Journal cover Journal topic
Wind Energy Science The interactive open-access journal of the European Academy of Wind Energy
https://doi.org/10.5194/wes-2016-38
© Author(s) 2016. This work is distributed under
the Creative Commons Attribution 3.0 License.
Research articles
17 Nov 2016
Review status
This discussion paper has been under review for the journal Wind Energy Science (WES). The revised manuscript was not accepted.
Stochastic Wake Modeling Based on POD Analysis
David Bastine1, Lukas Vollmer2, Matthias Wächter1, and Joachim Peinke1 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.

Citation: Bastine, D., Vollmer, L., Wächter, M., and Peinke, J.: Stochastic Wake Modeling Based on POD Analysis, Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2016-38, 2016.
David Bastine et al.
Interactive discussionStatus: closed
AC: Author comment | RC: Referee comment | SC: Short comment | EC: Editor comment
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RC1: 'Comments and technical corrections', Anonymous Referee #1, 25 Nov 2016 Printer-friendly Version Supplement 
AC1: 'Answers to referee number 1', David Bastine, 13 Feb 2017 Printer-friendly Version 
 
RC2: 'REVIEW', Anonymous Referee #2, 02 Dec 2016 Printer-friendly Version Supplement 
AC2: 'Answer to referee number 2', David Bastine, 13 Feb 2017 Printer-friendly Version 
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.
Modeling of wind turbine wakes plays a key role in the maximization of the power output and...
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