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Wind turbine aerodynamic load fluctuation reduction using model based iterative learning control

Wind turbine aerodynamic load fluctuation reduction using model based iterative learning control
Wind turbine aerodynamic load fluctuation reduction using model based iterative learning control
Control of aerodynamic loads in wind turbines is a critical issue in terms of keeping them economically competitive with alternative energy sources. This paper continues the investigation of the use of Iterative Learning Control (ILC) for load control in wind turbines with smart devices on rotor blades. Smart devices controlled by ILC are used to modify the blade section aerodynamics such that the fluctuations in lift due to periodic disturbances on the blades are minimized. In previous work, simple structure ILC laws were considered where the variables were chosen without the use of a model of the dynamics akin to auto-tuning design in standard control systems. This previous work demonstrated the potential of ILC in this area but, as expected, are limited in what they can deliver. This paper considers model based ILC for this application area where a Proper Orthogonal Decomposition based reduced order model of the flow is first constructed. The resulting model is used to design a norm optimal ILC scheme whose performance is evaluated in simulation.
6384-6389
Institute of Electrical and Electronics Engineers Inc.
Nowicka, Weronika, Natalia
e1ac7b8b-e806-4bb8-8a6f-55c54c18c7e2
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Tutty, Owen
c9ba0b98-4790-4a72-b5b7-09c1c6e20375
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72
Nowicka, Weronika, Natalia
e1ac7b8b-e806-4bb8-8a6f-55c54c18c7e2
Chu, Bing
555a86a5-0198-4242-8525-3492349d4f0f
Tutty, Owen
c9ba0b98-4790-4a72-b5b7-09c1c6e20375
Rogers, Eric
611b1de0-c505-472e-a03f-c5294c63bb72

Nowicka, Weronika, Natalia, Chu, Bing, Tutty, Owen and Rogers, Eric (2018) Wind turbine aerodynamic load fluctuation reduction using model based iterative learning control. In 2018 Annual American Control Conference, ACC 2018. vol. 2018-June, Institute of Electrical and Electronics Engineers Inc. pp. 6384-6389 . (doi:10.23919/ACC.2018.8431576).

Record type: Conference or Workshop Item (Paper)

Abstract

Control of aerodynamic loads in wind turbines is a critical issue in terms of keeping them economically competitive with alternative energy sources. This paper continues the investigation of the use of Iterative Learning Control (ILC) for load control in wind turbines with smart devices on rotor blades. Smart devices controlled by ILC are used to modify the blade section aerodynamics such that the fluctuations in lift due to periodic disturbances on the blades are minimized. In previous work, simple structure ILC laws were considered where the variables were chosen without the use of a model of the dynamics akin to auto-tuning design in standard control systems. This previous work demonstrated the potential of ILC in this area but, as expected, are limited in what they can deliver. This paper considers model based ILC for this application area where a Proper Orthogonal Decomposition based reduced order model of the flow is first constructed. The resulting model is used to design a norm optimal ILC scheme whose performance is evaluated in simulation.

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Wind Turbine Aerodynamic Load Fluctuations using Model Based - Accepted Manuscript
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Accepted/In Press date: 20 January 2018
e-pub ahead of print date: 16 August 2018
Additional Information: Will need embargo to end of conference at least.
Venue - Dates: 2018 Annual American Control Conference, ACC 2018, United States, 2018-06-26 - 2018-06-28

Identifiers

Local EPrints ID: 418180
URI: http://eprints.soton.ac.uk/id/eprint/418180
PURE UUID: f4b400c4-0240-4b1d-ae28-3a4bba08906c
ORCID for Weronika, Natalia Nowicka: ORCID iD orcid.org/0000-0002-7049-1162
ORCID for Bing Chu: ORCID iD orcid.org/0000-0002-2711-8717
ORCID for Eric Rogers: ORCID iD orcid.org/0000-0003-0179-9398

Catalogue record

Date deposited: 23 Feb 2018 17:30
Last modified: 07 Oct 2020 02:11

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Contributors

Author: Weronika, Natalia Nowicka ORCID iD
Author: Bing Chu ORCID iD
Author: Owen Tutty
Author: Eric Rogers ORCID iD

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