Mesoscale modeling of coastal low-level jets: implications for offshore wind resource estimation

Wind Energy ◽  
2013 ◽  
Vol 17 (8) ◽  
pp. 1199-1216 ◽  
Author(s):  
Christopher G. Nunalee ◽  
Sukanta Basu
Keyword(s):  
Mesoscale Modeling ◽  
Offshore Wind ◽  
Resource Estimation ◽  
Low Level ◽  
Low Level Jets ◽  
Wind Resource

scholarly journals Looking for an Offshore Low-Level Jet Champion among Recent Reanalyses: A Tight Race over the Baltic Sea

Energies ◽  
2020 ◽  
Vol 13 (14) ◽  
pp. 3670
Author(s):  
Christoffer Hallgren ◽  
Johan Arnqvist ◽  
Stefan Ivanell ◽  
Heiner Körnich ◽  
Ville Vakkari ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Wind Farms ◽  
Resource Assessment ◽  
Offshore Wind ◽  
The Baltic Sea ◽  
Average Wind Speed ◽  
Low Level ◽  
Wide Range ◽  
Low Level Jets ◽  
The Baltic

With an increasing interest in offshore wind energy, focus has been directed towards large semi-enclosed basins such as the Baltic Sea as potential sites to set up wind turbines. The meteorology of this inland sea in particular is strongly affected by the surrounding land, creating mesoscale conditions that are important to take into consideration when planning for new wind farms. This paper presents a comparison between data from four state-of-the-art reanalyses (MERRA2, ERA5, UERRA, NEWA) and observations from LiDAR. The comparison is made for four sites in the Baltic Sea with wind profiles up to 300 m. The findings provide insight into the accuracy of reanalyses for wind resource assessment. In general, the reanalyses underestimate the average wind speed. The average shear is too low in NEWA, while ERA5 and UERRA predominantly overestimate the shear. MERRA2 suffers from insufficient vertical resolution, which limits its usefulness in evaluating the wind profile. It is also shown that low-level jets, a very frequent mesoscale phenomenon in the Baltic Sea during late spring, can appear in a wide range of wind speeds. The observed frequency of low-level jets is best captured by UERRA. In terms of general wind characteristics, ERA5, UERRA, and NEWA are similar, and the best choice depends on the application.

Advances in Offshore Wind Resource Estimation

2011 ◽  
pp. 85-106
Author(s):  
Charlotte Bay Hasager ◽  
Merete Bruun Badger ◽  
Alfredo Peña ◽  
Jake Badger ◽  
Ioannis Antoniou ◽  
...  
Keyword(s):  
Offshore Wind ◽  
Resource Estimation ◽  
Wind Resource

scholarly journals Quality of wind characteristics in recent wind atlases over the North Sea

2020 ◽  
Author(s):  
Peter C. Kalverla ◽  
Albert A. M. Holtslag ◽  
Reinder J. Ronda ◽  
Gert-Jan Steeneveld
Keyword(s):  
North Sea ◽  
Offshore Wind ◽  
Alternative Methods ◽  
Low Level ◽  
The North ◽  
Engineering Models ◽  
The North Sea ◽  
Wind Climate ◽  
Low Level Jets ◽  
Low Level Jet

<p>Many wind energy applications rely on engineering models that simulate the interaction between the wind and the turbine(s). These models often represent the wind in an idealised fashion, which introduces uncertainties that translate into financial risk for investors.</p><p>Over the past four years, we investigated these uncertainties by re-evaluating common assumptions about the (offshore) wind field, studying the physics that govern winds in coastal areas, evaluating the representation of offshore winds in weather models, and proposing alternative methods to represent the offshore wind climate in engineering models.</p><p>Uncertainties in the wind climate were studied through a number of ‘anomalous wind events’. An important and illustrative example is the low-level jet, which can substantially impact power production and wind loads on the turbine. We found that low-level jets occur often over the North Sea. Moreover, numerical weather prediction models struggle to adequately represent this phenomenon. A climatology based only on observations is also biased, because the observations are limited in time and space. Thus, we combined field observations with output of reanalysis products to obtain a reliable climatology.</p><p>At the 2020 general assembly, we will present a new evaluation of three recent wind atlases over the North Sea: ERA5, The New European Wind Atlas (NEWA), and the Dutch Offshore Wind Atals (DOWA). With virtually no bias, DOWA outperforms the other datasets in terms of the mean wind profile and also in the representation of wind shear. The high resolution offered by DOWA (2.5 km) and NEWA (3 km) leads to substantial improvements in the frequency and the level of detail with which low-level jets are captured. However, the timing of the events is a bit off in NEWA. By contrast, DOWA was produced using continuous three-hourly data-assimilation updates, which imposes a much stronger constraint on the simulations. Consequently, the timing of low-level jets in DOWA is much better represented. This makes for a low-level jet climatology with unprecedented accuracy and detail, facilitating resource assessment and future studies on the characteristics of the offshore wind climate.</p>

scholarly journals Occurrence of Low-Level Jets over the Eastern U.S. Coastal Zone at Heights Relevant to Wind Energy

Energies ◽  
2022 ◽  
Vol 15 (2) ◽  
pp. 445
Author(s):  
Jeanie A. Aird ◽  
Rebecca J. Barthelmie ◽  
Tristan J. Shepherd ◽  
Sara C. Pryor
Keyword(s):  
Wind Energy ◽  
Wind Turbine ◽  
Coastal Zone ◽  
East Coast ◽  
Wrf Model ◽  
Offshore Wind ◽  
Low Level ◽  
Wind Speeds ◽  
Low Level Jets ◽  
The U.S

