What Are The Optimal Yaw Misalignment Correction Strategies To Mitigate The Effects Of Wake-induced Turbulence On Downstream Wind Turbines In A Tightly-spaced Offshore Wind Farm With Varying Water Depths And Seafloor Topographies?
The optimal strategies to mitigate wake-induced turbulence in a tightly spaced offshore wind farm with varying water depths and seafloor topographies involve a multi-faceted approach:
-
Wake Steering: Adjust the yaw angle of upstream turbines to direct their wakes away from downstream turbines. This is particularly effective in reducing interference, though effectiveness may vary with turbine spacing.
-
Dynamic Yaw Optimization: Implement real-time adjustments of yaw angles based on changing wind conditions and turbine loads. This requires advanced sensors and algorithms to continuously optimize each turbine's orientation.
-
Environmental Data Integration: Incorporate detailed water depth and seafloor topography data into control systems to better predict wake behavior in complex underwater environments.
-
Collaborative Control Strategies: Coordinate yaw adjustments across multiple turbines to create a beneficial flow regime, minimizing wake interference collectively.
-
Machine Learning and SCADA Analysis: Use historical data from SCADA systems and machine learning models to predict wake patterns and proactively adjust turbine yaw angles.
-
Turbine Layout Consideration: While rearrangement may not be feasible in existing farms, understanding the impact of layout on wake propagation can inform yaw adjustment strategies.
By combining these approaches, the wind farm can effectively mitigate wake effects, enhancing both performance and longevity of the turbines.