Modelling and assessing the near-wake representation and turbulence behaviour of control-oriented wake models
Abstract
Due to the interaction between the wake of an upstream turbine on a downstream turbine, power losses and increased fatigue loads occur. By yawing the upstream turbine with regard to the wind direction, one can potentially reduce the power losses of the downstream turbine and reduce the fatigue loads. The evolution of the wake depends on the pressure gradient within the near-wake region and the turbulent kinetic energy and must be incorporated in existing wake steering algorithms to provide an accurate estimation of the wake flow. This paper will show a first approach to implement a near-wake model and a turbulence model in the curled wake model within the controls-oriented framework FLORIS. The near-wake model is based on an analytical expression of the velocity profile to model the pressure gradient. Furthermore, two turbulence models are incorporated within the curled wake model based on a Gaussian-distribution and a mixing length formulation. The adapted curled wake model is then assessed with the measurement data acquired in the wind tunnel at ForWind – University of Oldenburg. The evaluation of the models show good agreement for the velocity deficit and representation of the near-wake region. Furthermore, the turbulent kinetic energy behaved as expected inmore »
- Authors:
-
[2];
[2];
- Univ. of Oldenburg (Germany). ForWind, Inst. of Physics
- National Renewable Energy Lab. (NREL), Golden, CO (United States). National Wind Technology Center
- Publication Date:
- Research Org.:
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE); German Federal Ministry for Economic Affairs and Energy
- OSTI Identifier:
- 1677438
- Report Number(s):
- NREL/JA-5000-78006
Journal ID: ISSN 1742-6588; MainId:31915;UUID:c94adaf6-1781-4e2b-8fd4-cf1a05d628d1;MainAdminID:18626
- Grant/Contract Number:
- AC36-08GO28308; 0325492H
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physics. Conference Series
- Additional Journal Information:
- Journal Volume: 1618; Journal ID: ISSN 1742-6588
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- WIND ENERGY; FLORIS; near-wake model; turbulence; wind turbines
Citation Formats
Hulsman, Paul, Martínez-Tossas, Luis A., Hamilton, Nicholas, and Kühn, Martin. Modelling and assessing the near-wake representation and turbulence behaviour of control-oriented wake models. United States: N. p., 2020.
Web. doi:10.1088/1742-6596/1618/2/022056.
Hulsman, Paul, Martínez-Tossas, Luis A., Hamilton, Nicholas, & Kühn, Martin. Modelling and assessing the near-wake representation and turbulence behaviour of control-oriented wake models. United States. https://doi.org/10.1088/1742-6596/1618/2/022056
Hulsman, Paul, Martínez-Tossas, Luis A., Hamilton, Nicholas, and Kühn, Martin. Tue .
"Modelling and assessing the near-wake representation and turbulence behaviour of control-oriented wake models". United States. https://doi.org/10.1088/1742-6596/1618/2/022056. https://www.osti.gov/servlets/purl/1677438.
@article{osti_1677438,
title = {Modelling and assessing the near-wake representation and turbulence behaviour of control-oriented wake models},
author = {Hulsman, Paul and Martínez-Tossas, Luis A. and Hamilton, Nicholas and Kühn, Martin},
abstractNote = {Due to the interaction between the wake of an upstream turbine on a downstream turbine, power losses and increased fatigue loads occur. By yawing the upstream turbine with regard to the wind direction, one can potentially reduce the power losses of the downstream turbine and reduce the fatigue loads. The evolution of the wake depends on the pressure gradient within the near-wake region and the turbulent kinetic energy and must be incorporated in existing wake steering algorithms to provide an accurate estimation of the wake flow. This paper will show a first approach to implement a near-wake model and a turbulence model in the curled wake model within the controls-oriented framework FLORIS. The near-wake model is based on an analytical expression of the velocity profile to model the pressure gradient. Furthermore, two turbulence models are incorporated within the curled wake model based on a Gaussian-distribution and a mixing length formulation. The adapted curled wake model is then assessed with the measurement data acquired in the wind tunnel at ForWind – University of Oldenburg. The evaluation of the models show good agreement for the velocity deficit and representation of the near-wake region. Furthermore, the turbulent kinetic energy behaved as expected in comparison to other work, showing a ring of high turbulent kinetic energy at non-yawed condition which is deflected to a curled shape at large yaw angles with the turbulence model based on a mixing length formulation.},
doi = {10.1088/1742-6596/1618/2/022056},
journal = {Journal of Physics. Conference Series},
number = ,
volume = 1618,
place = {United States},
year = {Tue Sep 22 00:00:00 EDT 2020},
month = {Tue Sep 22 00:00:00 EDT 2020}
}
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Figure 1: Comparison of the streamwise velocity component at the rotor center for each downstream distance acquired with the original curled wake model, the adapted curled wake model with the turbulence models and the hot-wire measurements . The shaded area indicates ±$σ$ of the hot-wire measurements
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Works referenced in this record:
Initial results from a field campaign of wake steering applied at a commercial wind farm – Part 1
journal, January 2019
- Fleming, Paul; King, Jennifer; Dykes, Katherine
- Wind Energy Science, Vol. 4, Issue 2
Wind farm power optimization through wake steering
journal, July 2019
- Howland, Michael F.; Lele, Sanjiva K.; Dabiri, John O.
