Abstract
Offshore wind has an important role in achieving net zero targets and is
a vital contributor to addressing the energy crisis. Continued expansion
in offshore wind is driving industry and governments across the world to
explore deeper and more exposed sites. Standard wind measurements using
meteorological masts are more challenging, or even impractical at such
sites. As a result, floating LIDAR and physics-based mesoscale models
are increasingly being deployed as cost-effective solutions for resource
assessment. This study investigates the performance of a meso-microscale
coupled Weather Research and Forecasting model by comparing against
using 15-months of in-situ wind data collected from two floating LiDAR
systems deployed in the Celtic Sea, Southwest UK. Wind speed
measurements from model and measurement were compared directly. Vertical
wind speed gradient estimates, chosen to quantify how the two data sets
predicted wind shear, were also compared, along with estimates of energy
generation, as predicted by the two data sets. At approximate turbine
hub height (150 m), the model predicted mean wind speeds are 2.38% and
2.81% lower than the measurements and 4.96% and 4.51% lower at the
P95 wind speed, for the two measurement locations. However, the
differences are greater at wind speeds faster than the turbine cut-out
speed. The inverse is true at for windspeeds, below the turbine cut-in
speed, where model predicted wind speeds are greater than the
measurements. As these high and low wind speeds do not contribute to
energy generation, the differences between model-predicted and
measurement-predicted energy production are smaller, with model
estimates lower by 0.56% and 1.32% for the two measurement sites.
Model calculated wind speed gradients were notably different from the
measurement-calculated wind speed gradients. In particular, the 90
th percentile value is 35% lower than that predicted
by measurements. Attempts to account for this when calculating energy
generation suggested that the model estimates were lower than
measurements by a much lower margin of 0.6% and 1.37%for the two
floating LiDAR locations. This work identifies differences between
numerical model predictions and floating Lidar measurements for a
proposed offshore wind site. Of the parameters considered, the energy
production estimates show the least difference. This helps inform
studies looking to accurately evaluate wind resource at more exposed
sites. However, usage of wind data that specifically relies on accuracy
for large or small wind speeds, such as engineering design, or weather
window calculations will be required to consider the impact of the
observed differences on their results.