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Title: Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results

Abstract

Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this study, the turbine was operated at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.

Authors:
 [1]; ORCiD logo [1];  [1];  [1]; ORCiD logo [1];  [1];  [2];  [3];  [3];  [3]
  1. National Renewable Energy Lab. (NREL), Golden, CO (United States). National Wind Technology Center
  2. Swiss Federal Inst. of Technology in Lausanne (Switzerland)
  3. Univ. of Stuttgart (Germany). Stuttgart Wind Energy (SWE)
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:
1433602
Report Number(s):
NREL/JA-5000-70692
Journal ID: ISSN 2366-7621
Grant/Contract Number:  
AC36-08GO28308
Resource Type:
Journal Article: Accepted Manuscript
Journal Name:
Wind Energy Science Discussions
Additional Journal Information:
Journal Name: Wind Energy Science Discussions; Journal ID: ISSN 2366-7621
Publisher:
European Academy of Wind Energy - Copernicus
Country of Publication:
United States
Language:
English
Subject:
17 WIND ENERGY; 47 OTHER INSTRUMENTATION; wind energy; wind farm controls; lidar; control systems; wakes

Citation Formats

Annoni, Jennifer, Fleming, Paul, Scholbrock, Andrew, Roadman, Jason, Dana, Scott, Adcock, Christiane, Porte-Agel, Fernando, Raach, Steffen, Haizmann, Florian, and Schlipf, David. Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results. United States: N. p., 2018. Web. doi:10.5194/wes-2018-6.
Annoni, Jennifer, Fleming, Paul, Scholbrock, Andrew, Roadman, Jason, Dana, Scott, Adcock, Christiane, Porte-Agel, Fernando, Raach, Steffen, Haizmann, Florian, & Schlipf, David. Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results. United States. doi:10.5194/wes-2018-6.
Annoni, Jennifer, Fleming, Paul, Scholbrock, Andrew, Roadman, Jason, Dana, Scott, Adcock, Christiane, Porte-Agel, Fernando, Raach, Steffen, Haizmann, Florian, and Schlipf, David. Thu . "Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results". United States. doi:10.5194/wes-2018-6. https://www.osti.gov/servlets/purl/1433602.
@article{osti_1433602,
title = {Analysis of Control-Oriented Wake Modeling Tools Using Lidar Field Results},
author = {Annoni, Jennifer and Fleming, Paul and Scholbrock, Andrew and Roadman, Jason and Dana, Scott and Adcock, Christiane and Porte-Agel, Fernando and Raach, Steffen and Haizmann, Florian and Schlipf, David},
abstractNote = {Wind turbines in a wind farm operate individually to maximize their own performance regardless of the impact of aerodynamic interactions on neighboring turbines. Wind farm controls can be used to increase power production or reduce overall structural loads by properly coordinating turbines. One wind farm control strategy that is addressed in literature is known as wake steering, wherein upstream turbines operate in yaw misaligned conditions to redirect their wakes away from downstream turbines. The National Renewable Energy Laboratory (NREL) in Golden, CO conducted a demonstration of wake steering on a single utility-scale turbine. In this study, the turbine was operated at various yaw misalignment setpoints while a lidar mounted on the nacelle scanned five downstream distances. The lidar measurements were combined with turbine data, as well as measurements of the inflow made by a highly instrumented meteorological mast upstream. The full-scale measurements are used to validate controls-oriented tools, including wind turbine wake models, used for wind farm controls and optimization. This paper presents a quantitative comparison of the lidar data and controls-oriented wake models under different atmospheric conditions and turbine operation. The results show good agreement between the lidar data and the models under these different conditions.},
doi = {10.5194/wes-2018-6},
journal = {Wind Energy Science Discussions},
number = ,
volume = ,
place = {United States},
year = {Thu Feb 08 00:00:00 EST 2018},
month = {Thu Feb 08 00:00:00 EST 2018}
}

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