Coastal wind speed gradients relevant for offshore windfarming are analysed based on synthetic aperture radar (SAR) data. The study concentrates on situations with offshore wind directions in the ...German Bight using SAR scenes from the European satellites Sentinel-1A and Sentinel-1B. High resolution wind fields at 10 m height are derived from the satellite data set and respective horizontal wind speed gradients are investigated up to about 170 km offshore. The wind speed gradients are classified according to their general shape with about 60% of the cases showing an overall increase of wind speeds with growing distance from the coast. About half of the remaining cases show an overall wind speed decrease and the other half a decrease with a subsequent increase at larger distances from the coast. An empirical model is fitted to the horizontal wind speed gradients, which has three main parameters, namely, the wind speed over land, the equilibrium wind speed over sea far offshore, and a characteristic adjustment length scale. For the cases with overall wind speed increase, a mean absolute difference of about 2.6 m/s is found between wind speeds over land and wind speeds far offshore. The mean normalised wind speed increase with respect to the land conditions is estimated as 40%. In terms of wind power density at 10 m height this corresponds to an absolute average growth by 0.3 kW/m2 and a normalised increase by 160%. The distance over which the wind speed grows to 95% of the maximum wind speed shows large variations with maximum above 170 km and a mean of 67 km. The impact of the atmospheric boundary layer stability on horizontal wind speed gradients is investigated using additional information on air and sea temperature differences. The absolute SAR-derived wind speed increase offshore is usually higher in unstable situations and the respective adjustment distance is shorter. Furthermore, we have found atypical cases with a wind speed decrease offshore to be often connected to stable atmospheric conditions. A particular low-level jet (LLJ) situation is analysed in more detail using vertical wind speed profiles from a wind LIDAR system.
The potential impact of offshore wind farms through decreasing sea surface wind speed on the shear forcing and its consequences for the ocean dynamics are investigated. Based on the unstructured-grid ...model SCHISM, we present a new cross-scale hydrodynamic model setup for the southern North Sea, which enables high-resolution analysis of offshore wind farms in the marine environment. We introduce an observational-based empirical approach to parameterize the atmospheric wakes in a hydrodynamic model and simulate the seasonal cycle of the summer stratification in consideration of the recent state of wind farm development in the southern North Sea. The simulations show the emergence of large-scale attenuation in the wind forcing and associated alterations in the local hydro- and thermodynamics. The wake effects lead to unanticipated spatial variability in the mean horizontal currents and to the formation of large-scale dipoles in the sea surface elevation. Induced changes in the vertical and lateral flow are sufficiently strong to influence the residual currents and entail alterations of the temperature and salinity distribution in areas of wind farm operation. Ultimately, the dipole-related processes affect the stratification development in the southern North Sea and indicate potential impact on marine ecosystem processes. In the German Bight, in particular, we observe large-scale structural change in stratification strength, which eventually enhances the stratification during the decline of the summer stratification toward autumn.
Wind speed deficits behind offshore wind parks in the German Bight are estimated from satellite synthetic aperture radar (SAR) data using a new filter technique. The deficit computation requires ...knowledge about the undisturbed wind field, which is derived by a two-dimensional (2D) convolution filter tailored to the geometry of the wake. Both the wind direction and the size of the wind farm are taken into account. The most relevant scale for the wind speed deficit estimator (WISDEM) is the width ξ$\xi$ of the wake. Unlike approaches used so far, the proposed technique is suitable for a full automisation of the estimation process. Furthermore, the rigorous definition of the method and the reproducibility of the results can help in the consistent analysis of big data sets and the meaningful intercomparison of different geographic study areas. The filter is applied to Sentinel‑1 SAR data demonstrating the ability of the method to quantify and visualise wind speed deficits in a very efficient way. The method also allows the study of the 2D structure of wakes, in particular curved shapes, which are found frequently. A statistical wake analysis is performed for one year of data showing the most frequent occurrence of wakes during the spring and summer seasons. According to mast measurements taken at the FINO‑1 platform, this period is characterised by relatively strong atmospheric stability. Error estimates are derived for WISDEM wind speed deficit estimates based on a 2D spectral analysis of a Sentinel‑1 SAR data set acquired over one year. The impact of the wake filter on the background wind spectrum is quantified by application of the convolution theorem. The deficit estimation error is shown to increase with decreasing deficit values and with increasing wake width. The error is most sensitive to spectral components with wavelength in the across wake direction near 2ξ$2\xi$. The slope of the derived wind spectra is very close to the Kolmogorov k-5∕3$k^{-5/3}$ law, at least down to wave length of about 3 km. A significant dependence of the spectra on the atmospheric stability was found with energy levels increasing with instability. This relationship is beneficial for wake estimations, because wakes are more likely to occur in stable conditions, where relatively homogeneous background wind fields lead to reduced deficit estimation errors.
