Ten Years of Meteorological Measurements for Offshore Wind Farms

Barthelmie, R.J.; Hansen, O.F.; Enevoldsen, Karen; Højstrup, Jørgen; Frandsen, Sten Tronæs; Pryor, Sara C.; Larsen, Søren Ejling; Motta, Maurizio; Sanderhoff, P.

doi:10.1115/1.1850489

Cited by 66 publications

(63 citation statements)

References 13 publications

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“…Further, it is important to note that offshore wind farms typically operate at upstream turbulence intensity (TI) levels of 5-8%, in between the limit cases of uniform (TI = 0%) and turbulent inflow (TI = 8%) considered here [66,67]. Moreover, it was already mentioned that in stably stratified boundary layers, turbulence levels are further reduced and wake meandering is suppressed [57,58].…”

Section: Discussionmentioning

confidence: 99%

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

2018

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Abstract:In wind farms, wakes originating from upstream turbines cause reduced energy extraction and increased loading variability in downstream rows. The prospect of mitigating these detrimental effects through coordinated controllers at the wind-farm level has fueled a multitude of research efforts in wind-farm control. The main strategies in wind-farm control are to influence the velocity deficits in the wake by deviating from locally optimal axial induction setpoints on the one hand, and steering wakes away from downstream rows through yaw misalignment on the other hand. The current work investigates dynamic induction and yaw control of individual turbines for wind-farm power maximization in large-eddy simulations. To this end, receding-horizon optimal control techniques combined with continuous adjoint gradient evaluations are used. We study a 4 × 4 aligned wind farm, and find that for this farm layout yaw control is more effective than induction control, both for uniform and turbulent inflow conditions. Analysis of optimal yaw controls leads to the definition of two simplified yaw control strategies, in which wake meandering and wake redirection are exploited respectively. Furthermore it is found that dynamic yawing provides significant benefits over static yaw control in turbulent flow environments, whereas this is not the case for uniform inflow. Finally, the potential of combining overinductive axial induction control with yaw control is shown, with power gains that approximate the sum of those achieved by each control strategy separately.

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Section: Discussionmentioning

confidence: 99%

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

2018

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“…Such masts include the 62 m mast at Rødsand in the Baltic Sea (Barthelmie et al 2005), several tall masts at Horns Rev (Tambke et al 2005) as well as the 100 m FINO-1 platform (Neumann et al 2006) in the North Sea. In their analysis of the measurements from Rødsand, Lange et al (2004a, b) found that even with a fetch as long as 30 km, the wind profile was a superposition of both land and sea profiles, and could not be adequately modelled by the Monin-Obukhov similarity theory.…”

Section: Introductionmentioning

confidence: 99%

Charnock’s Roughness Length Model and Non-dimensional Wind Profiles Over the Sea

Peña

Gryning

2008

Boundary-Layer Meteorol

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An analysis tool for the study of wind speed profiles over the water has been developed. The profiles are analysed using a modified dimensionless wind speed and dimensionless height, assuming that the sea surface roughness can be predicted by Charnock's roughness length model. In this form, the roughness dependency on wind speed is extracted and the variations on the wind profile are due solely to atmospheric stability. The use of the Charnock's non-dimensional wind profile is illustrated using data collected from a meteorological mast installed in the Danish North Sea. The best fit with the observed mean nondimensional wind profile under neutral atmospheric conditions is found using a value of 1.2 × 10 −2 for Charnock's parameter. The stability correction on the neutral wind profile suggested by the Businger-Dyer relations was found to perform well over the sea.

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“…It is remarkable that the apparent seasonality is very weak, and the fluctuations are huge in spite of the smoothing by a wide window of 1 week. The average load factor or capacity factor ͑the ratio of mean and rated output powers͒ around 21%-22% is considerably lower than at optimal off-shore sites, [27][28][29] in contempt of the geographic location of turbines belonging to the windiest region of Hungary. [30][31][32][33][34] The standard method for estimating wind power from wind speed data is based on the empirical power curve 35,36 provided by the producers ͑see the power curves, e.g., http:// www.enercon.de, http://www.nordex-online.com, http://www.vestas.com͒.…”

Section: -3mentioning

confidence: 96%

Comparison of wind power estimates from the ECMWF reanalyses with direct turbine measurements

Kiss

Varga²,

Jánosi

2009

Journal of Renewable and Sustainable Energy

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Reanalysis data are rarely used for wind power estimates because of the limited spatial and temporal resolution. Here we report on a detailed comparison of wind speed and electric power time series recorded at a continental location in Hungary and estimates provided by the European Centre for Medium-Range Weather Forecasts ͑ECMWF͒ ERA-40 and Interim databases at nearby grid points. The results show that the temporal behavior is adequately represented in reanalysis records with damped magnitudes, as expected. However, characteristic shape differences in the wind speed histograms for turbine measurements and reanalysis hinder a perfect match of statistics. A satisfying agreement of histograms for measured and modeled output powers is achieved by scaling up surface wind speeds to have the same long time average value as for the turbine records. The presented calibration permits us to provide wind power estimates for large geographic areas, where the wind field is similarly coherent as around the test site.

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Ten Years of Meteorological Measurements for Offshore Wind Farms

Cited by 66 publications

References 13 publications

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

Dynamic Strategies for Yaw and Induction Control of Wind Farms Based on Large-Eddy Simulation and Optimization

Charnock’s Roughness Length Model and Non-dimensional Wind Profiles Over the Sea

Comparison of wind power estimates from the ECMWF reanalyses with direct turbine measurements

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