• DocumentCode
    681691
  • Title

    Short-term wind prediction using an ensemble of Particle Swarm Optimised FIR filters

  • Author

    Dowell, Jethro ; Weiss, Steven

  • Author_Institution
    Wind Energy Syst. Centre for Doctoral Training, Univ. of Strathclyde, Glasgow, UK
  • fYear
    2013
  • fDate
    2-3 Dec. 2013
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Due to the large and increasing penetration of wind power around the world, accurate power production forecasts are required to manage power systems and wind power plants. In this paper we propose an ensemble of particle swarm optimised filtering technique for 1-hour-ahead prediction of hourly mean wind speed and direction. The performance of the new method is assessed by testing it on data from 13 locations around the UK where it performs comparably to linear techniques but is able to provide significant improvement at a subset of locations.
  • Keywords
    FIR filters; filtering theory; load forecasting; particle swarm optimisation; wind power plants; 1 hour ahead prediction; FIR Filters; filtering technique; hourly mean wind direction; hourly mean wind speed; particle swarm optimisation; power production forecast; short term wind prediction; wind power penetration; wind power plant;
  • fLanguage
    English
  • Publisher
    iet
  • Conference_Titel
    Intelligent Signal Processing Conference 2013 (ISP 2013), IET
  • Conference_Location
    London
  • Electronic_ISBN
    978-1-84919-774-8
  • Type

    conf

  • DOI
    10.1049/cp.2013.2065
  • Filename
    6740514