• DocumentCode
    3606492
  • Title

    Detection Of Power Quality Disturbances Using Deformation Tensor Parameters

  • Author

    Arias, Santiago ; Ustariz, Armando Jaime ; Cano, Eduardo Antonio

  • Author_Institution
    Univ. Nac. de Colombia, Bogota, Colombia
  • Volume
    13
  • Issue
    7
  • fYear
    2015
  • fDate
    7/1/2015 12:00:00 AM
  • Firstpage
    2106
  • Lastpage
    2113
  • Abstract
    This paper introduces a new segmentation algorithm of voltage waveforms. This new algorithm uses the strength of the tensor concept of the voltage signals to generate a unique pattern of deformation in three-phase systems. This deformation pattern is used to perform segmentation by detecting residues. In the process of segmentation, a modification to the Kalman filter has been proposed based on the work presented by Rakhee Panigrahi and Cesar Duarte. With this modification, we have obtained a robust response with a term included for estimating adaptively to sudden changes in the system. Additionally, it has been implemented a strategy of adaptive thresholding to adapt to noisy signals. This segmentation strategy is validated using a set of synthetic signals with variation of the remnant voltage and the starting point of the disturbance. Finally, the proposed algorithm is tested with a set of real signals.
  • Keywords
    Kalman filters; deformation; power supply quality; power system faults; Kalman filter; adaptive thresholding; deformation pattern; deformation tensor parameters; noisy signals; power quality disturbances; remnant voltage; segmentation algorithm; synthetic signals; tensor concept; three-phase systems; voltage signals; voltage waveforms; Color; Covariance matrices; Kalman filters; Media; Power quality; Robustness; Tensile stress; Adaptive kalman filter; Adaptive threshold; Electromagnetic perturbations; Segmentation; Tensor analysis; Voltage sags;
  • fLanguage
    English
  • Journal_Title
    Latin America Transactions, IEEE (Revista IEEE America Latina)
  • Publisher
    ieee
  • ISSN
    1548-0992
  • Type

    jour

  • DOI
    10.1109/TLA.2015.7273765
  • Filename
    7273765