Neural Networks model to detect wind turbine dynamics

The wind has been a source of energy for the human being since ancient times, mainly because it is widely available in different areas of the world. Several companies are investing huge capital to build wind farms with the aim of obtaining the maximum possible economic return. Therefore, a precise definition of the dynamics of operation of the turbines is necessary in order to appropriately define a system that takes full advantage of the wind energy. In this study, the measurements of the noise emitted by different wind turbines were used to obtain information on the dynamics of operation. A selected range of average spectral levels was extracted in a 1/3 octave band. A model based on the neural network for detection has been developed and applied to identify the operating conditions of wind turbines. The prediction and identification model have returned a high precision that suggests the adoption of this tool for several other applications.