This publication synthesizes the results of the WIPAFF (WInd PArk Far Fields) project. WIPAFF focused on the far field of large offshore wind park wakes (more than 5 km downstream of the wind parks) ...located in the German North Sea. The research project combined in situ aircraft and remote sensing measurements, satellite SAR data analysis and model simulations to enable a holistic coverage of the downstream wakes. The in situ measurements recorded on-board the research aircraft DO‑128 and remote sensing by laser scanner and SAR prove that wakes of more than 50 kilometers exist under certain atmospheric conditions. Turbulence occurs at the lateral boundaries of the wakes, due to shear between the reduced wind speed inside the wake and the undisturbed flow. The results also reveal that the atmospheric stability plays a major role in the evolution of wakes and can increase the wake length significantly by a factor of three or more. On the basis of the observations existing mesoscale and industrial models were validated and updated. The airborne measurement data is available at PANGAEA/ESSD.
The transition from land to sea affects the wind field in coastal regions. From the perspective of near-coastal offshore wind farms, the coastal transition complicates the task of energy resource ...assessment by, for example, introducing non-homogeneity into the free wind field. To help elucidate the matter, we quantify the average horizontal wind speed gradients at progressively increasing distances from the German coast using two years of hourly ERA5 reanalysis data, and further describe the dependence of wind speed gradients on the measurement height, atmospheric stability, and season. A vertical wind lidar located on Norderney Island near the German mainland acts as our observational reference for the ERA5 data, where a good agreement (R2=0.93$R^2 =\nobreak 0.93$) is found despite the relatively coarse ERA5 data resolution. Interestingly, the comparison of lidar data with the higher-resolution Weather Research and Forecasting (WRF) mesoscale model yields good but relatively weaker agreement (R2=0.85$R^2 =\nobreak 0.85$). The ERA5 data reveal that, for flow over the North Sea originating from the German mainland from the south, the wind speed at 10 m (110 m) above sea level increases by 30 % (20 %) some 80 km from the coast on average, and by 5 % at larger heights. An increased stratification increases the horizontal wind speed gradient at 10 m above sea level but decreases it at 110 m. Case studies using satellite and flight measurements are first analyzed to help reveal some of the underlying mechanisms governing horizontal wind speed gradients, including cases of decreasing wind speed with increasing distance from the coast, in which stable flow of warm air over the colder sea leads to an overall deceleration of the flow. The accuracy of offshore resource assessment appears to profit from utilising the horizontal wind speed gradient information contained in ERA5 reanalysis data.
Large offshore wind farms are usually clustered around transmission grids to minimize the expense of transmission, due to military zones, pipelines, and due to other uses such as nature preserves. ...However, this close proximity can undermine power production in downwind wind farms due to wakes from upwind wind farms. Therefore, the wind energy industry has great interest in determining the spatial dimensions of offshore wind farm wakes to assess the economical potential of planned wind farms. In this work we use wake measurements conducted by a research aircraft to evaluate the performance of a wind farm parameterization (WFP) in a mesoscale model during stably-stratified atmospheric conditions, in which the wake is expected to be the strongest. The observations were conducted on the 10 September 2016 within the project WIPAFF (Wind PArk Far Field) at the North Sea. The observations allow evaluation of both the horizontal and the vertical dimensions of the wake. The model simulates the length and most of the time the spatial dimensions of the wake. Further, we show that the largest potential for improving the performance of the WFP is rooted in an improvement of the background flow. This is due to the fact that the mesoscale model has problems representing the atmospheric boundary layer in the transition between land to open sea.
