Super-short Term Wind Speed Prediction based on Artificial Neural Networks for Wind Turbine Control Applications

摘要

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.