Two years of high-resolution simulations conducted with the Weather Research and Forecasting (WRF) model are used to characterize the frequency, intensity and height of low-level jets (LLJ) over the U.S. Atlantic coastal zone. Meteorological conditions and the occurrence and characteristics of LLJs are described for (i) the centroids of thirteen of the sixteen active offshore wind energy lease areas off the U.S. east coast and (ii) along two transects extending east from the U.S. coastline across the northern lease areas (LA). Flow close to the nominal hub-height of wind turbines is predominantly northwesterly and southwesterly and exhibits pronounced seasonality, with highest wind speeds in November, and lowest wind speeds in June. LLJs diagnosed using vertical profiles of modeled wind speeds from approximately 20 to 530 m above sea level exhibit highest frequency in LA south of Massachusetts, where LLJs are identified in up to 12% of hours in June. LLJs are considerably less frequent further south along the U.S. east coast and outside of the summer season. LLJs frequently occur at heights that intersect the wind turbine rotor plane, and at wind speeds within typical wind turbine operating ranges. LLJs are most frequent, intense and have lowest core heights under strong horizontal temperature gradients and lower planetary boundary layer heights.

scholarly journals Classification and properties of coastal wind profiles with negative gradients – an observational study

2022 ◽  
Author(s):  
Christoffer Hallgren ◽  
Johan Arnqvist ◽  
Erik Nilsson ◽  
Stefan Ivanell ◽  
Metodija Shapkalijevski ◽  
...  
Keyword(s):  
Baltic Sea ◽  
Local Minimum ◽  
Stable Stratification ◽  
Offshore Wind ◽  
The Baltic Sea ◽  
Wind Maximum ◽  
Low Level ◽  
Low Level Jets ◽  
Wind Profiles ◽  
The Baltic

Abstract. Wind profiles with a negative gradient are frequently occurring over the Baltic Sea and are important to take into consideration for offshore wind power as they affect not only the power production, but also the loads on the structure and the behavior of the wake behind the turbine. In this study, we classified non-normal profiles as wind profiles having negative shear in at least one part of the profile between 28 and 300 m: low-level jets (with a local wind maximum in the profile), profiles with a local minimum, and negative profiles. Using observations spanning over 3 years, we show that the non-normal wind profiles are common over the Baltic Sea in late spring and summer, with a peak of 40 % relative occurrence in May. Negative profiles (in the 28–300 m layer) were mostly occurring during unstable conditions, in contrast to low-level jets that primarily occurred in stable stratification. There were indications that the the zone with strong shear during low-level jets could cause a relative suppression of the variance for large turbulent eddies compared to the peak of the velocity spectra, in the layer below the jet core. Swell conditions were found to be favourable for the occurrence of negative profiles and profiles with a local minimum, as the waves fed energy into the surface layer, resulting in an increase of the wind speed from below.

Offshore wind resource estimation from satellite SAR wind field maps

Wind Energy ◽  
2005 ◽  
Vol 8 (4) ◽  
pp. 403-419 ◽  
Author(s):  
C. B. Hasager ◽  
M. Nielsen ◽  
P. Astrup ◽  
R. Barthelmie ◽  
E. Dellwik ◽  
...  
Keyword(s):  
Wind Field ◽  
Offshore Wind ◽  
Resource Estimation ◽  
Wind Resource

A hybrid solution for offshore wind resource assessment from limited onshore measurements

2021 ◽  
Vol 298 ◽  
pp. 117245
Author(s):  
Basem Elshafei ◽  
Alfredo Peña ◽  
Dong Xu ◽  
Jie Ren ◽  
Jake Badger ◽  
...  
Keyword(s):  
Resource Assessment ◽  
Offshore Wind ◽  
Wind Resource Assessment ◽  
Hybrid Solution ◽  
Wind Resource

scholarly journals A Climatology of Nocturnal Low-Level Jets at Cabauw

2009 ◽  
Vol 48 (8) ◽  
pp. 1627-1642 ◽  
Author(s):  
P. Baas ◽  
F. C. Bosveld ◽  
H. Klein Baltink ◽  
A. A. M. Holtslag
Keyword(s):  
Wind Speed ◽  
Ground Level ◽  
Geostrophic Wind ◽  
Stable Stratification ◽  
Radiative Cooling ◽  
Inertial Oscillation ◽  
Stable Boundary Layers ◽  
Above Ground Level ◽  
Low Level ◽  
Low Level Jets

Abstract A climatology of nocturnal low-level jets (LLJs) is presented for the topographically flat measurement site at Cabauw, the Netherlands. LLJ characteristics are derived from a 7-yr half-hourly database of wind speed profiles, obtained from the 200-m mast and a wind profiler. Many LLJs at Cabauw originate from an inertial oscillation, which develops after sunset in a layer decoupled from the surface by stable stratification. The data are classified to different types of stable boundary layers by using the geostrophic wind speed and the isothermal net radiative cooling as classification parameters. For each of these classes, LLJ characteristics like frequency of occurrence, height above ground level, and the turning of the wind vector across the boundary layer are determined. It is found that LLJs occur in about 20% of the nights, are typically situated at 140–260 m above ground level, and have a speed of 6–10 m s−1. Development of a substantial LLJ is most likely to occur for moderate geostrophic forcing and a high radiative cooling. A comparison with the 40-yr ECMWF Re-Analysis (ERA-40) is added to illustrate how the results can be used to evaluate the performance of atmospheric models.

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