Using high-fidelity computational fluid dynamics to help design a wind turbine wake measurement experiment
Abstract
Here, we describe the process of using large-eddy simulations of wind turbine wake flow to help design a wake measurement campaign. The main goal of the experiment is to measure wakes and wake deflection that result from intentional yaw misalignment under a variety of atmospheric conditions at the Scaled Wind Farm Technology facility operated by Sandia National Laboratories in Lubbock, Texas. Prior simulation studies have shown that wake deflection may be used for wind-plant control that maximizes plant power output. In this study, simulations are performed to characterize wake deflection and general behavior before the experiment is performed to ensure better upfront planning. Beyond characterizing the expected wake behavior, we also use the large-eddy simulation to test a virtual version of the lidar we plan to use to measure the wake and better understand our lidar scan strategy options. This work is an excellent example of a 'simulation-in-the-loop' measurement campaign.
- Authors:
-
- National Renewable Energy Lab. (NREL), Golden, CO (United States)
- Sandia National Lab. (SNL-NM), Albuquerque, NM (United States)
- Technical Univ. of Denmark, Roskilde (Denmark)
- Publication Date:
- Research Org.:
- National Renewable Energy Laboratory (NREL), Golden, CO (United States)
- Sponsoring Org.:
- USDOE Office of Energy Efficiency and Renewable Energy (EERE), Wind and Water Technologies Office (EE-4W)
- OSTI Identifier:
- 1335211
- Report Number(s):
- NREL/JA-5000-66857
Journal ID: ISSN 1742-6588
- Grant/Contract Number:
- AC36-08GO28308
- Resource Type:
- Accepted Manuscript
- Journal Name:
- Journal of Physics. Conference Series
- Additional Journal Information:
- Journal Volume: 753; Journal Issue: B; Journal ID: ISSN 1742-6588
- Publisher:
- IOP Publishing
- Country of Publication:
- United States
- Language:
- English
- Subject:
- 17 WIND ENERGY; wind turbine wakes; simulation; experiment; SWiFT; lidar; scaled wind farm technology
Citation Formats
Churchfield, M., Wang, Q., Scholbrock, A., Herges, T., Mikkelsen, T., and Sjoholm, M. Using high-fidelity computational fluid dynamics to help design a wind turbine wake measurement experiment. United States: N. p., 2016.
Web. doi:10.1088/1742-6596/753/3/032009.
Churchfield, M., Wang, Q., Scholbrock, A., Herges, T., Mikkelsen, T., & Sjoholm, M. Using high-fidelity computational fluid dynamics to help design a wind turbine wake measurement experiment. United States. https://doi.org/10.1088/1742-6596/753/3/032009
Churchfield, M., Wang, Q., Scholbrock, A., Herges, T., Mikkelsen, T., and Sjoholm, M. Mon .
"Using high-fidelity computational fluid dynamics to help design a wind turbine wake measurement experiment". United States. https://doi.org/10.1088/1742-6596/753/3/032009. https://www.osti.gov/servlets/purl/1335211.
