No abstract

The inclusion of smart devices in wind turbine rotor blades could, in conjunction with collective and individual pitch control, improve the aerodynamic performance of the rotors. This is currently an active area of research with the primary objective of reducing the fatigue loads but mitigating the effects of extreme loads is also of interest. The aerodynamic loads on a wind turbine blade contain periodic and non-periodic components and one approach is to consider the application of iterative learning control algorithms. In this paper, the control design is based on a simple, in relative terms, computational fluid dynamics model that uses non-linear wake effects to represent flow past an airfoil. A representation for the actuator dynamics is included to undertake a detailed investigation into the level of control possible and on how performance can be effectively measured.

Improving the aerodynamic effectiveness and hence energy production of wind turbines is of critical importance and there is currently research into to the inclusion of smart devices in rotor blades in conjunction with collective and individual pitch control. The main objective is to reduce fatigue loads which have periodic and non-periodic components. This paper gives results on the use of iterative learning control in this application area based on first constructing a simple but realistic computational fluid dynamics model to represent flow past an airfoil. As a first investigation into the control of wind turbines using such a model, the design of control laws with a simple structure is investigated.

Improving the aerodynamic effectiveness and hence energy production of wind turbines is of critical importance and there is currently research into to the inclusion of smart devices in rotor blades in conjunction with collective and individual pitch control. The main objective is to reduce fatigue loads which have periodic and non-periodic components. This paper gives further results on the use of iterative learning control in this application area based on first constructing a simple but realistic computational fluid dynamics model to represent flow past an airfoil. The new results are based on the use of pressure sensors to estimate the lift.

Smart rotors integrated into the blades of largescale 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.