Simulation data and code accompanying the publication: Dynamic wind farm flow control using free-vortex wake models

doi: 10.4121/50138917-cf01-4780-9d1d-443593b7e974.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: 10.4121/50138917-cf01-4780-9d1d-443593b7e974
Datacite citation style:
van den Broek, Maarten (2023): Simulation data and code accompanying the publication: Dynamic wind farm flow control using free-vortex wake models. Version 1. 4TU.ResearchData. dataset. https://doi.org/10.4121/50138917-cf01-4780-9d1d-443593b7e974.v1
Other citation styles (APA, Harvard, MLA, Vancouver, Chicago, IEEE) available at Datacite
Dataset
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Code and simulation results for a study on wake steering in wind farms under time-varying inflow inflow conditions for maximisation of power production.


A novel model-based controller is developed based on a distributed optimisation approach with the free-vortex wake model. The model of the wind turbine wake and the controller are provided as Julia code. The associated data contains control signals and results from experiments in large-eddy simulation as presented in the associated publication.


Code and simulation data supporting the paper "Dynamic wind farm flow control using free-vortex wake models"

history
  • 2023-09-11 first online, published, posted
publisher
4TU.ResearchData
format
code/.jl, notebooks/.ipynb, data/.csv, configurations/.json
funding
  • Robust closed-loop wake steering for large densely space wind farms (grant code 17512) Dutch Research Council (NWO)
organizations
TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, Delft Centre for Systems and Control

DATA

files (1)