Intra-array wake meandering increases fatigue loading in downstream turbines and decreases farm total power output. In the case of floating offshore wind turbines (FOWTs), the motions of the floating substructure could have a non-neglectable contribution to wake meandering dynamics. This research experientially analyses the influence of imposed motions on the far-wake meandering of a FOWT. The study considers a 1:500 scaled porous disc representation of the 2 MW FLOATGEN system (BW Ideol) located off the coast of Le Croisic, France. A representative marine neutral atmospheric boundary layer is generated in a wind tunnel whilst monochromic and multi-frequency content three degrees of freedom (surge, heave, pitch) motion is imposed on the model tower. The stereoscopic particle image velocimetry (S-PIV) is then utilised to measure velocity vectors at a cross-section located at 8.125 D downstream of the model. No significant effect on the far-wake recovery in the velocity, turbulence and turbulent kinetic energy distribution is observed. However, the frequency characteristics of the imposed motions were observed in the far-wake meandering spectral content and streamwise characteristics of far-wake, such as normalised available power. While the frequency spectrum of the vertical oscillations showed more sensitivity to the three degrees of freedom (3DoF) imposed motion in all frequency ranges, the lateral oscillation was sensitive for the reduced frequency above 0.15. The monochromic motions with a reduced frequency of less than 0.15 also did not influence the far-wake centre distribution in both lateral and vertical directions. Regardless of reduced frequency, imposed motions show a strong effect on average power, in which the harmonic signature can distinguish in far-wake memory. This study provides an investigation, which its result could be beneficial to developing and examining wake models for offshore wind turbines, with a particular focus on the influence of FOWTs motions.

The growing interest in floating offshore wind turbines (FOWTs) is rooted in the potential source of increased offshore energy production. As the technology is still in a pre-industrial state, several questions remain to be addressed where little field data are available. This study uses physical modelling at a reduced scale to investigate the signature of the floating motions into the wake spectral content of a simplified FOWT model. A wind turbine model based on the actuator disc concept is placed in an atmospheric boundary layer wind tunnel and subjected to a range of surge, heave and pitch motions. The signatures of idealised sinusoidal motion and realistic broadband motion on the model’s wake at distances of 4.6 D (D being the disc diameter) and 8 D are measured through the use of a rake of single hot wires. The spectral analysis shows that harmonic motion leaves clear signatures in the far wake's energy spectra, mainly in the top tip region, while broadband motion does not leave easily detectable signatures.

To achieve more accurate weather and climate forecasting, and propose efficient engineering solutions for exploiting offshore renewable energies, it is imperative to accurately describe the atmospheric turbulent flow in the offshore environment. The ocean’s dynamics raise specific challenges for the aforementioned applications, as they significantly alter the atmospheric flow through complex wind–wave interactions. These interactions are important in fairly common situations and notably in old-sea conditions, where ocean waves travel fast, under comparatively slow wind velocities. In the present study, a scanning LiDAR (sLiDAR) was deployed on the shore to study micro-scale wind–wave interactions by performing horizontal scans 18 m above the ocean, and as far as 2 km from the coast. In the proposed configuration, and in the test cases presented in old seas, the sLiDAR captures wave-induced disturbances propagating into the lower part of the marine atmospheric boundary layer. Based on measurements of high-resolution space–time maps of the Radial Wind Speed, an original two-dimensional spectral analysis of the space–time auto-correlation functions was performed. Unlike more conventional data-processing techniques, and as long as the waves travel sufficiently (∼twofold) faster than the mean wind at the measurement height, the upward transfer of motions from the waves to the wind can be clearly distinguished from the atmospheric turbulence in the wave-number–angular-frequency (k–w) turbulent spectra. These are the first space–time auto-correlation functions of the wind velocity fluctuations obtained at micro-scales above the ocean. The analyses demonstrate sLiDAR systems’ applicability in measuring k–w-dependent turbulent spectra in the coastal environment. The findings present new perspectives for the study of micro-scale wind–wave interactions.