A new analytical wake model for wind turbines, considering ambient turbulence intensity, thrust coefficient and yaw angle effects, is proposed from numerical and analytical studies. First, eight simulations by the Reynolds Stress Model are conducted for different thrust coefficients, yaw angles and ambient turbulence intensities. The wake deflection, mean velocity and turbulence intensity in the wakes are systematically investigated. A new wake deflection model is then proposed to analytically predict the wake center trajectory in the yawed condition. Finally, the effects of yaw angle are incorporated in the Gaussian-based wake model. The wake deflection, velocity deficit and added turbulence intensity in the wake predicted by the proposed model show good agreement with the numerical results. The model parameters are determined as the function of ambient turbulence intensity and thrust coefficient, which enables the model to have good applicability under various conditions.

LiDAR-based wind speed measurements have seen a significant increase in interest in wind energy. However, reconstruction of wind speed vector from a LiDAR-measured radial wind speed is still a challenge. Furthermore, for extensive application of LiDAR technology, it can be used as a means to validate simulation and analytical models. To that end, this study employed scanning Doppler LiDAR for assessment of wind fields at an offshore site and compared Weather Research and Forecasting (WRF)-based mesoscale simulations and several wake models with the measurements. Firstly, the effect of carrier-to-noise-ratio (CNR) and data availability on the quality of scanning LiDAR measurements was evaluated. Analysis of vertical profiles show that the average wind speed is higher for wind blowing from the sea than that blowing from the land. Furthermore, profiles obtained from the WRF simulation also show a similar tendency in the LiDAR measurements in general, though it overestimates the wind speeds at higher altitudes. A method for reconstruction of wind fields from plan-position indicator (PPI) and range height indicator (RHI) scans of LiDAR-measured line of sight velocities was then proposed and first used to investigate the effect of coastal terrain. An internal boundary layer with strong shear could be observed to develop from the coastline. Finally, the flow field around wind turbine was measured using PPI scan and used to validate wake models.

In this study, advanced hydrodynamic models are proposed to predict dynamic response of a floating offshore wind turbine (FOWT) in combined wave and current conditions and validated by laboratory and full-scale semi-submersible platforms. Firstly, hydrodynamic coefficient models are introduced to evaluate the added mass and drag coefficients in a wide range of Reynolds numbers. An advanced hydrodynamic model is then proposed to calculate the drag force of cylinder in combined wave and current conditions. The proposed model is validated by the water tank tests in the current-only, wave-only and current-wave conditions and is used to investigate the effect of current on the dynamic response of FOWT. Finally, the full-scale semi-submersible platform used in the Fukushima demonstration project is investigated. It is found that the predicted dynamic responses of platform by the proposed hydrodynamic models are improved by the directional spreading function of the sea wave spectrum and show favorable agreement with the field measurement.