FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models

LoCascio, Michael J.; Bay, Christopher J.; Bastankhah, Majid; Barter, Garrett E.; Fleming, Paul A.; Martínez-Tossas, Luis A.

doi:https://doi.org/10.5194/wes-7-1137-2022

Articles | Volume 7, issue 3

https://doi.org/10.5194/wes-7-1137-2022

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

https://doi.org/10.5194/wes-7-1137-2022

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

Articles | Volume 7, issue 3

Research article

|

01 Jun 2022

Research article |

| 01 Jun 2022

FLOW Estimation and Rose Superposition (FLOWERS): an integral approach to engineering wake models

Michael J. LoCascio, Christopher J. Bay, Majid Bastankhah, Garrett E. Barter, Paul A. Fleming, and Luis A. Martínez-Tossas

Model code and software

DTUWindEnergy/PyWake: PyWake M. M. Pedersen, P. van der Laan, M. Friis-Møller, J. Rinker, and P.-E. Réthoré https://doi.org/10.5281/zenodo.2562662

Short summary

This work introduces the FLOW Estimation and Rose Superposition (FLOWERS) wind turbine wake model. This model analytically integrates the wake over wind directions to provide a time-averaged flow field. This new formulation is used to perform layout optimization. The FLOWERS model provides a smooth flow field over an entire wind plant at fraction of the computational cost of the standard numerical integration approach.