Preprints
https://doi.org/10.5194/wes-2021-91
https://doi.org/10.5194/wes-2021-91

  22 Sep 2021

22 Sep 2021

Review status: this preprint is currently under review for the journal WES.

4D wind field generation for the aeroelastic simulation of wind turbines with lidars

Yiyin Chen1,, Feng Guo2,, David Schlipf2, and Po Wen Cheng1 Yiyin Chen et al.
  • 1Stuttgart Wind Energy (SWE), Institute of Aircraft Design, University of Stuttgart, Allmandring 5b, 70569 Stuttgart, Germany
  • 2Wind Energy Technology Institute, Flensburg University of Applied Sciences, Kanzleistraße 91-93, 24943 Flensburg, Germany
  • These authors contributed equally to this work.

Abstract. Lidar-assisted control (LAC) of wind turbines is a control concept that takes advantage of a nacelle-mounted lidar (a remote sensing device) to measure upstream wind speeds of a turbine to allow a preview of the incoming turbulence. Because the turbine will not be exposed to the identical turbulence as that measured by the lidar in advance, the simulation of a LAC system will be more realistic if wind evolution can be modelled in the wind field generation. Since the commonly used 3D stochastic wind field generation method does not include wind evolution, in this paper, we aim to extend the 3D method to 4D to enable the modelling of wind evolution along the wind direction. The most novel part of this research is that we propose a two-step Cholesky decomposition approach for the factorization of the coherence matrices in the wind field generation. With this approach, 4D wind fields can be generated by combining multiple statistically independent 3D wind fields. To enable better integration of the 4D method into the common workflow of wind turbine simulations, we implement the 4D method as an open-access tool evoTurb in combination with TurbSim and Mann turbulence generator. Moreover, since 4D wind field generation is supposed to be coupled with lidar simulations, and considering the range weighting effect of lidars and eventually multiple range gates, a 4D wind field will contain many more simulation points than a 3D one. To avoid excessive computational effort, we further investigate the impacts of the spatial discretization in 4D wind fields on lidar simulations to provide some insights to optimize the application of 4D wind field generation.

Yiyin Chen et al.

Status: open (until 21 Nov 2021)

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Yiyin Chen et al.

Yiyin Chen et al.

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Short summary
Lidar-assisted control of wind turbines requires a wind field generator capable of simulating wind evolution. Out of this need, we extend the Veer’s method for 3D wind field generation to 4D. We propose a two-step Cholesky decomposition approach. Based on this, we develop a 4D wind field generator – evoTurb coupled with TurbSim and Mann turbulence generator. We further investigate the impacts of the spatial discretization in 4D wind fields on lidar simulations to provide practical suggestions.