Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions
<jats:p>Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability. We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, in which variations in...
| Main Authors: | , , , , , , , |
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| Other Authors: | |
| Format: | Article |
| Language: | English |
| Published: |
Copernicus GmbH
2023
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| Online Access: | https://hdl.handle.net/1721.1/148536 |
| _version_ | 1811079547353825280 |
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| author | Howland, Michael F Ghate, Aditya S Quesada, Jesús Bas Pena Martínez, Juan José Zhong, Wei Larrañaga, Felipe Palou Lele, Sanjiva K Dabiri, John O |
| author2 | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering |
| author_facet | Massachusetts Institute of Technology. Department of Civil and Environmental Engineering Howland, Michael F Ghate, Aditya S Quesada, Jesús Bas Pena Martínez, Juan José Zhong, Wei Larrañaga, Felipe Palou Lele, Sanjiva K Dabiri, John O |
| author_sort | Howland, Michael F |
| collection | MIT |
| description | <jats:p>Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability.
We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, in which variations in the surface heat flux in time modify the atmospheric stability, wind speed and direction, shear, turbulence, and other atmospheric boundary layer (ABL) flow features.
The closed-loop wake steering control methodology developed in Part 1 (Howland et al., 2020c, https://doi.org/10.5194/wes-5-1315-2020) is implemented in an example eight turbine wind farm in large eddy simulations of the diurnal cycle.
The optimal yaw misalignment set points depend on the wind direction, which varies in time during the diurnal cycle.
To improve the application of wake steering control in transient ABL conditions with an evolving mean flow state, we develop a regression-based wind direction forecast method.
We compare the closed-loop wake steering control methodology to baseline yaw-aligned control and open-loop lookup table control for various selections of the yaw misalignment set-point update frequency, which dictates the balance between wind direction tracking and yaw activity.
In our diurnal cycle simulations of a representative wind farm geometry, closed-loop wake steering with set-point optimization under uncertainty results in higher collective energy production than both baseline yaw-aligned control and open-loop lookup table control.
The increase in energy production for the simulated wind farm design for closed- and open-loop wake steering control, compared to baseline yaw-aligned control, is 4.0 %–4.1 % and 3.4 %–3.8 %, respectively, with the range indicating variations in the energy increase results depending on the set-point update frequency.
The primary energy increases through wake steering occur during stable ABL conditions in our present diurnal cycle simulations.
Open-loop lookup table control decreases energy production in the example wind farm in the convective ABL conditions simulated, compared to baseline yaw-aligned control, while closed-loop control increases energy production in the convective conditions simulated.
</jats:p> |
| first_indexed | 2024-09-23T11:16:45Z |
| format | Article |
| id | mit-1721.1/148536 |
| institution | Massachusetts Institute of Technology |
| language | English |
| last_indexed | 2024-09-23T11:16:45Z |
| publishDate | 2023 |
| publisher | Copernicus GmbH |
| record_format | dspace |
| spelling | mit-1721.1/1485362023-03-15T03:32:31Z Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions Howland, Michael F Ghate, Aditya S Quesada, Jesús Bas Pena Martínez, Juan José Zhong, Wei Larrañaga, Felipe Palou Lele, Sanjiva K Dabiri, John O Massachusetts Institute of Technology. Department of Civil and Environmental Engineering <jats:p>Abstract. The magnitude of wake interactions between individual wind turbines depends on the atmospheric stability. We investigate strategies for wake loss mitigation through the use of closed-loop wake steering using large eddy simulations of the diurnal cycle, in which variations in the surface heat flux in time modify the atmospheric stability, wind speed and direction, shear, turbulence, and other atmospheric boundary layer (ABL) flow features. The closed-loop wake steering control methodology developed in Part 1 (Howland et al., 2020c, https://doi.org/10.5194/wes-5-1315-2020) is implemented in an example eight turbine wind farm in large eddy simulations of the diurnal cycle. The optimal yaw misalignment set points depend on the wind direction, which varies in time during the diurnal cycle. To improve the application of wake steering control in transient ABL conditions with an evolving mean flow state, we develop a regression-based wind direction forecast method. We compare the closed-loop wake steering control methodology to baseline yaw-aligned control and open-loop lookup table control for various selections of the yaw misalignment set-point update frequency, which dictates the balance between wind direction tracking and yaw activity. In our diurnal cycle simulations of a representative wind farm geometry, closed-loop wake steering with set-point optimization under uncertainty results in higher collective energy production than both baseline yaw-aligned control and open-loop lookup table control. The increase in energy production for the simulated wind farm design for closed- and open-loop wake steering control, compared to baseline yaw-aligned control, is 4.0 %–4.1 % and 3.4 %–3.8 %, respectively, with the range indicating variations in the energy increase results depending on the set-point update frequency. The primary energy increases through wake steering occur during stable ABL conditions in our present diurnal cycle simulations. Open-loop lookup table control decreases energy production in the example wind farm in the convective ABL conditions simulated, compared to baseline yaw-aligned control, while closed-loop control increases energy production in the convective conditions simulated. </jats:p> 2023-03-14T15:28:21Z 2023-03-14T15:28:21Z 2022 2023-03-14T15:23:24Z Article http://purl.org/eprint/type/JournalArticle https://hdl.handle.net/1721.1/148536 Howland, Michael F, Ghate, Aditya S, Quesada, Jesús Bas, Pena Martínez, Juan José, Zhong, Wei et al. 2022. "Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions." Wind Energy Science, 7 (1). en 10.5194/WES-7-345-2022 Wind Energy Science Creative Commons Attribution 4.0 International license https://creativecommons.org/licenses/by/4.0/ application/pdf Copernicus GmbH Copernicus Publications |
| spellingShingle | Howland, Michael F Ghate, Aditya S Quesada, Jesús Bas Pena Martínez, Juan José Zhong, Wei Larrañaga, Felipe Palou Lele, Sanjiva K Dabiri, John O Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions |
| title | Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions |
| title_full | Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions |
| title_fullStr | Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions |
| title_full_unstemmed | Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions |
| title_short | Optimal closed-loop wake steering – Part 2: Diurnal cycle atmospheric boundary layer conditions |
| title_sort | optimal closed loop wake steering part 2 diurnal cycle atmospheric boundary layer conditions |
| url | https://hdl.handle.net/1721.1/148536 |
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