Posters

Abstract

Estimating the uncertainty of wind resource assessments is typically based on standard approaches, which have been developed over many years and usually are ultimately based on onshore experience. Although there is broad consensus across the industry on methodology and assumptions, comparing reports for the same project from different experienced analysts typically shows good agreement for the net energy yield, broad alignment for the overall uncertainty but different approaches and individual numbers for many of the individual categories, as well as the category structure, that make the total uncertainty. This is particularly the case if one analyst bases their estimate on precedent, whilst the other analyst attempts to derive the uncertainty from scientific first principles or evidence, including benchmarking. At Wind Europe's last Technical Workshop in June last year (2023) held in Lyon France, Wonjung Chung presented an assessment of the inherent variability and hence uncertainty of multiple wind measurement campaigns in the Dutch sector of the North Sea, which suggests that the uncertainty of floating LiDAR measurement campaigns is significantly lower than currently specified in the most widely deployed methods. The method presented was to estimate the total uncertainty and then extract the primary other components, specifically spatial and long-term correction uncertainty categories. Highly optimistic estimates of those two uncertainties were assumed, to ensure that the floating LiDAR measurement uncertainty would be robustly conservative and reliable. However, the same approach applied to LiDAR measurement uncertainty could equally be applied to the other two categories. This poster will explore the potential for estimating the true spatial and long-term correction uncertainty by using similar methods, i.e. * Assuming optimistic assumptions for floating LiDAR measurement and LTC uncertainty, what is the implied spatial uncertainty, and * Assuming optimistic assumptions for floating LiDAR measurement and spatial uncertainty, what is the implied long-term correction uncertainty Planned sensitivity studies planned to assess the robustness of the initial conclusions include: * Evaluating alternative mesoscale maps, including originated on alternative reanalysis datasets * With some measurement campaigns being longer than one year, also considering impact of campaign duration on long-term corrected mean windspeed and associated uncertainty