Wind Turbine Power Coefficient Identification Using the FAST Simulator Data and Design of Switching Multiple Model Predictive Control

Due to the economic aspects and the global warming aims, the wind turbines have attracted a notable percent of the research subjects in the recent decades. The motivation of this paper is identification of the Wind Turbine (WT) power coefficient curve and improvement of the power tracking performance. To accomplish the first, using the steady state mode of the Fatigue Aerodynamics Structures and Turbulence (FAST) simulator, we collect the necessary data pack and, then, identify the power coefficient curve. For the second aim, a Multiple Model Predictive Control (MMPC) with a new adaptive structure is designed. The model selection, through the constructed model bank, is handled based on the estimated wind speed using the Newton-Rapshon (NR) and the kalman filter algorithm. The new adaptation law based on the Lyapunove theory damps the hazardous chattering in the control signal coming from the sudden switching between controllers and models. This will improve the wind turbine longevity. Afterwards, to investigate the effectiveness of the given method, the suggested algorithm is implemented on the NREL 1.5 MW baseline WT using the FAST simulator. Finally, the simulation results validate the efficiency of the suggested control system in the tracking error improvement, oscillation reduction in the generator torque and consequently mechanical power, simultaneously.