Preprints
https://doi.org/10.5194/wes-2024-154
https://doi.org/10.5194/wes-2024-154
27 Nov 2024
 | 27 Nov 2024
Status: this preprint is currently under review for the journal WES.

Obtaining fatigue-based frequency domain specifications for the design of controllers in wind turbines

Irene Miquelez-Madariaga, Jesús Arellano, Daniel Lacheta-Lecumberri, and Jorge Elso

Abstract. This work presents a methodology to (i) estimate fatigue using linear models and (ii) generate control specifications directly linked to the mechanical fatigue caused by driving loads for a wind turbine applications. The method is intended for frequency domain controller design techniques such as QFT or H and is based on Dirlik’s method for fatigue assessment. The main advantage of using frequency domain approach is that the need of computationally expensive processess such as the generation of turbulent wind fields or aeroelastic simulations is reduced. As a consequence, the controller design method becomes more agile. The method has been validated by designing controllers for the reference 15 MW wind turbine based on fatigue specifications, obtaining simulation results with OpenFAST and comparing the fatigue results from a rainflow algorithm with the linear estimation. Fatigue has been reduced by 22 % to 35 % at different wind speeds corresponding to above rated operation. The mean fatigue estimation error is 1.07 %, proving the method is suitable for a wind turbine control application.

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Irene Miquelez-Madariaga, Jesús Arellano, Daniel Lacheta-Lecumberri, and Jorge Elso

Status: open (until 25 Dec 2024)

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Irene Miquelez-Madariaga, Jesús Arellano, Daniel Lacheta-Lecumberri, and Jorge Elso
Irene Miquelez-Madariaga, Jesús Arellano, Daniel Lacheta-Lecumberri, and Jorge Elso

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Short summary
This paper presents a method for obtaining mechanical fatigue estimations from linear models and fatigue-based specifications for the design of controllers for wind turbines. The method is validated by the design of controllers for a 15 MW reference wind turbine. The error in the fatigue estimation is smaller than 2 % and fatigue loads are successfully reduced.
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