Wind speed prediction using statistical regression and neural network |
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| Authors: | Makarand A Kulkarni Sunil Patil G V Rama P N Sen |
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| Institution: | (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 |
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| Abstract: | Prediction of wind speed in the atmospheric boundary layer is important for wind energy assessment, 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. |
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| Keywords: | Wind speed prediction artificial neural network curve fitting ARIMA |
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