A dynamic wind farm simulation software, translated from FLORIDyn_Matlab [1], which was written by Marcus Becker. The code uses the Gaussian wake model derived in [3].
- Simulate wind farms dynamically at a low computational cost
- Estimate the power generated, added turbulence, and wake-induced losses.
- Apply heterogeneous and time-varying wind speeds and directions
- Test different modeling approaches
All examples work, most key examples are selectable via a menu:
include("examples/menu.jl")The other examples can be executed directly using the include statement. Often, more than 30x the performance of the Matlab version can be achieved. Currently, only IterateOPs_basic is implemented.
A Python version of FLORIDyn is available at https://github.com/TUDelft-DataDrivenControl/OFF .
Install Julia 1.11, if you haven't already. Julia 1.10 is still supported. On Linux, make sure that Python3 and Matplotlib are installed:
sudo apt install python3-matplotlib
Make sure that ControlPlots.jl works as explained here.
Before installing this software it is suggested to create a new project, for example like this:
mkdir test
cd test
julia --project=.Don't forget to type the dot at the end of the last command.
Then add FLORIDyn from Julia's package manager, by typing:
using Pkg
pkg"add FLORIDyn"at the Julia prompt. You can run the unit tests with the command:
pkg"test FLORIDyn"You can install the examples using the following command:
using FLORIDyn
install_examples()If you now quit Julia with and restart it with
./bin/run_juliathen you can get the example menu by typing:
menu()You can select any of the examples with the <UP> and <DOWN> keys, and then press <ENTER>.
For developers, follow the developer notes.
The documentation is available here.
This project is licensed under the BSD-3-Clause. The documentation is licensed under the CC-BY-4.0 License. Please see the below Copyright notice in association with the licenses that can be found in the file LICENSE in this folder.
Technische Universiteit Delft hereby disclaims all copyright interest in the package “FLORIDyn.jl” (dynamic wind farm simulation) written by the Author(s).
Prof.dr. H.G.C. (Henri) Werij, Dean of Aerospace Engineering, Technische Universiteit Delft.
See the copyright notices in the source files, and the list of authors in AUTHORS.md.
This research has been partly funded by Rijksdienst voor Ondernemend (RVO) Nederland under contract HEP24-03681024 through the EuroWindWakes project which is a Horizon Europe Partnership.
Citation of the FLORIDyn model:
[1] FLORIDyn - A dynamic and flexible framework for real-time wind farm control, M. Becker, D. Allaerts, J.W. van Wingerden, 2022, DOI 10.1088/1742-6596/2265/3/032103
Used FLORIS model:
[2] Experimental and theoretical study of wind turbine wakes in yawed conditions, M. Bastankhah, F. Porté-Agel, 2020, DOI 10.1017/jfm.2016.595
Gaussian wake model:
[3] Experimental and theoretical study of wind turbine wakes in yawed conditions, M. Bastankhah, F. Porté-Agel, 2016, Journal of Fluid Mechanics 806:506-541. DOI 10.1017/jfm.2016.595
Additional references for smaller subcomponents can be found in the code or in the related publications.
- Ensemble-Based Flow Field Estimation Using the Dynamic Wind Farm Model FLORIDyn, M. Becker, D. Allaerts, J.W. van Wingerden, 2022, DOI 10.3390/en15228589
- Wind pattern clustering of high frequent field measurements for dynamic wind farm flow control, M. Becker, D. Allaerts, J.W. van Wingerden, 2024, http://doi.org/10.1088/1742-6596/2767/3/032028
- Sensitivity analysis and Bayesian calibration of a dynamic wind farm control model: FLORIDyn, V.V. Dighe, M. Becker, wf. Göçmen, B. Sanderse, J.W. van Wingerden, 2022, http://doi.org/10.1088/1742-6596/2265/2/022062
- Time-shifted cost function design for more efficient dynamic wind farm flow control, M. Becker, D. Allaerts, J.W. van Wingerden, 2024, http://doi.org/10.1109/CCTA60707.2024.10666535
- Suitability of Dynamic Wake Models for AEP Estimation: A Wind Farm-Scale Validation Study, M. Van der Straeten, http://resolver.tudelft.nl/uuid:f35617a2-2409-439b-8bc2-6334b807ce1f
- Scaling DMD modes for modeling Dynamic Induction Control wakes in various wind speeds, J. Gutknecht, M. Becker, C. Muscari, wf. Lutz, J.W. van Wingerden, 2023, http://doi.org/10.1109/CCTA54093.2023.10252400
- Model predictive control of wakes for wind farm power tracking, A. Sterle, C.A. Hans, J. Raisch, 2024, http://doi.org/10.1088/1742-6596/2767/3/032005