• DocumentCode
    2602238
  • Title

    Application of neural networks in wind power (generation) prediction

  • Author

    Mishra, Alok Kumar ; Ramesh, L.

  • Author_Institution
    Dept. of Electr. Eng., Dr MGR Univ., Chennai, India
  • fYear
    2009
  • fDate
    6-7 April 2009
  • Firstpage
    1
  • Lastpage
    5
  • Abstract
    Wind power generation increases rapidly. The available wind energy depends on the wind speed, which is a random variable. For the wind-farm operator, this poses difficulty in the system scheduling and energy dispatching, as the schedule of the wind-power availability is not known in advance. In this paper, we propose an intelligent technique for forecasting wind speed of wind turbine. This technique is based on artificial neural network (ANN). The Back propagation (BP) neural network is then supplied with the data to establish the relationship between the inputs and the output. The model based on the neural network demonstrated a good agreement and produced the wind forecast with the accuracy of 90% and above.
  • Keywords
    load forecasting; neural nets; power system simulation; wind power plants; wind turbines; artificial neural network; back propagation neural network; energy dispatching; forecasting wind speed; neural networks; system scheduling; wind energy; wind power generation; wind turbine; wind-farm operator; Artificial intelligence; Artificial neural networks; Dispatching; Neural networks; Random variables; Wind energy; Wind forecasting; Wind power generation; Wind speed; Wind turbines; Artificial neural network; Wind power generation; Wind speed; Wind turbine;
  • fLanguage
    English
  • Publisher
    ieee
  • Conference_Titel
    Sustainable Power Generation and Supply, 2009. SUPERGEN '09. International Conference on
  • Conference_Location
    Nanjing
  • Print_ISBN
    978-1-4244-4934-7
  • Type

    conf

  • DOI
    10.1109/SUPERGEN.2009.5348160
  • Filename
    5348160