Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions

Howland, Michael F.; Ghate, Aditya S.; Quesada, Jesús Bas; Pena Martínez, Juan José; Zhong, Wei; Larrañaga, Felipe Palou; Lele, Sanjiva K.; Dabiri, John O.

doi:https://doi.org/10.5194/wes-7-345-2022

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.

https://doi.org/10.5194/wes-7-345-2022

© Author(s) 2022. This work is distributed under
the Creative Commons Attribution 4.0 License.

Articles | Volume 7, issue 1

Research article

|

09 Feb 2022

Research article |

| 09 Feb 2022

Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions

Michael F. Howland, Aditya S. Ghate, Jesús Bas Quesada, Juan José Pena Martínez, Wei Zhong, Felipe Palou Larrañaga, Sanjiva K. Lele, and John O. Dabiri

Data sets

Supporting data for Optimal closed-loop wake steering, Part 2: Diurnal cycle atmospheric boundary layer conditions Michael F. Howland https://doi.org/10.5281/zenodo.5160943

Model code and software

PadeOps Aditya S. Ghate, Akshay Subramaniam, and Michael F. Howland https://github.com/FPAL-Stanford-University/PadeOps

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.