Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Peña, Alfredo; Floors, Rogier; Sathe, Ameya; Gryning, Sven‐Erik; Wagner, Rozenn; Courtney, Michael; Larsén, Xiaoli Guo; Hahmann, Andrea N.; Hasager, Charlotte Bay

doi:10.1007/s10546-015-0079-8

Cited by 100 publications

(112 citation statements)

References 63 publications

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“…The 116-m tall meteorological mast, part of the Danish National Test Station of wind turbines, is situated in a coastal rural farmland area in Jutland, consisting of grassland (Peña et al 2015a). The mast (56 • 26 26.0 N; 08 • 09 03.1 E) is located 1.8 km east of the North Sea coastline and 200 m south of the closest wind-turbine stand.…”

Section: Høvsøre (Both Land and Coastal)mentioning

confidence: 99%

Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

Gryning

Floors

Peña

et al. 2015

Boundary-Layer Meteorol

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Wind-speed observations from tall towers are used in combination with observations up to 600 m in altitude from a Doppler wind lidar to study the long-term conditions over suburban (Hamburg), rural coastal (Høvsøre) and marine (FINO3) sites. The variability in the wind field among the sites is expressed in terms of mean wind speed and Weibull distribution shape-parameter profiles. The consequences of the carrier-to-noise-ratio (CNR) threshold-value choice on the wind-lidar observations are revealed as follows. When the wind-lidar CNR is lower than a prescribed threshold value, the observations are often filtered out as the uncertainty in the wind-speed measurements increases. For a pulsed heterodyne Doppler lidar, use of the traditional -22 dB CNR threshold value at all measuring levels up to 600 m results in a ≈7 % overestimation in the long-term mean wind speed over land, and a ≈12 % overestimation in coastal and marine environments. In addition, the height of the profile maximum of the shape parameter of the Weibull distribution (so-called reversal height) is found to depend on the applied CNR threshold; it is found to be lower at small CNR threshold values. The reversal height is greater in the suburban (high roughness) than in the rural (low roughness) area. In coastal areas the reversal height is lower than that over land and relates to the internal boundary layer that develops downwind from the coastline. Over the sea the shape parameter increases towards the sea surface. A parametrization of the vertical profile of the shape parameter fits well with observations over land, coastal regions and over the sea. An applied model for the dependence of the reversal height on the surface roughness is in good agreement with the observations over land.

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Section: Høvsøre (Both Land and Coastal)mentioning

confidence: 99%

Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

Gryning

Floors

Peña

et al. 2015

Boundary-Layer Meteorol

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“…The prevailing wind direction is west. In Jutland, such western winds often feature high speeds (Peña et al, 2016).…”

Section: Terrain Climate and Wind Farmmentioning

confidence: 99%

Wind field reconstruction from nacelle-mounted lidar short-range measurements

et al. 2017

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Abstract. Profiling nacelle lidars probe the wind at several heights and several distances upstream of the rotor. The development of such lidar systems is relatively recent, and it is still unclear how to condense the lidar raw measurements into useful wind field characteristics such as speed, direction, vertical and longitudinal gradients (wind shear). In this paper, we demonstrate an innovative method to estimate wind field characteristics using nacelle lidar measurements taken within the induction zone. Model-fitting wind field reconstruction techniques are applied to nacelle lidar measurements taken at multiple distances close to the rotor, where a wind model is combined with a simple induction model. The method allows robust determination of free-stream wind characteristics. The method was applied to experimental data obtained with two different types of nacelle lidar (five-beam Demonstrator and ZephIR Dual Mode). The reconstructed wind speed was within 0.5 % of the wind speed measured with a mast-top-mounted cup anemometer at 2.5 rotor diameters upstream of the turbine. The technique described in this paper overcomes measurement range limitations of the currently available nacelle lidar technology.

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“…DTU has a test center for tall wind turbines at Høvsøre including a 116.5 m tall meteorological mast equipped with cup anemometers, wind vanes, sonic anemometers and temperature measurements [37]. It is located 6 km south of the central scanning LiDAR position SC (position H in Figure 1).…”

Section: Meteorological Mastmentioning

confidence: 99%

Validation of Sentinel-1A SAR Coastal Wind Speeds Against Scanning LiDAR

Ahsbahs¹,

Badger²,

Karagali³

et al. 2017

Remote Sensing

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High-accuracy wind data for coastal regions is needed today, e.g., for the assessment of wind resources. Synthetic Aperture Radar (SAR) is the only satellite borne sensor that has enough resolution to resolve wind speeds closer than 10 km to shore but the Geophysical Model Functions (GMF) used for SAR wind retrieval are not fully validated here. Ground based scanning light detection and ranging (LiDAR) offer high horizontal resolution wind velocity measurements with high accuracy, also in the coastal zone. This study, for the first time, examines accuracies of SAR wind retrievals at 10 m height with respect to the distance to shore by validation against scanning LiDARs. Comparison of 15 Sentinel-1A wind retrievals using the GMF called C-band model 5.N (CMOD5.N) versus LiDARs show good agreement. It is found, when nondimenionalising with a reference point, that wind speed reductions are between 4% and 8% from 3 km to 1 km from shore. Findings indicate that SAR wind retrievals give reliable wind speed measurements as close as 1 km to the shore. Comparisons of SAR winds versus two different LiDAR configurations yield root mean square error (RMSE) of 1.31 ms −1 and 1.42 ms −1 for spatially averaged wind speeds.

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Ten Years of Boundary-Layer and Wind-Power Meteorology at Høvsøre, Denmark

Cited by 100 publications

References 63 publications

Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

Weibull Wind-Speed Distribution Parameters Derived from a Combination of Wind-Lidar and Tall-Mast Measurements Over Land, Coastal and Marine Sites

Wind field reconstruction from nacelle-mounted lidar short-range measurements

Validation of Sentinel-1A SAR Coastal Wind Speeds Against Scanning LiDAR

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