A Numerically Efficient Parametrization of Turbulent Wind-Turbine Flows for Different Thermal Stratifications

Englberger, Antonia; Dörnbrack, Andreas

doi:10.1007/s10546-018-0377-z

Cited by 10 publications

(10 citation statements)

References 42 publications

(66 reference statements)

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“…It would be worthwhile to include a low-level jet case as standard inflow field for wake and load simulations. Recent papers have developed affordable methods to provide realistic inflow fields (Gebraad et al, 2014;Englberger and Dörnbrack, 2018). Expensive computational fluid dynamics (CFD) simulations have been used to derive parameterisations to generate realistic inflow fields for wind farm simulations.…”

Section: Discussionmentioning

confidence: 99%

Low-level jets over the North Sea based on ERA5 and observations: together they do better

et al. 2019

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Abstract. Ten years of ERA5 reanalysis data are combined with met-mast and lidar observations from 10 offshore platforms to investigate low-level jet characteristics over the Dutch North Sea. The objective of this study is to combine the best of two worlds: (1) ERA5 data with a large spatiotemporal extent but inherent accuracy limitations due to a relatively coarse grid and an incomplete representation of physical processes and (2) observations that provide more reliable estimates of the measured quantity but are limited in both space and time. We demonstrate the effect of time and range limitations on the reconstructed wind climate, with special attention paid to the impact on low-level jets. For both measurement and model data, the representation of wind speed is biased. The limited temporal extent of observations leads to a wind speed bias on the order of ±1 m s−1 as compared to the long-term mean. In part due to data-assimilation strategies that cause abrupt discontinuities in the diurnal cycle, ERA5 also exhibits a wind speed bias of approximately 0.5 m s−1. The representation of low-level jets in ERA5 is poor in terms of a one-to-one correspondence, and the jets appear vertically displaced (“smeared out”). However, climatological characteristics such as the shape of the seasonal cycle and the affinity with certain circulation patterns are represented quite well, albeit with different magnitudes. We therefore experiment with various methods to adjust the modelled low-level jet rate to the observations or, vice versa, to correct for the erratic nature of the short observation periods using long-term ERA5 information. While quantitative uncertainty is still quite large, the presented results provide valuable insight into North Sea low-level jet characteristics. These jets occur predominantly for circulation types with an easterly component, with a clear peak in spring, and are concentrated along the coasts at heights between 50 and 200 m. Further, it is demonstrated that these characteristics can be used as predictors to infer the observed low-level jet rate from ERA5 data with reasonable accuracy.

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Section: Discussionmentioning

confidence: 99%

Low-level jets over the North Sea based on ERA5 and observations: together they do better

et al. 2019

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show abstract

“…It would be worthwhile to include a low-level jet case as standard inflow field for wake and load simulations. Recent papers have developed affordable methods to provide realistic inflow fields (Gebraad et al, 2014;Englberger and Dörnbrack, 2018). Expensive CFD simulations have been used to derive parameter-15 izations to generate realistic inflow fields for wind farm simulations.…”

mentioning

confidence: 99%

Low-level jets over the North Sea based on ERA5 and observations: together they do better

Kalverla¹,

Steeneveld²,

Holtslag³

2019

Preprint

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Abstract. Ten years of ERA5 reanalysis data are combined with met-mast and LiDAR observations from ten offshore platforms to investigate low-level jet characteristics over the Dutch North Sea. The objective of this study is to combine the best of two worlds: (1) ERA5 data with large spatiotemporal extent but inherent accuracy limitations due to a relatively coarse grid and an incomplete representation of physical processes, and (2) observations that provide more reliable estimates of the measured quantity, but are limited in both space and time. We demonstrate the effect of time and range limitations on the reconstructed wind climate, with special attention paid to the impact on low-level jets. For both measurement and model data, the representation of wind speed is biased. The limited temporal extent of observations leads to a wind speed bias on the order of 1 m s−1. In part due to data-assimilation strategies that cause abrupt discontinuities in the diurnal cycle, ERA5 also exhibits a wind speed bias of approximately 0.5 m s−1. Representation of low-level jets in ERA5 is poor in terms of a one-to-one correspondence, and the jets appear vertically displaced (`smeared out'). However, climatological characteristics such as the shape of the seasonal cycle and the affinity with certain circulation patterns are represented quite well, albeit with different magnitudes. We therefore experiment with various methods to adjust modelled low-level jet rate to the observations or, vice versa, to correct for the erratic nature of the short observation periods using long-term ERA5 information. While quantitative uncertainty is still quite large, the presented results provide valuable insight into North Sea low-level jet characteristics. These jets occur predominantly for circulation types with an easterly component, with a clear peak in spring, and concentrate along the coasts at heights between 50–200 m. Further, it is demonstrated that these characteristics can be used as predictors to infer the observed low-level jet rate from ERA5 data with reasonable accuracy.

