Abstract
As offshore wind farms grow to multi-gigawatt scales, wake interactions become a significant source of energy loss and can potentially reduce annual energy production (AEP) by up to 10–20%. Yaw-based wake steering is a promising control strategy to mitigate these losses by intentionally misaligning turbine yaw angles to deflect wakes away from downstream turbines. This study investigates yaw-based wake steering at the Alpha Ventus offshore wind farm using an integrated aerodynamic and economic evaluation framework. The framework employs a BEM-based, yaw-aware Gaussian wake model with gradient-based optimization. The model is benchmarked against widely used engineering models, PyWake and TOPFARM, to ensure consistency. The study is evaluated primarily using site-specific Alpha Ventus conditions, with idealized inflow scenarios used for supporting analysis. The optimized yaw strategy increases total farm AEP on the order of 3.75%, achieving a substantial reduction in mean wake deficit (over 60%) compared to baseline operation. These improvements persist across a broad range of wind conditions, indicating a robust benefit from wake steering. Furthermore, an economic evaluation across multiple price scenarios demonstrates improved financial performance with yaw control. The levelized cost of energy (LCOE) is reduced, accompanied by increases in net present value (NPV), internal rate of return (IRR), and capacity factor (CF) relative to baseline operation. The results highlight the value of integrating farm-level control with economic analysis and support further development of load-aware and adaptive yaw control strategies.