Neural networks and reinforcement learning in wind turbine control - J. E. Sierra-García; M. Santos (Revista Iberoamericana de Automática e Informática Industrial RIAI)
Pitch control of wind turbines is complex due to the intrinsic non-linear behavior of these devices, and the external disturbances they are subjected to related to changing wind conditions and other meteorological phenomena. This difficulty is even higher in the case of floating offshore turbines, due to ocean currents and waves. Neural networks and other intelligent control techniques have been proven very useful for the modeling and control of these complex systems. Thus, this paper presents different intelligent control configurations applied to wind turbine pitch control. Direct pitch control based on neural networks and reinforcement learning, and some hybrid control configurations are described. The usefulness of neuro-estimators for the improvement of controllers is also presented. Finally, some of these techniques are used in an application example with a land wind turbine model.