Posters

Abstract

The interaction between wind farms and the surrounding atmosphere is an extremely complex process which brings significant modelling challenges. As wind farms and cluster increase in size and scope, the risk of potential AEP biases and uncertainty increases thereby requiring greater understanding of this interaction. One such component is wind farm blockage, however there has been a lot of debate as to its nature and requirements for modelling such an effect, and has been cited as a potential for unexplained deviations between pre-/post-construction energy yield estimates. The Offshore Wind Accelerator's (OWA) Global Blockage Effect (GloBE) project set out to provide the industry with consensus on the nature of the blockage effect phenomenon, the required physics recipe when modelling it, and establishing accountancy framework. The project, which concluded December 2023, was led by RWE and the Carbon Trust, funded by ten of the leading offshore wind farm developers and the Crown Estate, and included in-kind contributions from Vaisala and DTU and collaborations with projects run by Fraunhofer IWES (X-Wakes) and TNO (AFFABLE). It strived to achieve consensus by: * Conducting a large-scale 8-month measurement campaign at RWE's Nordsee Ost and Amrumbank West wind farms in the German Bight using 7x scanning LiDARs, 1x floating LiDAR, turbine SCADA and refurbished met mast * Assembling a large consortium of industry experts (including many of the leading Lenders' Technical Advisors (LTAs)) to: 1. Critique and inform the measurement campaign design 2. Validate various blockage models against the measured data 3. Work together to develop a shared understanding of blockage * Conducting an array of modelling across a range of model orders including LES-CFD, RANS-CFD and rapid models to delineate the physics of blockage * Testing a set of hypotheses using a combination of measurements from the offshore experiment and modelling. The measurement campaign has delivered a huge, rich and robust dataset capturing critical flow behaviour including both de-/accelerations crucial to understanding the blockage effect. New and novel techniques are used to ensure that lower-than-typical measurement uncertainty such as motion correction and drone-based hard targeting. Patterns of wind speed and turbine power are compared against models in order to better understand the physics of blockage and derive a recipe to model the complex farm-atmosphere interaction with rapid engineering models. Since previous publications [1] [2] [3] [4] [5] [6] [7] [8], delegates will see the full and final state-of-the-art processed measured wind/SCADA dataset including accessing it. Model comparisons over the full spectrum available will demonstrate how different models perform. Engineers engaged in energy yield predictions can draw on this best practice to inform their on processes. Financiers and commercial managers can use the findings from GloBE to scrutinise yield estimates for proposed wind farm developments, understanding whether the losses and uncertainties assigned are credible. Researchers will learn where areas of uncertainty and disagreement remain so that future research can be targeted appropriately. Lastly, areas where consensus has been reached will be communicated to the industry, which will gain confidence in a crucial area of energy yield assessment.