• DocumentCode
    924028
  • Title

    Very short-term wind forecasting for Tasmanian power generation

  • Author

    Potter, Cameron W. ; Negnevitsky, Michael

  • Author_Institution
    Sch. of Eng., Univ. of Tasmania, Australia
  • Volume
    21
  • Issue
    2
  • fYear
    2006
  • fDate
    5/1/2006 12:00:00 AM
  • Firstpage
    965
  • Lastpage
    972
  • Abstract
    This paper describes very short-term wind prediction for power generation, utilizing a case study from Tasmania, Australia. Windpower presently is the fastest growing power generation sector in the world. However, windpower is intermittent. To be able to trade efficiently, make the best use of transmission line capability, and address concerns with system frequency in a re-regulated system, accurate very short-term forecasts are essential. The research introduces a novel approach-the application of an adaptive neuro-fuzzy inference system to forecasting a wind time series. Over the very short-term forecast interval, both windspeed and wind direction are important parameters. To be able to be gain the most from a forecast on this time scale, the turbines must be directed toward on oncoming wind. For this reason, this paper forecasts wind vectors, rather than windspeed or power output.
  • Keywords
    fuzzy neural nets; load forecasting; power engineering computing; power transmission; time series; wind power plants; Tasmanian power generation; adaptive neurofuzzy inference system; short-term wind forecasting; transmission line capability; wind power; wind time series; Australia; Frequency; Hydroelectric power generation; Oceans; Power generation; Power transmission lines; Production; Wind energy generation; Wind forecasting; Wind power generation; Adaptive neuro-fuzzy inference systems (ANFIS); intelligent systems; very short-term forecasting; windpower;
  • fLanguage
    English
  • Journal_Title
    Power Systems, IEEE Transactions on
  • Publisher
    ieee
  • ISSN
    0885-8950
  • Type

    jour

  • DOI
    10.1109/TPWRS.2006.873421
  • Filename
    1626404