Abstract
AbstractThe natural operation of wind turbines (WT) shows a nonlinear behavior which makes it difficult for the system to be controlled. Because of this, artificial intelligence techniques appear as promising control solutions. In this work, artificial neural networks (ANN) are used to complement the Direct Speed Control (DSC) of a wind turbine. Specifically, a neural network is used for the Maximum Power Point Tracking (MPPT) of a wind turbine model, controlling the generator speed and maintaining the active power into the correct levels to reach a power coefficient (\({C}_{p}\)) within its optimum values. The real characteristics of a 1.5 MW wind turbine are considered. OpenFast and Matlab/Simulink software tools are used to model and simulate the non-linear WT and the controller, respectively. The intelligent proposed solution is compared with the standard control embedded in OpenFast with satisfactory results.KeywordsNeural networksDirect controlMPPTPower coefficientWind turbine
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