Impact of inflow conditions and turbine placement on the performance of offshore wind turbines exceeding 7 MW

Abstract. Accurately assessing wind turbine performance in large offshore wind farms requires a nuanced understanding of how inflow parameters—turbulence intensity (TI), wind shear, and wind veer—affect power production across different turbine rows. In this study, we analyze 13 months of 10-minute operational data from more than 40 high-capacity turbines in a North Sea offshore wind farm, complemented by nacelle-based LiDAR measurements of inflow. Our objectives are to (1) determine how power production differs between front, middle and rear sections of the farm under the influence of TI, shear, and veer, and (2) evaluate the effectiveness of International Electrotechnical Commission (IEC)–based normalization methods, including Rotor Equivalent Wind Speed (REWS) and turbulence corrections in the front row and inside a wind farm consisting of large-scale wind turbines.

The results indicate that the impact of wind shear and veer on power output is strongly dependent on the turbine location: free stream shear and veer correlate negatively with active power in the front row, yet show positive correlations in the mid and rear rows. In addition, the TI in the wake region has a distinct influence on power production—particularly at lower wind speeds—relative to the TI observed in the free-flow region. Finally, the rear section of the wind farm exhibits approximately 20 % lower variability in active power relative to the front section. These location-specific changes underscore the evolving nature of inflow conditions within large wind farms. Furthermore, IEC-based REWS do not fully capture the effects of shear and veer in a large scale wind turbines in an offshore environment. The findings highlight that turbines operating in non-free-flow conditions may require additional inflow-characterization parameters beyond standard IEC norms to achieve more accurate performance evaluations and enhance overall farm efficiency.