Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures
<p>The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actu...
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| Format: | Article |
| Language: | English |
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Copernicus Publications
2025-07-01
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| Series: | Wind Energy Science |
| Online Access: | https://wes.copernicus.org/articles/10/1403/2025/wes-10-1403-2025.pdf |
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| author | L. Cheung G. Yalla P. Mohan A. Hsieh K. Brown N. deVelder D. Houck M. T. Henry de Frahan M. Day M. Sprague |
| author_facet | L. Cheung G. Yalla P. Mohan A. Hsieh K. Brown N. deVelder D. Houck M. T. Henry de Frahan M. Day M. Sprague |
| author_sort | L. Cheung |
| collection | DOAJ |
| description | <p>The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actuation. In this work, we develop a framework, which accounts for the impacts of the large-scale coherent structures and turbulence on the mean flow, for modeling AWM. The framework uses a triple-decomposition approach for the unsteady flow field and models the mean flow and fine-scale turbulence with a parabolized Reynolds-averaged Navier–Stokes (RANS) system. The wave components are modeled using a simplified spatial linear stability formulation that captures the growth and evolution of the coherent structures. Comparisons with high-fidelity large eddy simulations (LESs) of the turbine wakes showed that this framework was able to capture the additional wake mixing and faster wake recovery in the far-wake regions for both the pulse and helix AWM strategies with minimal computational expense. In the near-wake region, some differences are observed in both the RANS velocity profiles and initial growth of the large-scale structures, which may be due to some simplifying assumptions used in the model.</p> |
| format | Article |
| id | doaj-art-6ffe9935d99f491f915eb7a226e08f26 |
| institution | Kabale University |
| issn | 2366-7443 2366-7451 |
| language | English |
| publishDate | 2025-07-01 |
| publisher | Copernicus Publications |
| record_format | Article |
| series | Wind Energy Science |
| spelling | doaj-art-6ffe9935d99f491f915eb7a226e08f262025-08-20T03:28:06ZengCopernicus PublicationsWind Energy Science2366-74432366-74512025-07-01101403142010.5194/wes-10-1403-2025Modeling the effects of active wake mixing on wake behavior through large-scale coherent structuresL. Cheung0G. Yalla1P. Mohan2A. Hsieh3K. Brown4N. deVelder5D. Houck6M. T. Henry de Frahan7M. Day8M. Sprague9Sandia National Laboratories, Livermore, CA, USASandia National Laboratories, Albuquerque, NM, USANational Renewable Energy Laboratory, Golden, CO, USASandia National Laboratories, Albuquerque, NM, USASandia National Laboratories, Albuquerque, NM, USASandia National Laboratories, Albuquerque, NM, USASandia National Laboratories, Albuquerque, NM, USANational Renewable Energy Laboratory, Golden, CO, USANational Renewable Energy Laboratory, Golden, CO, USANational Renewable Energy Laboratory, Golden, CO, USA<p>The use of active wake mixing (AWM) to mitigate downstream turbine wakes has created new opportunities for reducing power losses in wind farms. However, many current analytical or semi-empirical wake models do not capture the flow instabilities that are excited through the blade pitch actuation. In this work, we develop a framework, which accounts for the impacts of the large-scale coherent structures and turbulence on the mean flow, for modeling AWM. The framework uses a triple-decomposition approach for the unsteady flow field and models the mean flow and fine-scale turbulence with a parabolized Reynolds-averaged Navier–Stokes (RANS) system. The wave components are modeled using a simplified spatial linear stability formulation that captures the growth and evolution of the coherent structures. Comparisons with high-fidelity large eddy simulations (LESs) of the turbine wakes showed that this framework was able to capture the additional wake mixing and faster wake recovery in the far-wake regions for both the pulse and helix AWM strategies with minimal computational expense. In the near-wake region, some differences are observed in both the RANS velocity profiles and initial growth of the large-scale structures, which may be due to some simplifying assumptions used in the model.</p>https://wes.copernicus.org/articles/10/1403/2025/wes-10-1403-2025.pdf |
| spellingShingle | L. Cheung G. Yalla P. Mohan A. Hsieh K. Brown N. deVelder D. Houck M. T. Henry de Frahan M. Day M. Sprague Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures Wind Energy Science |
| title | Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures |
| title_full | Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures |
| title_fullStr | Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures |
| title_full_unstemmed | Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures |
| title_short | Modeling the effects of active wake mixing on wake behavior through large-scale coherent structures |
| title_sort | modeling the effects of active wake mixing on wake behavior through large scale coherent structures |
| url | https://wes.copernicus.org/articles/10/1403/2025/wes-10-1403-2025.pdf |
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