Periodic LQG Wind Turbine Control with Adaptive Load Reduction
Research output: Contribution to journal › Research article › Invited › peer-review
Contributors
Abstract
A periodic linear quadratic Gaussian (LQG) control law augmented with a reference point adaption to enable adequate rotor speed tracking and sufficient load reductions for a wind turbine is presented. The solution of the periodic LQG control problem is based on solving two periodic Ricatti differential equations in continuous time with a multiple shooting integration technique. For this, the available gridded linear time-variant description of the turbine is converted to a harmonic representation using harmonic Fourier approximation. While the
periodic LQG controller provides rotor speed tracking and effective damping of the aeroelastic blade modes, the reference point adaption explicitly reduces the loads resulting from the periodic operation of the turbine rotor at the rotor rotational frequency. The performance of the proposed control system is compared against a baseline controller in realistic wind scenarios using a high
fidelity nonlinear simulator. The results show a significant damage equivalent load reduction while maintaining adequate rotor speed tracking.
periodic LQG controller provides rotor speed tracking and effective damping of the aeroelastic blade modes, the reference point adaption explicitly reduces the loads resulting from the periodic operation of the turbine rotor at the rotor rotational frequency. The performance of the proposed control system is compared against a baseline controller in realistic wind scenarios using a high
fidelity nonlinear simulator. The results show a significant damage equivalent load reduction while maintaining adequate rotor speed tracking.
Details
Original language | English |
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Pages (from-to) | 7674-7679 |
Number of pages | 6 |
Journal | IFAC-PapersOnLine |
Volume | 56(2023) |
Issue number | 2 |
Publication status | Published - 1 Jul 2023 |
Peer-reviewed | Yes |
Conference
Title | 22nd World Congress of the International Federation of Automatic Control |
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Abbreviated title | IFAC 2023 |
Conference number | 22 |
Duration | 9 - 14 July 2023 |
Website | |
Degree of recognition | International event |
Location | Pacific Convention Plaza Yokohama |
City | Yokohama |
Country | Japan |
External IDs
Scopus | 85184960824 |
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Mendeley | 4f845394-da5c-3efe-b060-1eed45372b39 |
ORCID | /0000-0001-6734-704X/work/167216632 |