Posters

Abstract

Turbulence intensity (TI) is an important wind quantity impacting fatigue loading on turbine components and hence their lifetime. For offshore sites, Floating Lidar Systems (FLS) are the de-facto wind resource measurement instrumentation due to their deployment flexibility, track record and measurement accuracy. However, the estimation of turbulence intensity from an FLS is biased high owing to the influence of buoy motion due to waves on the measurements in addition to the measurement principle of a lidar device. To compensate the impact of wave motion on the lidar measurements, mechanical compensation or post-processing approaches are normally used where the wave influence on the measurements is compensated accounting for the buoy motion. While both methods have been shown to reduce the motion impact on the measurements, the first method requires extra hardware increasing the cost while unable to compensate for large motions. The second method requires access to the high-frequency lidar line-of-sight measurements (LOS), which is not yet a standard part of a lidar measurement dataset. Therefore, in this work, we investigate a motion compensation model where the compensation is applied to reconstructed lidar wind fields instead of the high-frequency LOS measurements. Establishing model performance on the reconstructed lidar wind fields in comparison to the high-frequency LOS data would enable the reanalysis of current and historic measurement campaign data to generate motion compensated TI. We conduct the study in a simulation environment where the wind field, wave field and lidar are emulated. Synthetic 3D turbulence wind fields are generated using TurbSim allowing for the investigation of a range of flow conditions on which to test the compensation model. The lidar measurements and wave impact on the measurements are simulated inside the 3D wind fields using a lidar simulator that recreates lidar kinematic and optical properties. For the study, we investigate both continuous-wave (ZX300) and pulsed (Windcube) vertically profiling lidars. First, the sensitivity to the induced translational and rotational motion due to the wave motion is investigated to understand the sensitivity of buoy motion on the reconstructed wind field. Subsequently, the motion compensation methodology is applied to the reconstructed wind field compensating for the wave motion. The compensated TI results are compared against a virtual fixed lidar and a virtual anemometer in addition to the high-frequency compensation approach to quantify the accuracy of the model. A comparison against the high-frequency compensation is also performed to further understand the effectiveness of the two methods. The results of the study would be used to inform the effectiveness of the motion compensation on reconstructed lidar data and allow for a better estimation of TI and enabling the reduction in uncertainty in the design criteria for offshore wind farm development.