• DocumentCode
    147094
  • Title

    Variable constrained based LMS algorithm for power system harmonic estimation

  • Author

    Singh, S.K. ; Nath, Asoke ; Chakraborty, Rupak ; Kalita, Jugal ; Sinha, N. ; Goswami, Arup K.

  • Author_Institution
    Electr. Eng. Dept., Nat. Inst. of Technol., Silchar, India
  • fYear
    2014
  • fDate
    3-5 April 2014
  • Firstpage
    1131
  • Lastpage
    1134
  • Abstract
    Many algorithms have been proposed for harmonic estimation to improve the power quality performance but till today it is still a challenge for accurate estimation. In this paper an adaptive filtering algorithm called Variable Constrained based Least Mean Square (VCLMS) is applied for the first time for estimating harmonic parameters. The algorithm has been considered to estimate the amplitudes and phases in case of time varying power signals containing harmonics in the presence of White Gaussian Noise in MATLAB simulating environment. Also a comparison between a recently proposed algorithm i.e. Least Mean Square (LMS) are presented to show the effectiveness of the proposed VCLMS algorithm.
  • Keywords
    Gaussian noise; adaptive filters; least squares approximations; power system harmonics; MATLAB; VCLMS; adaptive filtering algorithm; power system harmonic estimation; variable constrained based LMS algorithm; variable constrained based least mean square; white Gaussian noise; Electrical engineering; Estimation; Gaussian noise; Harmonic analysis; Least squares approximations; MATLAB; Power systems; Extended Least Mean Square (ELMS); Forgetting Factor Recursive Least Square (FF-RLS); Least Mean Square (LMS); Recursive Least Square (RLS); Variable Constrained based Least Mean Square (VCLMS);
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Communications and Signal Processing (ICCSP), 2014 International Conference on
  • Conference_Location
    Melmaruvathur
  • Print_ISBN
    978-1-4799-3357-0
  • Type

    conf

  • DOI
    10.1109/ICCSP.2014.6950025
  • Filename
    6950025