Application of artificial neural network for short term wind speed forecasting

The wind speed forecasting is important for managing issues arising because of intermittency and variability of wind in wind power integration in electrical power systems. The main objective of this work is short-term forecasting of wind speed on the basis of historical time series meteorological data. Nonlinear data driven model is used here for forecasting the wind speed as it is a powerful and adaptive modeling tool for forecasting purpose. Five different ANN models are developed. The minimum mean square error (MSE) for these models are found on the basis of network performance. The developed model with least error can be used for forecasting wind speed for predicting power generation from wind turbines within error of ±30% (as per CERC).