee, IWC
    Dash, PK
    IEEE TRANSACTIONS ON INDUSTRIAL ELECTRONICS, 2003, 50 (04) : 800 - 805
  • [5] Detection and Identification of Transient Power Quality Disturbance
    Hao, Xiaohong
    Cao, Juan
    Han, Yufang
    Gu, Qun
    PROCEEDINGS OF THE 2017 2ND INTERNATIONAL CONFERENCE ON AUTOMATION, MECHANICAL CONTROL AND COMPUTATIONAL ENGINEERING (AMCCE 2017), 2017, 118 : 173 - 179
  • [6] 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 - +
  • [7] 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
  • [8] Expert system for power quality disturbance classifier
    Reaz, Mamun Bin Ibne
    Choong, Florence
    Sulaiman, Mohd Shahiman
    Mohd-Yasin, Faisal
    Kamada, Masaru
    IEEE TRANSACTIONS ON POWER DELIVERY, 2007, 22 (03) : 1979 - 1988
  • [9] Design of Online Intelligent Detection System for Power Quality and Fault Identification in Distribution Networks
    He W.
    He C.
    Zhang Z.
    Ren B.
    Applied Mathematics and Nonlinear Sciences, 2024, 9 (01)
  • [10] A multi-agent intelligent interpretation system for power system disturbance diagnosis
    Hossack, J
    McArthur, SDJ
    Davidson, E
    McDonald, JR
    Cumming, T
    APPLICATIONS AND INNOVATIONS IN INTELLIGENT SYSTEMS X, 2003, : 91 - 104