Iterative learning control for load control of smart turbine blades with variable rotation rates

Author

Tutty, Owen ; Blackwell, Mark ; Rogers, Eric ; Sandberg, Richard

Author_Institution

Fac. of Eng. & the Environ., Univ. of Southampton, Southampton, UK

fYear

2015

fDate

1-3 July 2015

Firstpage

3690

Lastpage

3695

Abstract

Previous work has demonstrated the feasibility of iterative learning control applied to wind turbine blades with smart rotors in order to smooth the natural fluctuations in aerodynamic load through vorticity generation at the trailing edge using devices such as flaps. Here we extend this work by a) including a more physically realistic model of the flow by adding a model of the wake which evolves with the flow downstream of the blade, and b) allowing for fluctuations in the period of rotation of the blade, reflecting a situation found in practise. Again, ILC control is found to produce a significant reduction in 2-norm and ∞-norm measures of the variation of the load.

Keywords

aerodynamics; blades; iterative learning control; rotors; wakes; wind turbines; ∞-norm measures; 2-norm measures; ILC; aerodynamic load; flaps; iterative learning control; smart rotors; smart turbine blade load control; variable rotation rates; vorticity generation; wake; wind turbine blades; Atmospheric modeling; Automotive components; Blades; Computational fluid dynamics; Load modeling; Mathematical model; Wind turbines;

fLanguage

English

Publisher

ieee

Conference_Titel

American Control Conference (ACC), 2015

Conference_Location

Chicago, IL

Print_ISBN

978-1-4799-8685-9

Type

conf

DOI

10.1109/ACC.2015.7171903

Filename

7171903