• DocumentCode
    25157
  • Title

    Forecasting of the Transformer Core Destruction Factor by means of Multivariate Methods for Data Analysis

  • Author

    Diaz, G.A. ; Romero, A.A. ; Mombello, E. ; Furlan, N.

  • Author_Institution
    Univ. Nac. de San Juan (UNSJ), San Juan, Argentina
  • Volume
    11
  • Issue
    1
  • fYear
    2013
  • fDate
    Feb. 2013
  • Firstpage
    492
  • Lastpage
    498
  • Abstract
    In designing and building of transformers, the core destruction factor is the superposition of all effects that cause a difference between the value of the core losses calculated during the design stage of the unit and the measured value after built. In this paper, two methods for forecasting the core destruction factor are proposed. One based on Mahalanobis distance and the other one based on cluster analysis. A comparison of the results obtained by conventional calculation procedure with respect to those obtained through the proposed methodologies is developed. Finally, the expected cost savings by applying the methods proposed in this article are estimated.
  • Keywords
    data analysis; pattern clustering; transformer cores; Mahalanobis distance; cluster analysis; core losses; cost savings; data analysis; multivariate methods; transformer core destruction factor forecasting; Covariance matrices; Forecasting; Media; Reactive power; Robustness; Silicon compounds; Transformer cores; Mahalanobis distance; clustering; forecasting; transformer losses;
  • fLanguage
    English
  • Journal_Title
    Latin America Transactions, IEEE (Revista IEEE America Latina)
  • Publisher
    ieee
  • ISSN
    1548-0992
  • Type

    jour

  • DOI
    10.1109/TLA.2013.6502851
  • Filename
    6502851