• DocumentCode
    2893525
  • Title

    Harmonic analysis approach based on wavelet transform and neural network

  • Author

    Maofa, Gong ; Xiaocong, Liu ; Longqing, Chai ; Liming, Gong ; Guoliang, Li

  • Author_Institution
    Coll. of Inf. & Electr. Eng., Shandong Univ. of Sci. &Technol., Qingdao, China
  • fYear
    2011
  • fDate
    6-9 July 2011
  • Firstpage
    574
  • Lastpage
    576
  • Abstract
    The paper presents a new approach based on wavelet and neural network for the estimation of harmonic components in the power system. This proposed method preprocesses the signal using wavelet analysis to get feature extraction of signals. Then it analyses and calculates the feature vector by the artificial neural network (ANN), and the harmonic components of the current can be got. The combination of wavelet and ANN make up for each other´s deficiencies and it can solve the frequency aliasing effectively. The structure of this method and the specific algorithm are presented. The simulation model is also built and the results show that the harmonic components can be detected at real time with high precision.
  • Keywords
    feature extraction; harmonic analysis; neural nets; power system harmonics; wavelet transforms; artificial neural network; feature extraction; feature vector; frequency aliasing; harmonic analysis; harmonic components estimation; power system harmonics; wavelet transform; Estimation; Harmonic analysis; Power system harmonics; Wavelet analysis; Wavelet packets; Harmonic Analysis; Neural Network; Wavelet Transform;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electric Utility Deregulation and Restructuring and Power Technologies (DRPT), 2011 4th International Conference on
  • Conference_Location
    Weihai, Shandong
  • Print_ISBN
    978-1-4577-0364-5
  • Type

    conf

  • DOI
    10.1109/DRPT.2011.5993958
  • Filename
    5993958