Journal
JOURNAL OF EARTH SYSTEM SCIENCE
Volume 117, Issue 4, Pages 457-463Publisher
INDIAN ACAD SCIENCES
DOI: 10.1007/s12040-008-0045-7
Keywords
wind speed prediction; artificial neural network; curve fitting; ARIMA
Funding
- Indian Space Research Organization
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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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