Problem Domain
Surface wind plays a crucial role in climate and weather system of the Earth. It has significant impact on agriculture, navigation, structural engineering calculations and reduction of atmospheric pollution as well as the economy of the region as an alternate energy source . Wind speed modelling and forecasting is an important aspect of wind power generation . Our research group is working on wind modelling and forecasting.
Existing Methods
Over the years many tools have been developed for this purpose. A good number of such tools rely on statistical methods,
- ARMA and ARIMA
- models based on probability distribution of wind speed
- Models based on artificial neural networks have also been developed by many authors for making short-term predictions of wind speed and generated wind power
As a matter of fact, none of these forecasting methods, based on time series analysis or meteorological models, is capable of significantly reducing the prediction error compared to the elementary method of persistence and this is usually attributed to the high fluctuations and variability in wind speed. Exploring the source of these random fluctuations in wind speed, especially whether it is stochastic or deterministic, is therefore important both for understanding the nature of the dynamics and for improving the tools used
for prediction.
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