The atmospheric boundary layer experiences multiple changes in coastal regions, especially with wind directions from land towards the sea, where the wind speed usually increases due to the smaller ...roughness of the ocean surface. These effects are of particular relevance for offshore wind energy utilization; they are summarized under the term coastal effects. This paper provides an overview of coastal effects and their potential impact on the operating conditions of offshore wind farms with a focus on the German Bight. Common numerical and experimental tools to study coastal effects and developing internal boundary layers (IBL) are introduced, and a review on the current state of research is given. The German Bight is an interesting example to illustrate impacts of coastal effects on offshore wind energy, because of the large number of wind turbines with a coastal distance of 100 km or less. Phenomena related to the stability of the boundary layer, like low level jets, are discussed. Spatial variations of vertical heat fluxes in the coastal zone related to variable water depths or Wadden Sea areas are analysed. The study illustrates that due to the increasing size of offshore wind farms, horizontal wind speed gradients caused by coastal effects can lead to significant wind variations within a single farm.Research topics which still need further attention are discussed in the framework of the rapidly developing wind energy sector with increasing wind turbine hub heights and rotor diameters as well as growing wind farm sizes. One example is the interaction of coastal effects with offshore wind farm wakes. The necessity to consider a large spectrum of spatial and temporal scales to understand and describe coastal effects is highlighted. We summarize modelling and observation tools, which are suitable for the investigation and prediction of the boundary layer dynamics in coastal areas. Existing applications and results are described based on several examples with collocated observation and model results obtained in the X‑Wakes project. The study puts particular focus on the large potential provided by the combination of different measurements and modelling techniques and gives recommendations for future developments of integrated approaches including the formulation of priorities.
More than 12 GW of offshore wind turbines are currently in operation in European waters. To optimise the use of the marine areas, wind farms are typically clustered in units of several hundred ...turbines. Understanding wakes of wind farms, which is the region of momentum and energy deficit downwind, is important for optimising the wind farm layouts and operation to minimize costs. While in most weather situations (unstable atmospheric stratification), the wakes of wind turbines are only a local effect within the wind farm, satellite imagery reveals wind-farm wakes to be several tens of kilometres in length under certain conditions (stable atmospheric stratification), which is also predicted by numerical models. The first direct in situ measurements of the existence and shape of large wind farm wakes by a specially equipped research aircraft in 2016 and 2017 confirm wake lengths of more than tens of kilometres under stable atmospheric conditions, with maximum wind speed deficits of 40%, and enhanced turbulence. These measurements were the first step in a large research project to describe and understand the physics of large offshore wakes using direct measurements, together with the assessment of satellite imagery and models.
Sea surface measurements are mainly gathered using satellite altimeter, buoy, and platform measurements. Satellite measurements typically have a coarse spatial resolution and need recalibration in ...coastal regions, whereas point measurements of buoys only represent limited areas around the measurement point because of the complex coastal bathymetry. Wave models (WAM) are used to expand the sparse observations in space and time. As a part of the project WIndPArk far-field (WIPAFF), which focused on wakes behind offshore wind farms, extensive airborne light detection and ranging (LiDAR) measurements of ocean waves in the German Bight were performed for more than 90 h. The LiDAR data processed for significant wave height can be used to validate and improve WAM models for complex areas and fill the observation gap between satellite altimeter and point measurements. This creates a detailed picture of the sea surface for coastal engineering and environmental applications. After introducing the measurement techniques and the data situation, intercomparisons between the available airborne measurements, buoy data, and WAM model output are presented to provide an insight into the potential of airborne LiDAR measurements for wave characterization and wave model validation.
We present an analysis of wind measurements from a series of airborne campaigns conducted to sample the wakes from two North Sea wind farm clusters, with the aim of determining the dependence of the ...downstream wind speed recovery on the atmospheric stability. The consequences of the stability dependence of wake length on the expected annual energy yield of wind farms in the North Sea are assessed by an engineering model. Wakes are found to extend for significantly longer downstream distances (>50 km) in stable conditions than in neutral and unstable conditions (
< 15 km). The parameters of one common engineering model are modified to reproduce the observed wake decay at downstream distances
> 30 km. More significant effects on the energy yield are expected for wind farms separated by distances
< 30 km, which is generally the case in the North Sea, but additional data would be required to validate the suggested parameter modifications within the engineering model. A case study is accordingly performed to show reductions in the farm efficiency downstream of a wind farm. These results emphasize not only the importance of understanding the impact of atmospheric stability on offshore wind farms but also the need to update the representation of wakes in current industry models to properly include wake‐induced energy losses, especially in large offshore clusters.
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