Computational fluid dynamics based iterative learning control for smart rotor enabled fatigue load reduction in wind turbines

Abstract

Smart rotors integrated into the blades of large-scale turbines offer, when used in conjunction with collective and individual pitch control, the potential to significantly improve aerodynamic performance and load control. Of the four main ways to modify the lift on the blades, this work seeks to modify the blade section aerodynamics by damping perturbations in the lift using circulation control by integrating smart devices, such as microtabs or active vortex generators into the blades. This paper uses a computational fluid dynamics model with nonlinear wake effects to represent the flow past an airfoil as an approximate model of the dynamics for the design of iterative learning control algorithms for this problem area. Under a 2-norm measure a two orders of magnitude reduction over the case with no control is established.