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

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

Dataset

• Renewable Energy
• Energy

free-vortex wake, wake steering, wind farm flow control, wind turbine

CC BY 4.0

RefWorks, BibTeX, Reference Manager, Endnote, DataCite, NLM, DC, CFF

by Maarten van den Broek

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"

• 2023-09-11 first online, published, posted

4TU.ResearchData

code/.jl, notebooks/.ipynb, data/.csv, configurations/.json

• Robust closed-loop wake steering for large densely space wind farms (grant code 17512) Dutch Research Council (NWO)

TU Delft, Faculty of Mechanical, Maritime and Materials Engineering, Delft Centre for Systems and Control