Cyclic yaw control for wind farm power optimization: The role of Strouhal number, farm configuration, and turbulence intensity

This study investigates the potential of the cyclic yaw control (CYC) strategy to enhance the power performance of wind farms. Wind tunnel experiments are conducted to evaluate the effectiveness of CYC (only yawing the first wind turbine) under various inflow conditions and farm configurations. The effects of different turbine numbers, spacing and control parameters (including initial yaw angle, yaw amplitude and Strouhal number) on power efficiency are systematically examined. Results show that CYC significantly improves power production in full wake state, with a 32% maximum gain in an eight-turbine wind farm model under moderate inflow turbulence intensity (0.07). This gain decreases to 17% as turbulence intensity increases to 0.12. The control strategy becomes more effective in larger farms with denser turbine arrangements, especially when wake effects are significant. In all scenarios, the maximum power gain is achieved when the yaw Strouhal number falls within [0.10,0.25] and the amplitude is in the range [20∘,30∘]. The optimal yaw Strouhal number decreases with farm length, while the optimal amplitude increases slightly. Inflow conditions and spanwise spacing affect wind farm power production but have negligible effects on the optimal control parameters. Power outputs under CYC exhibit periodic behavior, with fluctuations generally stronger than baseline cases. Interestingly, in the Strouhal number range around 0.24−0.44, CYC increases the mean power production while reducing power fluctuations of a three-turbine wind farm. Overall, these findings suggest that CYC holds considerable potential to improve wind farm power performance.

Authors

Publication Details

Journal
Applied Energy
Published
2026-01-22
DOI
https://doi.org/10.1016/j.apenergy.2026.127419
Citations
2
Primary Topic
Wind Energy Research and Development
Type
article
Field-Weighted Citation Impact
209.38
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article

Cyclic yaw control for wind farm power optimization: The role of Strouhal number, farm configuration, and turbulence intensity

Guiyue Duan, Fernando Porté-Agel
2 citations
Applied Energy
Wind Energy Research and Development
209.38
article

Cyclic yaw control for wind farm power optimization: The role of Strouhal number, farm configuration, and turbulence intensity

Guiyue Duan, Fernando Porté-Agel
article en
2 citations

Abstract

This study investigates the potential of the cyclic yaw control (CYC) strategy to enhance the power performance of wind farms. Wind tunnel experiments are conducted to evaluate the effectiveness of CYC (only yawing the first wind turbine) under various inflow conditions and farm configurations. The effects of different turbine numbers, spacing and control parameters (including initial yaw angle, yaw amplitude and Strouhal number) on power efficiency are systematically examined. Results show that CYC significantly improves power production in full wake state, with a 32% maximum gain in an eight-turbine wind farm model under moderate inflow turbulence intensity (0.07). This gain decreases to 17% as turbulence intensity increases to 0.12. The control strategy becomes more effective in larger farms with denser turbine arrangements, especially when wake effects are significant. In all scenarios, the maximum power gain is achieved when the yaw Strouhal number falls within [0.10,0.25] and the amplitude is in the range [20∘,30∘]. The optimal yaw Strouhal number decreases with farm length, while the optimal amplitude increases slightly. Inflow conditions and spanwise spacing affect wind farm power production but have negligible effects on the optimal control parameters. Power outputs under CYC exhibit periodic behavior, with fluctuations generally stronger than baseline cases. Interestingly, in the Strouhal number range around 0.24−0.44, CYC increases the mean power production while reducing power fluctuations of a three-turbine wind farm. Overall, these findings suggest that CYC holds considerable potential to improve wind farm power performance.

Applied EnergyVol. 408
Affordable and clean energy
Openalex Percentile: Top 0%
Wind Energy Research and Development
209.38
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