Preprints
https://doi.org/10.5194/wes-2016-38
https://doi.org/10.5194/wes-2016-38

  17 Nov 2016

17 Nov 2016

Review status: this preprint was under review for the journal WES but the revision was not accepted.

Stochastic Wake Modeling Based on POD Analysis

David Bastine1, Lukas Vollmer2, Matthias Wächter1, and Joachim Peinke1 David Bastine et al.
  • 1AG TWiSt, Institute of Physics, ForWind, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg
  • 2AG Energy Meteorology, Institute of Physics, ForWind, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg

Abstract. In this work, large eddy simulation data is analyzed to investigate a new stochastic modeling approach for the wake of a wind turbine. The data is generated by the LES model PALM combined with an actuator disk with rotation representing the turbine. After applying a proper orthogonal decomposition (POD), three different stochastic models for the weighting coefficients of the POD modes are deduced resulting in three wake models. Their performance is investigated mainly on the basis of aeroelastic simulations of a wind turbine in the wake. Three different load cases and their statistic characteristics are compared for the original LES, truncated PODs and the stochastic wake models including different numbers of POD modes. It is shown that approximately six POD modes are enough to capture the load dynamics on large temporal scales. Modeling the weighting coefficients as independent stochastic processes leads to similar load characteristics as in the case of the truncated POD. To complete this simplified wake description, we show evidence that the small-scale dynamics can be grasped by adding to our model a homogeneous turbulent field. In this way, we present a procedure how to derive stochastic wake models from costly CFD calculations or elaborated experimental investigations. These numerically efficient models provide the added value of possible long-term studies. Depending on the aspects of interest, different minimalized models may be obtained.

David Bastine et al.

 
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Status: closed
Status: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
Printer-friendly Version - Printer-friendly version Supplement - Supplement

David Bastine et al.

David Bastine et al.

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Short summary
Modeling of wind turbine wakes plays a key role in the maximization of the power output and lifetime of wind turbines in wind farms. In order to capture important dynamic and turbulent aspects of the wake, a new stochastic modeling approach is presented in this work. The resulting new kind of stochastic wake model captures important characteristics of loads which act on wind turbines in the wake. It might therefore be of great use for the planing and controlling of wind farms.