The northeastern coast of the U.S. is projected to expand its offshore wind capacity from the existing 30 MW to over 22 GW in the next decade. Yet, only a few wind measurements are available in the region and none at hub height, thus extrapolations are needed to estimate wind speed as a function of height. A common method is the log-law, which is based on surface roughness length (z0). No reliable estimates of z0 for the region have been presented in the literature. Here, we fill this knowledge gap using two field campaigns that were conducted in the Nantucket Sound at the Cape Wind (CW) platform. We tested three different methods to calculate z0: 1) analytical, dependent on friction velocity u* and a stability function psi; 2) the Charnock relationship between z0 and u*; and 3) a statistical method based on wind speed observed at the three levels. The first two methods are physical, whereas the statistical method is purely mathematical. Comparing mean and median of z0, we find that the median is a more robust statistics. In general, the median z0 exhibits little seasonal variability and a weak dependency on atmospheric stability, which was predominantly unstable (54-67%). The statistical method, despite delivering unrealistic z0 values at times, gives the best estimates of 60-m winds. The unrealistic z0 values are caused by non-monotonic wind speed profiles, occurring about 41% of the time, and should not be rejected because they produce realistic fits. In summary, if wind speed data from multiple levels are available, the statistical method is recommended. If multi-level wind speeds are not available but advanced sonic anemometry is available at one level, the analytical method is recommended over the Charnock's. If a constant value of z0 is sought after to characterize the region, we recommend the median from the statistical method, i.e., 6.09*10^(-3) m.
The rapid growth of offshore wind energy requires accurate modeling of the wind resource, which can be depleted by wind farm wakes. Turbulence dissipation rate governs the accuracy of model predictions of hub-height wind speed and the development and erosion of wakes. Here we assess the variability of turbulence kinetic energy and dissipation rate using 13 months of observations from a profiling lidar deployed on a platform off the Massachusetts coast. Offshore, turbulence dissipation rate is 2 orders of magnitude smaller than onshore, with a subtle diurnal cycle. Wind direction largely influe…
Offshore wind energy development is underway in the U.S., with proposed sites located in hurricane-prone regions. Turbine design criteria outlined by the International Electrotechnical Commission do not encompass the extreme wind speeds and directional shifts of hurricanes stronger than a Category 2. We examine the most turbulent portion of a hurricane (the eyewall) using large-eddy simulations with Cloud Model 1 (CM1). Gusts and mean wind speeds near the eyewall exceed the current design threshold of 50 m s-1 mean wind and 70 m s-1 gusts for Class I turbines. Gust factors are greatest at the …
The offshore wind energy sector has rapidly expanded over the past two decades, providing a renewable energy solution for coastal nations. Sector development has been led in Europe, but is growing globally. Most developments to date have been in well-mixed, i.e. unstratified, shallow-waters near to shore. Sector growth is, for the first time, pushing developments to deep water, into a brand new environment: seasonally stratified shelf seas. Seasonally stratified shelf seas, where water density varies with depth, have a disproportionately key role in primary production, marine ecosystem and bio…
Recently it was demonstrated how climate data can be utilized to estimate regional wind power densities. In particular it was shown that the quality of the global scale estimate compared well with regional high resolution studies and a link between surface temperature and moist density in the estimate was presented. In the present paper the methodology is tested further, to ensure that the results using one climate data set are reliable. This is achieved by extending the study to include four ensemble members. With the confidence that one instantiation is sufficient a climate change data set, …
We present here a computational fluid dynamics (CFD) simulation of Lillgrund offshore wind farm, which is located in the Oresund Strait between Sweden and Denmark. The simulation combines a dynamic representation of wind turbines embedded within a Large-Eddy Simulation CFD solver, and uses hr-adaptive meshing to increase or decrease mesh resolution where required. This allows the resolution of both large scale flow structures around the wind farm, and local flow conditions at individual turbines; consequently, the response of each turbine to local conditions can be modelled, as well as the res…
Ton Duc Thang University（同德堂大学）；Oxford Brookes University（牛津布鲁克斯大学）；Duy Tan University（duy tan大学）；Hong Kong Polytechnic University（香港理工大学）
This study explores wind energy resources in different locations through the Gulf of Oman and also their future variability due climate change impacts. In this regard, EC-EARTH near surface wind outputs obtained from CORDEX-MENA simulations are used for historical and future projection of the energy. The ERA5 wind data are employed to assess suitability of the climate model. Moreover, the ERA5 wave data over the study area are applied to compute sea surface roughness as an important variable for converting near surface wind speeds to those of wind speed at turbine hub-height. Considering the p…
Can satellite data be used to address challenges currently faced by the Offshore Renewable Energy (ORE) sector? What benefit can satellite observations bring to resource assessment and maintenance of ORE farms? Can satellite observations be used to assess the environmental impact of offshore renewables leading towards a more sustainable ORE sector? This review paper faces these questions presenting a holistic view of the current interactions between satellite and ORE sectors, and future needs to make this partnerships grow. The aim of the work is to start the conversation between these sectors…
The kinematics of offshore wind turbines are of great importance when installing the turbines, as the motions of the components during craning operations are a limiting factor. Most critical is the installation of the blades: the blade's bolts need to be inserted into the rotor flange, an operation that requires great precision. Both the blade and the turbine undergo environmental loading, leading to relative motions between the blade root and the hub during installation. Results from an offshore wind farm installation measurement campaign showed, that the partially installed turbines show int…
The wind blows stronger and more reliably over the sea than over land. Thus, offshore wind energy is expected to make a major contribution to the energy transition in Germany, especially in the German Bight. But what happens when a growing number of wind farms extract more and more wind energy from the atmosphere?
We present an analytical model of aeolian sand transport. The model quantifies the momentum transfer from the wind to the transported sand by providing expressions for the thickness of the saltation layer and the apparent surface roughness. These expressions are derived from basic physical principles and a small number of assumptions. The model further predicts the sand transport rate (mass flux) and the impact threshold (the smallest value of the wind shear velocity at which saltation can be sustained). We show that, in contrast to previous studies, the present model's predictions are in very…
Adjusting ocean wind observations to a standard height, usually 10 m, requires the use of a boundary layer model, and knowledge of the thermodynamical variables. Height adjustment is complicated by the fact that a necessary parameter, the roughness height, cannot be given in a closed form solution. If only the wind and reporting height are known, the best that can be done is to assume neutral stability. The determination of roughness height is analyzed and a simple approximation (used by Atlas et al. 2011) is derived in detail. This approximation is accurate for winds in the range of 1 - 30 m/…
In the design process of marine structures like offshore wind turbines the long-term distribution of significant wave height needs to be modelled to estimate loads. This is typically done by fitting a translated Weibull distribution to wave data. However, the translated Weibull distribution often fits well at typical values, but poorly at high wave heights such that extreme loads are underestimated. Here, we analyzed wave datasets from six locations suitable for offshore wind turbines. We found that the exponentiated Weibull distribution provides better overall fit to these wave data than the …
