• DocumentCode
    775994
  • Title

    Fuzzy neural network and fuzzy expert system for load forecasting

  • Author

    Dash, P.K. ; Liew, A.C. ; Rahman, S.

  • Author_Institution
    Dept. of Electr. Eng., Regional Eng. Coll., Rourkela, India
  • Volume
    143
  • Issue
    1
  • fYear
    1996
  • fDate
    1/1/1996 12:00:00 AM
  • Firstpage
    106
  • Lastpage
    114
  • Abstract
    A hybrid neural network fuzzy expert system is developed to forecast short-term electric load accurately. The fuzzy membership values of the load and other weather variables are the inputs to the neural network, and the output comprises the membership values of the predicted load. An adaptive fuzzy correction scheme is used to forecast the final load by using a fuzzy rule base and fuzzy inference mechanism. Extensive studies have been performed for all seasons, and a few examples are presented in the paper, average, peak and hourly load forecasts
  • Keywords
    expert systems; fuzzy neural nets; inference mechanisms; learning (artificial intelligence); load forecasting; power system analysis computing; adaptive fuzzy correction scheme; fuzzy inference mechanism; fuzzy membership values; fuzzy rule base; hourly load forecasts; load forecasting; neural network fuzzy expert system; peak load forecasts; short-term electric load; weather variables;
  • fLanguage
    English
  • Journal_Title
    Generation, Transmission and Distribution, IEE Proceedings-
  • Publisher
    iet
  • ISSN
    1350-2360
  • Type

    jour

  • DOI
    10.1049/ip-gtd:19960314
  • Filename
    488069