Abstract
The stability of the atmospheric boundary layer (ABL) is an important factor in wind turbine response analysis, as it affects mean wind profiles, turbulence characteristics, and wake behaviour. Existing studies on the sensitivity of floating wind turbine response to atmospheric stability rely on surface-layer profile formulations such as Monin-Obukhov similarity theory (MOST) or empirical power laws. These approaches are limited in their ability to represent stable conditions at the heights relevant to modern wind turbines, frequently overestimating wind shear beyond the shallow surface layer. In addition, stable atmospheres often exhibit local negative shear (low-level jets) and pronounced wind veering – both of which affect the structural response of wind turbines, particularly large rotor systems. More advanced models are therefore required to capture stable boundary layer wind profiles accurately and to reduce uncertainties in response simulations.
This study investigates the sensitivity of the global response of a 15-MW floating wind turbine to stable wind profiles derived from analytical models of varying complexity. Wind profiles are generated for combinations of rotor-equivalent wind speed and stability levels using MOST, the Gryning profile, and a recently developed analytical model for stable ABL flow, by Narasimhan. The latter enables modelling of both wind speed and direction profiles and features low-level jets under stable conditions. The selection of models facilitates a systematic assessment of shear, veer, and low-level jet effects while maintaining equal rotor-equivalent wind speed.
The wind profiles are used to generate turbulent inflow fields for dynamic response simulations of the IEA 15-MW reference turbine mounted on the VolturnUS-S semi-submersible floater. Substantial differences in platform motion, structural loads, and power output are observed and attributed to variations in the vertical and directional wind speed distributions across the rotor. The findings highlight the limitations of conventional surface-layer models under stable conditions and emphasize the importance of advanced wind modelling approaches to reduce uncertainties in response analyses and support the efficient design of floating wind turbines.