Preprints
https://doi.org/10.5194/wes-2024-50
https://doi.org/10.5194/wes-2024-50
02 May 2024
 | 02 May 2024
Status: this preprint is currently under review for the journal WES.

Evaluating the potential of wake steering co-design for wind farm layout optimization through a tailored genetic algorithm

Matteo Baricchio, Pieter M. O. Gebraad, and Jan-Willem van Wingerden

Abstract. Wake steering represents a viable solution to mitigate the wake effect within a wind farm. New research that consider the effect of the control strategy within the layout optimization are emerging, adopting a co-design approach. This study estimates the potential of this technique within the layout optimization for a wide range of realistic conditions. To capture the benefits of such method, a genetic algorithm tailored to the layout optimization problem has been developed in this work, hence appointed as layout-optimization genetic algorithm (LO-GA). The crossover phase is designed to recognize and exploit the differences and the similarities between parent layouts whereas the randomness of the mutation is limited to improve the exploration of the design space. New relations have been introduced to calculate the geometric yaw angles based on the reciprocal positions between the turbines. For a base case of 16 turbines located at Hollandse Kust Noord site, a gain in the annual energy production between 0.3 % and 0.4 % is obtained when the co-design approach is adopted. This increases up to 0.6 % for larger farms, saturating after 25 turbines. The benefit of the co-design decreases if the power density of the wind farm is lower than 15 Wm-2 or if the wind resource is highly unidirectional. On the other hand, in case wake steering is not applied during the operation of the farm, a decrease in the AEP up to 0.6 % is registered for a layout optimized with the co-design method. To prevent the risk related to future decisions on the control strategy, a multi-objective co-design approach is proposed. This is based on the simultaneous optimization of the layout for a scenario in which wake steering is applied versus a case where wake steering is not adopted during the operation of the farm. We have concluded that the solutions obtained with this method ensure an AEP gain higher than 0.3 % for a 16-turbines farm while limiting the loss below 0.1 % in case wake steering is not applied.

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Matteo Baricchio, Pieter M. O. Gebraad, and Jan-Willem van Wingerden

Status: open (until 30 May 2024)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse
  • RC1: 'Comment on wes-2024-50', Anonymous Referee #1, 13 May 2024 reply
Matteo Baricchio, Pieter M. O. Gebraad, and Jan-Willem van Wingerden
Matteo Baricchio, Pieter M. O. Gebraad, and Jan-Willem van Wingerden

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Short summary
Wake steering can be integrated within the wind farm layout optimization through a co-design approach. This study estimates the potential of this method for a wide range of realistic conditions, adopting a tailored genetic algorithm and novel geometric yaw relations. A gain in the annual energy yield between 0.3 % and 0.4 % is obtained for a 16-tubrines farm and a multi-objective implementation is used to limit the loss in case wake steering is not used during the farm operation.
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