The intent of this experiment was to develop standards for using the LES (Large Eddy Simulation) turbulence scheme in CFD (Computational Fluid Dynamics) for the wind farm application, to develop a method to predict wind turbine wakes that is more accurate than using RANS (Reynolds Averaged Navier Stokes), and to make comparisons to RANS results.
Although there have been many previous attempts at predicting the propagation of a wind turbine wake through a wind turbine farm, most use a mixture of empirical models and CFD. Of the few that are pure CFD, all known use the RANS turbulence closure model. This is primarily due to the larger computational resources required for LES calculations.
The wind farm geometry was simplified to two turbines in a row aligned with the wind direction. This was necessary to have a computational domain of a size that matched the time frame and computational resources available for this effort. Turbine spacings of 7, 9, and 11 diameters (D) were evaluated. The domain size and mesh density were evaluated through verification studies.
In order to better approximate the true nature of an atmospheric boundary layer, numerical "wind" was created a priori, and then used as the inlet boundary condition. Numerical wind was created for both thermally neutral and unstable atmospheric boundary layer conditions. Stable boundary layer conditions are left to future efforts.
The results achieved using LES are the best possible for a desk top computer in the allotted time frame. While the LES results are not fully independent of the mesh density or domain size, they do represent a significant improvement over the results achieve using the RANS turbulence closure technique.
Validation was done through comparing the predicted downstream turbine power deficit results to the measurements of the Horns Rev wind farm documented through the ENDOW and UPWIND projects. Horizontal velocity profiles downstream of the 2nd turbine are also presented, however no measurements are available to compare with.
LES is currently commonly used for large scale atmospheric studies, but at present it is considered novel for use in turbine wake prediction.
This effort produced results that are comparable to experimental results and showed clear areas to improve computational issues.
|Commitee:||Hertzberg, Jean, Mohseni, Kamran, Moriarty, Patrick|
|School:||University of Colorado at Boulder|
|School Location:||United States -- Colorado|
|Source:||MAI 47/01M, Masters Abstracts International|
|Subjects:||Aerospace materials, Mechanical engineering|
|Keywords:||CFD, Fluent, LES, Wake prediction, Wind farm, Wind turbine|
Copyright in each Dissertation and Thesis is retained by the author. All Rights Reserved
The supplemental file or files you are about to download were provided to ProQuest by the author as part of a
dissertation or thesis. The supplemental files are provided "AS IS" without warranty. ProQuest is not responsible for the
content, format or impact on the supplemental file(s) on our system. in some cases, the file type may be unknown or
may be a .exe file. We recommend caution as you open such files.
Copyright of the original materials contained in the supplemental file is retained by the author and your access to the
supplemental files is subject to the ProQuest Terms and Conditions of use.
Depending on the size of the file(s) you are downloading, the system may take some time to download them. Please be