show abstract

“…It would be worthwhile to include a low-level jet case as standard inflow field for wake and load simulations. Recent papers have developed affordable methods to provide realistic inflow fields (Gebraad et al, 2014;Englberger and Dörnbrack, 2018). Expensive CFD simulations have been used to derive parametrizations to generate realistic inflow fields for wind farm simulations.…”

Section: Discussionmentioning

confidence: 99%

“…Simpler representations of the wake can be validated and tuned with high-resolution simulations, though. Englberger and Dörnbrack (2018), for example, designed a cheap method to derive realistic turbulent inflow fields, from a small number of expensive simulations. Kanev et al (2018) combine a database of structural loads obtained from a relatively limited number of expensive simulations with a cheaper model for wind farm optimization.…”

Section: Engineering Models: From Power Formula To Digital Twinsmentioning

confidence: 99%

“…Parametrizations in the coarser models are being improved by learning from the detailed simulations, and detailed simulations in turn are fed with more sophisticated/realistic inflow from the coarser models (e.g. Englberger and Dörnbrack, 2018). Extrapolating this trend into the future suggests the wind energy sector will increasingly realize the vision of true digital twins (Boschert and Rosen, 2016): virtual replicas of physical objects or systems that emulate the functioning of their real counterparts, to be used for advanced planning, monitoring, and real-time optimization.…”

Section: Chaptermentioning

confidence: 99%

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Characterisation of offshore winds for energy applications

Kalverla

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Offshore wind energy is regarded as one of the main ingredients of a sustainable energy system. A popular scenario for 2050 describes a stunning fleet of twenty-five thousand wind turbines that is to be installed in the North Sea. Obviously, the realisation of such a grand vision requires realistic estimates of the expected energy production, optimal wind farm layouts, and lifetime of various turbine designs. A wide range of computer models is used to simulate, for example, the interaction between the wind and the turbines. As inputs, they require (climatological) information about the wind field. An inherent property of model simulations and associated predictions is that they come with uncertainties. There is always a chance that reality will deviate from the anticipated course. Since offshore wind projects require large investments, these uncertainties naturally transform into financial risks. Therefore, a growing interest emerges in uncertainty quantification and reduction. This thesis addresses uncertainties that originate from the representation of the offshore wind field in the aforementioned engineering models. This goal is partly achieved through crossvalidation between available observations, output from meteorological models, and combined products of observations and meteorological model simulations that are known as reanalysis datasets. Additionally, the thesis reflects on the impact of (over)simplifications that are commonly used to reduce computational demands. Standard inflow specifications for engineering models have been built around highly idealized descriptions of the wind, such as the Weibull distribution, the logarithmic wind profile, and the 'wind rose'. With the growth of individual wind turbines, offshore wind projects, and the corresponding investments, these simplified descriptions are becoming inadequate. Moreover, contemporary design standards consider conditions of extreme winds, extreme shear, wind gusts, etcetera in an abstract statistical fashion that does not reflect the physical nature of these events. Chapter 1 further elaborates on the different models, data sources, assumptions and simplifications, and uncertainties.

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A Numerically Efficient Parametrization of Turbulent Wind-Turbine Flows for Different Thermal Stratifications

Cited by 10 publications

References 42 publications

Low-level jets over the North Sea based on ERA5 and observations: together they do better

Low-level jets over the North Sea based on ERA5 and observations: together they do better

Low-level jets over the North Sea based on ERA5 and observations: together they do better

Characterisation of offshore winds for energy applications

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