@article{osti_1335211,
title = {Using high-fidelity computational fluid dynamics to help design a wind turbine wake measurement experiment},
author = {Churchfield, M. and Wang, Q. and Scholbrock, A. and Herges, T. and Mikkelsen, T. and Sjoholm, M.},
abstractNote = {Here, we describe the process of using large-eddy simulations of wind turbine wake flow to help design a wake measurement campaign. The main goal of the experiment is to measure wakes and wake deflection that result from intentional yaw misalignment under a variety of atmospheric conditions at the Scaled Wind Farm Technology facility operated by Sandia National Laboratories in Lubbock, Texas. Prior simulation studies have shown that wake deflection may be used for wind-plant control that maximizes plant power output. In this study, simulations are performed to characterize wake deflection and general behavior before the experiment is performed to ensure better upfront planning. Beyond characterizing the expected wake behavior, we also use the large-eddy simulation to test a virtual version of the lidar we plan to use to measure the wake and better understand our lidar scan strategy options. This work is an excellent example of a 'simulation-in-the-loop' measurement campaign.},
doi = {10.1088/1742-6596/753/3/032009},
journal = {Journal of Physics. Conference Series},
number = B,
volume = 753,
place = {United States},
year = {Mon Oct 03 00:00:00 EDT 2016},
month = {Mon Oct 03 00:00:00 EDT 2016}
}
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Works referenced in this record:
Evaluating techniques for redirecting turbine wakes using SOWFA
journal, October 2014
- Fleming, Paul A.; Gebraad, Pieter M. O.; Lee, Sang
- Renewable Energy, Vol. 70
Simulation comparison of wake mitigation control strategies for a two-turbine case: Simulation comparison of wake mitigation control strategies for a two-turbine case
journal, October 2014
- Fleming, Paul; Gebraad, Pieter M. O.; Lee, Sang
- Wind Energy, Vol. 18, Issue 12
A spinner-integrated wind lidar for enhanced wind turbine control: Spinner-integrated wind lidar for enhanced steering and control
journal, October 2012
- Mikkelsen, T.; Angelou, N.; Hansen, K.
- Wind Energy, Vol. 16, Issue 4
A numerical study of the effects of atmospheric and wake turbulence on wind turbine dynamics
journal, January 2012
- Churchfield, Matthew J.; Lee, Sang; Michalakes, John
- Journal of Turbulence, Vol. 13
An experimental and numerical study of the atmospheric stability impact on wind turbine wakes: Experimental and numerical study of the atmospheric stability impact on wake
journal, December 2015
- Machefaux, Ewan; Larsen, Gunner C.; Koblitz, Tilman
- Wind Energy, Vol. 19, Issue 10
Application of a LES technique to characterize the wake deflection of a wind turbine in yaw
journal, December 2009
- Jiménez, Ángel; Crespo, Antonio; Migoya, Emilio
- Wind Energy, Vol. 13, Issue 6
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
Works referencing / citing this record:
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journal, January 2019
- Kirby, Andrew C.; Brazell, Michael J.; Yang, Zhi
- The International Journal of High Performance Computing Applications, Vol. 33, Issue 5
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journal, March 2017
- Breton, S. -P.; Sumner, J.; Sørensen, J. N.
- Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, Vol. 375, Issue 2091
Wind-Turbine and Wind-Farm Flows: A Review
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- Porté-Agel, Fernando; Bastankhah, Majid; Shamsoddin, Sina
- Boundary-Layer Meteorology, Vol. 174, Issue 1
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- Clifton, Andrew; Clive, Peter; Gottschall, Julia
- Remote Sensing, Vol. 10, Issue 3
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- Bastankhah, Majid; Porté-Agel, Fernando
- Journal of Renewable and Sustainable Energy, Vol. 11, Issue 2
High resolution wind turbine wake measurements with a scanning lidar
journal, May 2017
- Herges, T. G.; Maniaci, D. C.; Naughton, B. T.
- Journal of Physics: Conference Series, Vol. 854
Why the Coriolis force turns a wind farm wake clockwise in the Northern Hemisphere
journal, January 2017
- van der Laan, Maarten Paul; Sørensen, Niels Nørmark
- Wind Energy Science, Vol. 2, Issue 1
IEA Wind Task 32: Wind Lidar : identifying and mitigating barriers to the adoption of wind lidar
collection, January 2018
- Clifton, Andrew; Clive, Peter; Gottschall, Julia
- Universität Stuttgart
Wind Farm Simulations Using an Overset hp-Adaptive Approach with Blade-Resolved Turbine Models
conference, June 2017
- Kirby, Andrew C.; Brazell, Michael; Yang, Zhi
- 23rd AIAA Computational Fluid Dynamics Conference
Why the Coriolis force turns a wind farm wake clockwise in the Northern Hemisphere
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- van der Laan, Maarten Paul; Sørensen, Niels Nørmark
- Wind Energy Science Discussions