• DocumentCode
    1662296
  • Title

    Comparison of the fuzzy regression analysis and the least squares regression method to the electrical load estimation

  • Author

    Zalewski, W.

  • Author_Institution
    Bialystok Tech. Univ., Poland
  • Volume
    1
  • fYear
    1998
  • Firstpage
    207
  • Abstract
    An essential point in correct calculations and analysis of power distribution systems is a proper evaluation of loads. The acquisition of this data is complex because of a large number of nodes and their area distribution. As a rule receiving nodes are not equipped with stationary measuring instruments so measurements of loads are performed only sporadically. The theory which enables efficient description of unreliable and inaccurate data, and relationship between them, is the fuzzy set theory. The paper presents possibilities of application of the fuzzy set theory to power distribution system calculations. Unreliable and inaccurate input data were modeling by means of fuzzy numbers. A regression model, expressing the correlation between a substation peak load and a set of customer features (explanatory variables), existing in the substation population, is determined. The fuzzy set approach and standard regression method are compared
  • Keywords
    distribution networks; fuzzy set theory; least squares approximations; load forecasting; statistical analysis; electrical load estimation; fuzzy regression analysis; fuzzy set theory; least squares regression method; power distribution system calculations; power distribution systems; regression model; stationary measuring instruments; substation peak load; Fuzzy sets; Instruments; Least squares methods; Load modeling; Power distribution; Power system modeling; Regression analysis; Set theory; Shape measurement; System buses;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Electrotechnical Conference, 1998. MELECON 98., 9th Mediterranean
  • Conference_Location
    Tel-Aviv
  • Print_ISBN
    0-7803-3879-0
  • Type

    conf

  • DOI
    10.1109/MELCON.1998.692372
  • Filename
    692372