Super-short term wind speed prediction based on artificial neural networks for wind turbine control applications

Paper in proceeding, 2018

In this paper, an Artificial Neural Network (ANN) methodology to cast super-short term (under 30 seconds) wind speed predictions is presented. The aim is to obtain computationally efficient super-short term predictions that will be used in Wind Turbine (WT) real-time control applications in the future. A combination of power measurements and meteorological data are used to obtain the estimated rotor effective wind speed. This signal is then used as an input to train the ANNs. Additionally, a polynomial fitting is proposed to enhance the ANN results at each prediction step. The proposed strategy is compared with a classic persistence approach in order to quantify the achieved improvement.