Articles | Volume 7, issue 5
https://doi.org/10.5194/wes-7-1791-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-7-1791-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
08 Sep 2022
Research article |
| 08 Sep 2022
| 08 Sep 2022
FarmConners wind farm flow control benchmark – Part 1: Blind test results
DTU Wind and Energy Systems, Technical University of Denmark, Lyngby/Roskilde, Denmark
Filippo Campagnolo
Wind Energy Institute, Technische Universität München, 85748 Garching b. München, Germany
Thomas Duc
ENGIE Green, 6 rue Alexander Fleming, 69007 Lyon, France
Irene Eguinoa
Wind Energy Department, CENER, Sarriguren, Spain
Søren Juhl Andersen
DTU Wind and Energy Systems, Technical University of Denmark, Lyngby/Roskilde, Denmark
Vlaho Petrović
ForWind, Institute of Physics, University of Oldenburg, Küpkersweg 70, 26129 Oldenburg, Germany
Lejla Imširović
Wind Energy Institute, Technische Universität München, 85748 Garching b. München, Germany
Robert Braunbehrens
Wind Energy Institute, Technische Universität München, 85748 Garching b. München, Germany
Jaime Liew
DTU Wind and Energy Systems, Technical University of Denmark, Lyngby/Roskilde, Denmark
Mads Baungaard
DTU Wind and Energy Systems, Technical University of Denmark, Lyngby/Roskilde, Denmark
Maarten Paul van der Laan
DTU Wind and Energy Systems, Technical University of Denmark, Lyngby/Roskilde, Denmark
Guowei Qian
Department of Civil Engineering, School of Engineering, The University of Tokyo, 7-3-1, Hongo, Bunkyo-ku, Tokyo, Japan
Maria Aparicio-Sanchez
Wind Energy Department, CENER, Sarriguren, Spain
Rubén González-Lope
Wind Energy Department, CENER, Sarriguren, Spain
Vinit V. Dighe
Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
Marcus Becker
Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
Maarten J. van den Broek
Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
Jan-Willem van Wingerden
Delft Center for Systems and Control, Delft University of Technology, Delft, the Netherlands
Adam Stock
Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, The University of Strathclyde, Glasgow, UK
Matthew Cole
Wind Energy and Control Centre, Department of Electronic and Electrical Engineering, The University of Strathclyde, Glasgow, UK
Renzo Ruisi
DNV, Group Research & Development, Bristol, United Kingdom
Ervin Bossanyi
DNV, Group Research & Development, Bristol, United Kingdom
Niklas Requate
Fraunhofer IWES, Bremerhaven, Germany
Simon Strnad
Fraunhofer IWES, Bremerhaven, Germany
Jonas Schmidt
Fraunhofer IWES, Bremerhaven, Germany
Lukas Vollmer
Fraunhofer IWES, Bremerhaven, Germany
Ishaan Sood
Mechanical Engineering, KU Leuven, Celestijnenlaan 300, Leuven 3001, Belgium
Johan Meyers
Mechanical Engineering, KU Leuven, Celestijnenlaan 300, Leuven 3001, Belgium
Model code and software
FarmConners Wind Farm Control Benchmark Repository Tuhfe Göçmen, Konstanze Kölle, Vlaho Petrovic, Pawel Gancarski https://doi.org/10.5281/zenodo.5786988
Short summary
The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control settings, and model complexities for the (initial) assessment of wind farm flow control benefits. Here we present the first part of the benchmark results for three blind tests with large-scale rotors and 11 participating models in total, via direct power comparisons at the turbines as well as the observed or estimated power gain at the wind farm level under wake steering control strategy.
The FarmConners benchmark is the first of its kind to bring a wide variety of data sets, control...
Altmetrics
Final-revised paper
Preprint