Abstract

<p>The objective of this work is to enhance the understanding of the mean wind and turbulence characteristics in the wake of a full-scale wind turbine.  Here, we present observations of the three-dimensional wind vector in the near wake of a wind turbine, a Vestas V52 with a 52-m rotor diameter.  The test turbine is located at the Risø campus of the Technical University of Denmark (DTU). The measurements were acquired using three, state-of-the-art, scanning, continuous-wave wind lidars, developed in DTU Wind Energy (<em>Short-Range WindScanner</em>). In our study, the area of focus was a vertical, two-dimensional plane at a distance of two rotor diameters from the wind turbine, in the downwind direction. Using the scanning lidars it was possible to derive spatially distributed estimations of the first and second-order moments of the wind vector within the vertical plane. The plane was within an area equal to 2.6 x 1.8 rotor diameters, towards the transverse and vertical direction respectively, covering a measuring range that included both the wake and free flow. The field test took place during a period of almost two weeks (July 2 - July 14, 2019). Approximately half of the time, the wind direction was favourable such that the measuring plane was covering a cross-section of the mean flow, which included the entire area where the wind speed deficit occurred. This data set enables the quantification of the wind speed deficit and the corresponding momentum deficit in the wake and reveals the turbulent layer that surrounds the mean wind speed deficit. Thus, allowing the investigation of the relation between the momentum fluxes and the local wind speed gradients, which is important for the understanding of the physical properties of the flow behind a wind turbine. Furthermore, we investigate the effect that wakes have on the vertical shear close to the ground, which can have a direct impact on the wind-surface interaction on the downwind side. Since the measuring plane was extended also to areas of the free flow, we compare the wind characteristics within the mean wake flow to the ones of the free flow. The knowledge of the features of the wake and the physical connection between the mean and turbulent flow provides a new detailed input for improved wake modelling. This is necessary for a more accurate prediction of the wake characteristics and can enable a more realistic quantification of the interaction between wind turbines in a wind farm, as well as the impact of the wake flow on the surrounding microclimate.</p>

Highlights

  • OSA1.3 : Meteorological observations from GNSS and other space-based geodetic observing techniques OSA1.7: The Weather Research and Forecasting Model (WRF): development, research and applications

  • OSA3.5: MEDiterranean Services Chain based On climate PrEdictions (MEDSCOPE)

  • UP2.1 : Cities and urban areas in the earth- OSA3.1: Climate monitoring: data rescue, atmosphere system management, quality and homogenization 14:00-15:30

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Introduction

OSA1.3 : Meteorological observations from GNSS and other space-based geodetic observing techniques OSA1.7: The Weather Research and Forecasting Model (WRF): development, research and applications. EMS Annual Meeting Virtual | 3 - 10 September 2021 Strategic Lecture on Europe and droughts: Hydrometeorological processes, forecasting and preparedness Serving society – furthering science – developing applications: Meet our awardees ES2.1 - continued until 11:45 from 11:45: ES2.3: Communication of science ES2.2: Dealing with Uncertainties

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