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Turbulence and Control of Wind Farms

Journal Article · · Annual Review of Control, Robotics, and Autonomous Systems
 [1];  [2];  [2]
  1. Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA,; AAAS Science & Technology Policy Fellow, Building Technologies Office, US Department of Energy, Washington, DC, USA
  2. Department of Mechanical Engineering, Johns Hopkins University, Baltimore, Maryland, USA,

The dynamics of the turbulent atmospheric boundary layer play a fundamental role in wind farm energy production, governing the velocity field that enters the farm as well as the turbulent mixing that regenerates energy for extraction at downstream rows. Understanding the dynamic interactions among turbines, wind farms, and the atmospheric boundary layer can therefore be beneficial in improving the efficiency of wind farm control approaches. Anticipated increases in the sizes of new wind farms to meet renewable energy targets will increase the importance of exploiting this understanding to advance wind farm control capabilities. This review discusses approaches for modeling and estimation of the wind farm flow field that have exploited such knowledge in closed-loop control, to varying degrees. We focus on power tracking as an example application that will be of critical importance as wind farms transition into their anticipated role as major suppliers of electricity. The discussion highlights the benefits of including the dynamics of the flow field in control and points to critical shortcomings of the current approaches.

Research Organization:
Oak Ridge Institute for Science and Education (ORISE), Oak Ridge, TN (United States)
Sponsoring Organization:
USDOE Office of Science (SC)
DOE Contract Number:
SC0014664
OSTI ID:
1983004
Journal Information:
Annual Review of Control, Robotics, and Autonomous Systems, Vol. 5, Issue 1; ISSN 2573-5144
Publisher:
Annual Reviews
Country of Publication:
United States
Language:
English

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Active Power Control of Waked Wind Farms * *J.W. van Wingerden would like to acknowledge the CL-Windcon project. This project has received funding from the European Union Horizon 2020 research and innovation programme under grant agreement No 727477. L. Pao gratefully acknowledges funding provided by the Hanse-Wissenschaftskolleg Institute for Advanced Study, Delmenhorst, Germany. J. Aho has been supported in part by the Renewable and Sustainable Energy Institute and a University of Colorado Boulder Graduate School Summer Fellowship. journal July 2017
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