OFF framework, code underlying the publication A dynamic open-source model to investigate wake dynamics in response to wind farm flow control strategies

doi:10.4121/331f86fe-5acb-4a60-99cd-7f8f0135c200.v1
The doi above is for this specific version of this dataset, which is currently the latest. Newer versions may be published in the future. For a link that will always point to the latest version, please use
doi: 10.4121/331f86fe-5acb-4a60-99cd-7f8f0135c200
Datacite citation style:
Becker, Marcus; Lejeune, Maxime (2024): OFF framework, code underlying the publication A dynamic open-source model to investigate wake dynamics in response to wind farm flow control strategies. Version 1. 4TU.ResearchData. software. https://doi.org/10.4121/331f86fe-5acb-4a60-99cd-7f8f0135c200.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Software

The OFF toolbox provides one interface to dynamic parametric wake modeling. The goal is to enable testing of different approaches, comparisons using the same interface, and an environment to develop new techniques.


The OFF toolbox was used to predict the power and energy generated by a wind farm during ~24 hours of wind direction changes, parts of which were validated with LES. The findings can be found in the publication "A dynamic open-source model to investigate wake dynamics in response to wind farm flow control strategies", Marcus Becker, Maxime Lejeune, Philipe Chatelain, Dries Allaerts, Rafael Mudafort, and Jan-Willem van Wingerden, Wind Energy Science, 2024 (submitted).


The input files, as well as the results from the LES and FLORIS can be found in the data repository with the DOI 10.4121/29c209fa-f2a4-456d-9353-67cf81be1aaa


The code used in this repository is designed to work together with NREL's FLORIS toolbox and was tested with FLORIS v4.0.1:

https://github.com/NREL/floris/releases/tag/v4.0.1




history
  • 2024-11-07 first online, published, posted
publisher
4TU.ResearchData
funding
  • Robust closed-loop wake steering for large densely spaced wind farms (grant code 17512) Nederlandse Organisatie voor Wetenschappelijk Onderzoek
organizations
TU Delft, Faculty of Mechanical Engineering, Delft Center for Systems and Control

DATA

To access the source code, use the following command:

git clone https://data.4tu.nl/v3/datasets/edbd184d-dd9f-4d14-a569-d4487c48772b.git "OFF"

Or download the latest commit as a ZIP.