Abstract
This work presents a new methodology to estimate the motion-induced standard deviation and related turbulence intensity on the retrieved horizontal wind speed by means of the velocity-azimuth-display algorithm applied to the conical scanning pattern of a floating Doppler lidar. The method considers a ZephIR™300 continuous-wave focusable Doppler lidar and does not require access to individual line-of-sight radial-wind information along the scanning pattern. The method combines a software-based velocity-azimuth-display and motion simulator and a statistical recursive procedure to estimate the horizontal wind speed standard deviation—as a well as the turbulence intensity—due to floating lidar buoy motion. The motion-induced error is estimated from the simulator’s side by using basic motional parameters, namely, roll/pitch angular amplitude and period of the floating lidar buoy, as well as reference wind speed and direction measurements at the study height. The impact of buoy motion on the retrieved wind speed and related standard deviation is compared against a reference sonic anemometer and a reference fixed lidar over a 60-day period at the IJmuiden test site (the Netherlands). Individual case examples and an analysis of the overall campaign are presented. After the correction, the mean deviation in the horizontal wind speed standard deviation between the reference and the floating lidar was improved by about 70%, from 0.14 m/s (uncorrected) to −0.04 m/s (corrected), which makes evident the goodness of the method. Equivalently, the error on the estimated turbulence intensity (3–20 m/s range) reduced from 38% (uncorrected) to 4% (corrected).
Highlights
In recent years, offshore wind energy has become a trustable and mature technology for electricity generation [1]
The ZephIRTM300 lidar used in this work is a continuous-wave focusable Doppler lidar adapted for offshore measurements that uses a conical scanning pattern combined with the velocity-azimuth-display algorithm to retrieve the wind velocity
We presented a methodology to estimate the 10-min motion-induced standard deviation and turbulence intensity on the retrieved horizontal wind speed (HWS) for a ZephIRTM300 lidar at a given measurement height without accessing individual line-of-sight information of the lidar scanning pattern or individual 1-s data
Summary
Offshore wind energy has become a trustable and mature technology for electricity generation [1]. Due to the high requirements of the industry regarding resolution and accuracy, lidar has been the most used technology for different applications in the wind energy sector since the appearance of the first commercial units. These applications include turbine control [12], resource assessment [13,14,15], wakes [16,17,18], and power curve measurements in flat terrain [19], among others
Sign-in/Register to view highlights & summary Sign-in/Register to access full text options 
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Schedule a callDisclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.
