08 Mar 2022
08 Mar 2022
Status: this preprint is currently under review for the journal WES.

Gradient-Based Wind Farm Layout Optimization Results Compared with Large-Eddy Simulations

Jared J. Thomas1, Christopher J. Bay2, Andrew P. J. Stanley2, and Andrew Ning1 Jared J. Thomas et al.
  • 1Brigham Young University, Provo, UT 84602
  • 2National Renewable Energy Laboratory, Golden, CO, 80401

Abstract. The physics models commonly used during wind farm layout optimization include simplifying assumptions that can alter the design space compared to reality and higher-fidelity simulations. Some characteristics of these simple models may negatively influence the resulting layouts. In this paper, we perform wind farm layout optimization using a simple engineering wake model and then simulate the base and optimized layouts using large-eddy simulation (LES) to confirm that the layout was actually improved and not just an artifact of the simplifying assumptions in the low-fidelity wind farm simulation. We begin by describing the physics models used, including changes specific for use with gradient-based optimization. We then compare the simple model's output to previously published model and LES results. Using the simple models described, we performed gradient-based wind farm layout optimization using exact gradients. We optimized the wind farm twice, with high- and low-turbulence intensity (TI), respectively. We then recalculated annual energy production (AEP) using LES for the original and optimized layouts in each TI scenario and compared the results. For the high-TI case, the simple model predicted an AEP improvement of 7.7 %, while the LES reported 9.3 %. For the low-TI case, the simple model predicted a 10.0 % AEP improvement, while the LES reported 10.7 %. We concluded that the improvements found by optimizing with the simple model are not just an artifact of the model, but are real improvements assuming appropriate wind rose fidelity. We also found that the optimization did take advantage of the number of wind directions used, often aligning wind turbines in directions that were not included in the simulation. We found that, for the case studied, at least 50 wind directions are needed to avoid having the number of wind directions in the optimization significantly impact the optimized results. Future work should investigate further LES comparisons and wind rose fidelity in wind speed.

Jared J. Thomas et al.

Status: final response (author comments only)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2022-4', Anonymous Referee #1, 10 May 2022
    • AC1: 'Reply on RC1', Jared Thomas, 10 Jun 2022
      • AC2: 'Reply on AC1', Jared Thomas, 10 Jun 2022
  • RC2: 'Comment on wes-2022-4', Anonymous Referee #2, 16 Jun 2022
    • AC3: 'Reply on RC2', Jared Thomas, 11 Nov 2022

Jared J. Thomas et al.

Jared J. Thomas et al.


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Short summary
We wanted to determine if and how optimization algorithms may be exploiting inaccuracies in the simple models used for wind farm layout optimization. Comparing optimization results from a simple model to large-eddy simulations showed that even a simple model provides enough information for optimizers to find good layouts. However, varying the number of wind directions in the optimization showed that the wind resource discretization can negatively impact the optimization results.