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      Permanent link:
      https://www.ias.ac.in/article/fulltext/jess/117/04/0457-0463

    • Keywords

       

      Wind speed prediction; artificial neural network; curve fitting; ARIMA.

    • Abstract

       

      Prediction of wind speed in the atmospheric boundary layer is important for wind energy assess- ment,satellite launching and aviation,etc.There are a few techniques available for wind speed prediction,which require a minimum number of input parameters.Four different statistical techniques,viz.,curve fitting,Auto Regressive Integrated Moving Average Model (ARIMA),extrapolation with periodic function and Artificial Neural Networks (ANN)are employed to predict wind speed.These methods require wind speeds of previous hours as input.It has been found that wind speed can be predicted with a reasonable degree of accuracy using two methods,viz.,extrapolation using periodic curve fitting and ANN and the other two methods are not very useful.

    • Author Affiliations

       

      Makarand A Kulkarni1 Sunil Patil2 G V Rama3 P N Sen1

      1. Department of Atmospheric and Space Sciences, University of Pune, Pune 411 007, India.
      2. Department of Physics, University of Pune, Pune 411 007, India.
      3. Meteorological Facility, Sriharikota 524 124, Nellore (Dt), A.P., India.
    • Dates

       
  • Journal of Earth System Science | News

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