Preprints
https://doi.org/10.5194/wes-2024-107
https://doi.org/10.5194/wes-2024-107
10 Sep 2024
 | 10 Sep 2024
Status: this preprint is currently under review for the journal WES.

Direct integration of non-axisymmetric Gaussian wind-turbine wake including yaw and wind-veer effects

Karim Ali, Pablo Ouro, and Tim Stallard

Abstract. The performance of a wind farm is significantly influenced by turbine-wake interactions. These interactions are typically quantified for each turbine by evaluating its rotor-averaged wind speed, which is impacted by upstream wakes, using numerical methods that involve discrete points across the rotor disk. Although various point distributions exist in the literature, we introduce an analytical expression for integrating a Gaussian wake over a circular disk, which accounts for wake stretching and shearing resulting from upstream turbine yaw and wind veer. This expression is versatile, accommodating any lateral offset and hub-height difference between the wake source (upstream turbines) and the target turbine. Validation against numerical evaluations of the rotor-averaged deficit at various downstream locations from the wake source demonstrates excellent agreement. Furthermore, the analytical expression is shown to be compatible with multiple wake superposition models. The presented solution is differentiable, providing a foundation for deriving mathematical expressions for the gradients of a turbine's power generation concerning its location within a farm and/or the operational conditions of upstream turbines. This capability is particularly advantageous for optimization-based applications.

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Karim Ali, Pablo Ouro, and Tim Stallard

Status: open (until 27 Oct 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2024-107', Anonymous Referee #1, 20 Sep 2024 reply
Karim Ali, Pablo Ouro, and Tim Stallard
Karim Ali, Pablo Ouro, and Tim Stallard

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Short summary
We introduce an innovative analytical method to better understand and optimize wind farm performance by accurately calculating how turbine wakes affect each other. Unlike traditional numerical approaches, our method provides a precise way to measure the impact of upstream wakes on downstream turbines. This new approach, validated through numerical comparisons, enhances optimisation strategies, potentially leading to more efficient wind farm operations and increased power generation.
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