Preprints
https://doi.org/10.5194/wes-2021-116
https://doi.org/10.5194/wes-2021-116

  26 Oct 2021

26 Oct 2021

Review status: this preprint is currently under review for the journal WES.

FLOWERS: An integral approach to engineering wake models

Michael LoCascio1,2, Christopher Bay1, Majid Bastankhah3, Garrett Barter1, Paul Fleming1, and Luis Martínez-Tossas1 Michael LoCascio et al.
  • 1National Wind Technology Center, National Renewable Energy Laboratory, Golden, CO 80401, USA
  • 2Civil and Environmental Engineering, Stanford University, Stanford, CA 94305, USA
  • 3Department of Engineering, Durham University, Durham DH1 3LE, UK

Abstract. Annual energy production (AEP) is often the objective function in wind plant layout optimization studies. The conventional method to compute AEP for a wind farm is to first evaluate power production for each wind direction and speed using either computational fluid dynamics simulations or engineering wake models. The AEP is then calculated by weighted-averaging (based on the wind rose at the wind farm site) the power produced across all wind directions. We propose a novel formulation for time-averaged wake velocity that incorporates an analytical integral of a wake deficit model across every wind direction. This approach computes the average flow field more efficiently, and layout optimization is an obvious application to exploit this benefit. The clear advantage of this new approach is that the layout optimization produces solutions with comparable AEP performance yet is completed about 700 times faster. The analytical integral and the use of a Fourier expansion to express the wind speed and wind direction frequency create a more smooth solution space for the gradient-based optimizer to excel compared with the discrete nature of the existing weighted-averaging power calculation.

Michael LoCascio et al.

Status: open (until 11 Dec 2021)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • CC1: 'Comment on wes-2021-116', Mads Pedersen, 28 Oct 2021 reply
  • RC1: 'Comment on wes-2021-116', Anonymous Referee #1, 26 Nov 2021 reply

Michael LoCascio et al.

Michael LoCascio et al.

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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.