Modular framework allowing to scan a numerical wind field with a virtual lidar and create constrained turbulent wind fields for wind turbine simulations.
The framework aims to provide an open source base for such tests but also to be used as a platform where other modules (e.g. different velocity vector reconstruction methods) can be easily added and tested. More information on motivation and possible applications can be found in [1] and [6].
The framework is based around a wrapper script calling the different modules. The input/output definition is done through a function that gathers all the necessary parameters called InputParameters.m. In principal, this should be the only interaction with the user. The different functionalities (e.g. performing virtual lidar measurements or constraining the windfields) are activated by using the relevant flags defined in the inputs.
The main IO interface of ViConDAR. Here you can switch on/off flags, define parameters and request plots. Exact definitions of flags and variables can be found in the code comments. Any new modules should have all relevant flags and parameters defined here.
Main wrapper script to be executed. This part should be modified only to call a new module if one is added.
All functions required for VIConDAR are gathered here. Any new modules should be added here.
This folder contains scripts used for batch processing and other small useful tools. These run as stand alone and do not interface directly with ViConDAR.
The other directories are defined in the InputParameters.m and are created while the code is running. These directories include folders for lidar outputs, inputs to constrained turbulence generators as well as outputs
To check everything works and see the format of the files, a test file is provided. Please read the readme file in the folder for instructions on how to run the test cases.
In order to maintain modularity, any new addition should respect the structure of ViConDAR. The data format should be kept the same and all the rest of the functionalities should remain functional. The best practice would be to create a function with your new addition that will be added on top of the existing functions. Moreover, relevant flags and parameter definitions should be added in the InputParameter.m file. Once you have tested your implementation in your personal fork please create a pull request to the master stating your exact modifications as well as an example test case. After reviewing it we will add it to the master acknowledging the contribution.
To report a bug or a feature request as well as any other comment please use the issues functionality of github. We have created templates for bugs and feature requests, please use these. In case of other comments please use the empty issue form.
- The input windfields files can be created with any kind of turbulence generator as long as they are converted to the global Vicondar format. An example of the structure of such a file is included in the test files folder (TEST_Sh25_SD01_V15_TI05.mat). Currently, Turbsim by NREL (https://github.com/OpenFAST/openfast/tree/master/modules/turbsim) and the Mann turbulence generator by DTU (https://www.hawc2.dk/download/pre-processing-tools) are directly supported with relevant code in the functions and HelpfulStandAlone folders of this repository. The python script for converting the Mann format to the Vicondar format is written by Davide Conti from DTU Wind Energy.
- The constrained turbulence generators connected to ViConDAR are Turbsim V2.00 Alpha from NREL (https://github.com/OpenFAST/openfast/tree/master/modules/turbsim), PyConTurb from DTU (https://gitlab.windenergy.dtu.dk/pyconturb/pyconturb) and Nikolay Dimitrov's method from DTU. The turbsim executable is included in the present repository compiled by SWE (Matthias Kretschmer) including some relevant bug fixes from NREL as well as some additional input options. A version of PyConTurb is also included although the user is encouraged to update to the latest version from the repository. Dimitrov's method is implemented in python by Davide Conti from DTU. The outputs of ViConDAR can be used with this method in order to create constrained windfields that can be for simulations with HAWC2. The tools are available at: https://gitlab.windenergy.dtu.dk/nkdi/constrained-simulation/-/tree/master/python_scripts.
- Some functions regarding reading and writing .wnd files are created and distributed as open source by NREL. We have slightly modified some of them for our purposes and added them to this repository. Exact details can be found in the headers of the source code.
- Python(>=v3.5) has to be installed in the system. The path to the correct python.exe corresponding to the python environment including PyConTurb and its dependencies has to be explicitly stated in the InputParameters file.
- Pettas V., Costa García F., Kretschmer M., Rinker J.M., Clifton A., Cheng P.W., “A numerical framework for constraining synthetic wind fields with lidar measurements for improved load simulations”. In: AIAA Scitech 2020 Forum. American Institute of Aeronautics and Astronautics; 2020:1-6. https://doi.org/10.2514/6.2020-0993
- Rinker, J. M., “PyConTurb: an open-source constrained turbulence generator”, Journal of Physics: Conference Series, Vol. 1037, 2018, p. 062032. URL http://stacks.iop.org/1742-6596/1037/i=6/a=062032?key=crossref.e906e6eebbe4b3f8b1b8ad8e740718b1.
- NWTC Information Portal (Alpha Versions). https://www.nrel.gov/wind/nwtc/turbsim.html. Last modified 14-June-2016 ;
- Dimitrov N., Natarajan A., “Application of simulated lidar scanning patterns to constrained Gaussian turbulence fields for load validation”, 2017, Wind Energ., 20: 79– 95. https://doi.org/10.1002/we.1992 .
- Conti, D., Pettas, V., Dimitrov, N., and Peña, A.: Wind turbine load validation in wakes using wind field reconstruction techniques and nacelle lidar wind retrievals, Wind Energ. Sci., 6, 841–866, https://doi.org/10.5194/wes-6-841-2021, 2021.
- Gräfe, M., Pettas, V., and Cheng, P. W.: Wind field reconstruction using nacelle based lidar measurements for floating wind turbines, Journal of Physics: Conference Series, 2265, 042 022, https://doi.org/10.1088/1742-6596/2265/4/042022, 2022.
If you use ViConDAR for a publication, use the following citation:
Pettas V, Costa García F, Kretschmer M, Rinker JM, Clifton A, Cheng PW. A numerical framework for constraining synthetic wind fields with lidar measurements for improved load simulations. In: AIAA Scitech 2020 Forum. American Institute of Aeronautics and Astronautics; 2020:1-6. https://doi.org/10.2514/6.2020-0993
or in .bib format:
@inproceedings{Pettas2020, address = {Reston, Virginia}, author = {Pettas, Vasilis and {Costa Garc{'{i}}a}, Francisco and Kretschmer, Matthias and Rinker, Jennifer M. and Clifton, Andrew and Cheng, Po Wen}, booktitle = {AIAA Scitech 2020 Forum}, doi = {10.2514/6.2020-0993}, isbn = {978-1-62410-595-1}, month = {jan}, number = {January}, pages = {1--6}, publisher = {American Institute of Aeronautics and Astronautics}, title = {{A numerical framework for constraining synthetic wind fields with lidar measurements for improved load simulations}}, url = {https://doi.org/10.2514/6.2020-0993 }, year = {2020} }
Vasilis Pettas, University of Stuttgart, Stuttgart Wind Energy (SWE) ORCID: 0000-0001-9985-9031
Francisco Costa, University of Stuttgart, Stuttgart Wind Energy (SWE) ORCID: 0000-0003-1318-9677
Moritz Gräfe, University of Stuttgart, Stuttgart Wind Energy (SWE)