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Title: Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution

Abstract

Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.

Authors:
ORCiD logo [1]; ORCiD logo [1]; ORCiD logo [1]
  1. National Renewable Energy Laboratory (NREL), Golden, CO (United States)
Publication Date:
Research Org.:
National Renewable Energy Lab. (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:
1603920
Report Number(s):
[NREL/JA-5000-74643]
Grant/Contract Number:  
[AC36-08GO28308]
Resource Type:
Accepted Manuscript
Journal Name:
Journal of Physics: Conference Series
Additional Journal Information:
[ Journal Volume: 1452]
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; wind power plants; rotor wake; wake dynamics; wake evolution

Citation Formats

Quon, Eliot W, Doubrawa Moreira, Paula, and Debnath, Mithu C. Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution. United States: N. p., 2020. Web. doi:10.1088/1742-6596/1452/1/012070.
Quon, Eliot W, Doubrawa Moreira, Paula, & Debnath, Mithu C. Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution. United States. doi:10.1088/1742-6596/1452/1/012070.
Quon, Eliot W, Doubrawa Moreira, Paula, and Debnath, Mithu C. Tue . "Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution". United States. doi:10.1088/1742-6596/1452/1/012070.
@article{osti_1603920,
title = {Comparison of Rotor Wake Identification and Characterization Methods for the Analysis of Wake Dynamics and Evolution},
author = {Quon, Eliot W and Doubrawa Moreira, Paula and Debnath, Mithu C},
abstractNote = {Optimal wind power plant design requires understanding of wind turbine wake physics and validation of engineering wake models under wake-controlled operating conditions. In this work, we have developed and investigated several different wake identification and characterization methods for analyzing wake evolution and dynamics. The accuracy and robustness of these methods, based on Gaussian function fitting and adaptive contour identification, have been assessed by application to a large-eddy simulation data set. A new contour-based method based on downstream momentum deficit has been considered. Uncertainties arising from wake-identification errors result in characterizations of the wake expansion, recovery, and meandering motion that differ by 19% of the rotor area, 4% of the freestream, and 15% rotor diameter, respectively.},
doi = {10.1088/1742-6596/1452/1/012070},
journal = {Journal of Physics: Conference Series},
number = ,
volume = [1452],
place = {United States},
year = {2020},
month = {3}
}

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Works referenced in this record:

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
  • DOI: 10.1175/JTECH-D-13-00104.1

Does median filtering truly preserve edges better than linear filtering?
journal, June 2009

  • Arias-Castro, Ery; Donoho, David L.
  • The Annals of Statistics, Vol. 37, Issue 3
  • DOI: 10.1214/08-AOS604

A new analytical model for wind-turbine wakes
journal, October 2014


Towards a Simplified DynamicWake Model Using POD Analysis
journal, January 2015

  • Bastine, David; Witha, Björn; Wächter, Matthias
  • Energies, Vol. 8, Issue 2
  • DOI: 10.3390/en8020895

Using High-Fidelity Computational Fluid Dynamics to Help Design a Wind Turbine Wake Measurement Experiment
journal, September 2016


Benchmarks for Model Validation based on LiDAR Wake Measurements
journal, July 2019


Wind Turbine Wake Characterization from Temporally Disjunct 3-D Measurements
journal, November 2016

  • Doubrawa, Paula; Barthelmie, Rebecca; Wang, Hui
  • Remote Sensing, Vol. 8, Issue 11
  • DOI: 10.3390/rs8110939

Spatial study of the wake meandering using modelled wind turbines in a wind tunnel
journal, October 2011

  • España, G.; Aubrun, S.; Loyer, S.
  • Wind Energy, Vol. 14, Issue 7, p. 923-937
  • DOI: 10.1002/we.515

Evaluating techniques for redirecting turbine wakes using SOWFA
journal, October 2014


High resolution wind turbine wake measurements with a scanning lidar
journal, May 2017


Wake structure in actuator disk models of wind turbines in yaw under uniform inflow conditions
journal, July 2016

  • Howland, Michael F.; Bossuyt, Juliaan; Martínez-Tossas, Luis A.
  • Journal of Renewable and Sustainable Energy, Vol. 8, Issue 4
  • DOI: 10.1063/1.4955091

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
  • DOI: 10.1002/we.380

On atmospheric stability in the dynamic wake meandering model: On atmospheric stability in the dynamic wake meandering model
journal, September 2013

  • Keck, Rolf-Erik; de Maré, Martin; Churchfield, Matthew J.
  • Wind Energy, Vol. 17, Issue 11
  • DOI: 10.1002/we.1662

Estimating the wake deflection downstream of a wind turbine in different atmospheric stabilities: an LES study
journal, January 2016

  • Vollmer, Lukas; Steinfeld, Gerald; Heinemann, Detlev
  • Wind Energy Science, Vol. 1, Issue 2
  • DOI: 10.5194/wes-1-129-2016

Wake behavior and control: comparison of LES simulations and wind tunnel measurements
journal, January 2019

  • Wang, Jiangang; Wang, Chengyu; Campagnolo, Filippo
  • Wind Energy Science, Vol. 4, Issue 1
  • DOI: 10.5194/wes-4-71-2019