• DocumentCode
    618471
  • Title

    Continuous wind power generation by wind velocity prediction using an optimized prediction error algorithm

  • Author

    Tamilarasi, K. ; Vinoth Kumar, S. ; Balamurugan, P.S.

  • Author_Institution
    Comput. Sci. & Eng., Karpagam Univ., Coimbatore, India
  • fYear
    2013
  • fDate
    11-12 April 2013
  • Firstpage
    1194
  • Lastpage
    1199
  • Abstract
    Each and every developing technologies and all electronic gadgets work in electricity.Windmill plays a vital role in generating current electricity in non-renewable resource. Even though its capital is high and maintenance are too expensive we are moving towards the wind power plant. The major expansion is taking place occurring damages in gearbox and generator due to heavy wind speed. In these proposed system by using the probabilistic neural network (PNN). Controlling the rotation speed of the blades through changing the pitch angle by predicting the wind velocity. The OPEA algorithm is used for an effective predicting the wind speed. Through this we can produce the electricity even the wind speed is higher without any damages in gear and generator.
  • Keywords
    wind power; wind power plants; continuous wind power generation; electricity; electronic gadgets; gearbox; generator; heavy wind speed; nonrenewable resource; optimized prediction error algorithm; probabilistic neural network; wind power plant; wind velocity prediction; windmill; Communications technology; Conferences; OPEA; PNN; Wind velocity; nonrenewable; pitch angle; prediction;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Information & Communication Technologies (ICT), 2013 IEEE Conference on
  • Conference_Location
    JeJu Island
  • Print_ISBN
    978-1-4673-5759-3
  • Type

    conf

  • DOI
    10.1109/CICT.2013.6558282
  • Filename
    6558282