Our analysis gave our client a more accurate characterisation of the wind resource at its site.
Confidential
Our client was developing an offshore wind farm and as part of its Energy Yield Estimate (EYA), it required an accurate prediction of the wind climate at the site. In the absence of a meteorological mast on site, our client was deriving the wind climate from other sources, including a light detection and ranging method (LIDAR) on a nearby island.
The LIDAR system had collected a large amount of data but was affected by two elements which had to be compensated for:
We were asked to quantify both elements and assess the sensitivity of the conclusions to atmospheric stability. We used computational fluid dynamics (CFD) to simulate the wind over the island, including meshing around the steep cliffs and incorporating atmospheric stability variations into the model. We then assessed the operational performance of the LIDAR unit by calculating the radial velocities that the LIDAR would measure and the way in which it would interpret them, to infer the horizontal wind speed.
This analysis gave our client a more accurate characterisation of the wind resource at the site. From the results, we were able to determine factors to:
This improved the confidence in the wind resource assessment and reduced uncertainty in the estimate, which will feed into the client’s business case for potential investors in the wind farm.
