Articles | Volume 7, issue 1
https://doi.org/10.5194/wes-7-345-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-7-345-2022
© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions
Civil and Environmental Engineering, Massachusetts Institute of Technology, Cambridge, MA 02139, USA
Aditya S. Ghate
Department of Astronautics and Aeronautics, Stanford University,
Stanford, CA 94305, USA
NASA Ames Research Center, Moffet Field, CA 94035, USA
Jesús Bas Quesada
Siemens Gamesa Renewable Energy Innovation & Technology, Sarriguren, Navarra, 31621, Spain
Juan José Pena Martínez
Siemens Gamesa Renewable Energy Innovation & Technology, Sarriguren, Navarra, 31621, Spain
Wei Zhong
Siemens Gamesa Renewable Energy Innovation & Technology, Sarriguren, Navarra, 31621, Spain
Felipe Palou Larrañaga
Siemens Gamesa Renewable Energy Innovation & Technology, Sarriguren, Navarra, 31621, Spain
Sanjiva K. Lele
Department of Astronautics and Aeronautics, Stanford University,
Stanford, CA 94305, USA
John O. Dabiri
Graduate Aerospace Laboratories (GALCIT), California Institute of Technology, Pasadena, CA 91125, USA
Department of Mechanical and Civil Engineering, California Institute of Technology, Pasadena, CA 91125, USA
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Wake losses significantly reduce the power production of utility-scale wind farms since all wind turbines are operated in a greedy, individual power maximization fashion. In order to mitigate wake losses, collective wind farm operation strategies use wake steering, in which certain turbines are intentionally misaligned with respect to the incoming wind direction. The control strategy developed is dynamic and closed-loop to adapt to changing atmospheric conditions.
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Short summary
Wake steering control, in which turbines are intentionally misaligned with the incident wind, has demonstrated potential to increase wind farm energy. We investigate wake steering control methods in simulations of a wind farm operating in the terrestrial diurnal cycle. We develop a statistical wind direction forecast to improve wake steering in flows with time-varying states. Closed-loop wake steering control increases wind farm energy production, compared to baseline and open-loop control.
Wake steering control, in which turbines are intentionally misaligned with the incident wind,...
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