- Proceedings of the National Academy of Sciences, Vol. 116, Issue 29
Large-eddy simulations of the Lillgrund wind farm: LES of the Lillgrund wind farm
journal, February 2014
- Nilsson, Karl; Ivanell, Stefan; Hansen, Kurt S.
- Wind Energy, Vol. 18, Issue 3
Analytical modelling of wind speed deficit in large offshore wind farms
journal, January 2006
- Frandsen, Sten; Barthelmie, Rebecca; Pryor, Sara
- Wind Energy, Vol. 9, Issue 1-2
A new analytical model for wind-turbine wakes
journal, October 2014
- Bastankhah, Majid; Porté-Agel, Fernando
- Renewable Energy, Vol. 70
Experimental validation of the UPM computer code to calculate wind turbine wakes and comparison with other models
journal, January 1988
- Crespo, A.; Hernandez, J.; Fraga, E.
- Journal of Wind Engineering and Industrial Aerodynamics, Vol. 27, Issue 1-3
Wind turbine wake aerodynamics
journal, August 2003
- Vermeer, L. J.; Sørensen, J. N.; Crespo, A.
- Progress in Aerospace Sciences, Vol. 39, Issue 6-7, p. 467-510
Quantifying Wind Turbine Wake Characteristics from Scanning Remote Sensor Data
journal, April 2014
- Aitken, Matthew L.; Banta, Robert M.; Pichugina, Yelena L.
- Journal of Atmospheric and Oceanic Technology, Vol. 31, Issue 4
Calculating the flowfield in the wake of wind turbines
journal, January 1988
- Ainslie, J. F.
- Journal of Wind Engineering and Industrial Aerodynamics, Vol. 27, Issue 1-3
Near-wake behaviour of wind turbines
journal, March 1999
- Magnusson, M.
- Journal of Wind Engineering and Industrial Aerodynamics, Vol. 80, Issue 1-2
Wind tunnel experiments on wind turbine wakes in yaw: redefining the wake width
journal, January 2018
- Schottler, Jannik; Bartl, Jan; Mühle, Franz
- Wind Energy Science, Vol. 3, Issue 1
Analysis of control-oriented wake modeling tools using lidar field results
journal, January 2018
- Annoni, Jennifer; Fleming, Paul; Scholbrock, Andrew
- Wind Energy Science, Vol. 3, Issue 2
A new Gaussian-based analytical wake model for wind turbines considering ambient turbulence intensities and thrust coefficient effects
journal, June 2018
- Ishihara, Takeshi; Qian, Guo-Wei
- Journal of Wind Engineering and Industrial Aerodynamics, Vol. 177
Anisotropy of the Reynolds stress tensor in the wakes of wind turbine arrays in Cartesian arrangements with counter-rotating rotors
journal, January 2015
- Hamilton, Nicholas; Cal, Raúl Bayoán
- Physics of Fluids, Vol. 27, Issue 1
Anisotropic character of low-order turbulent flow descriptions through the proper orthogonal decomposition
journal, January 2017
- Hamilton, Nicholas; Tutkun, Murat; Cal, Raúl Bayoán
- Physical Review Fluids, Vol. 2, Issue 1
Development of coherent motion in the wake of a model wind turbine
journal, August 2017
- Eriksen, Pål Egil; Krogstad, Per-Åge
- Renewable Energy, Vol. 108
Figures / Tables found in this record:
Figures/Tables have been extracted from DOE-funded journal article accepted manuscripts.