Application of wavelet and neural network models for wind speed and power generation forecasting in a Brazilian experimental wind park

The wind speed and wind generation forecasting are of extreme importance to aid in the planning studies and scheduled operation of hydrothermal and wind systems. This kind of generation is in the incipient phase in Brazil; however, the perspectives are mainly exciting aiming for increasing the potential of electricity generation. The use of wind power for producing electricity can create uncertainties in the generation. Therefore, the development of wind forecasting models is essential to integrate this kind of energy source with the generation system in an effective way. This work proposes the application of Artificial Neural Networks - ANN to produce a tool capable of accomplishing the wind speed forecasting. The ANN model is created using input data preprocessing by the Wavelet Transform - WT to extract important characteristics of the wind speed. Outputs of several ANNs show clearly the potential of the model based on WT compared with the others.