Bringing satellite winds to hub-height
Downloaded from orbit.dtu.dk on: Dec 30, 2016 Bringing satellite winds to hub-height Badger, Merete; Pena Diaz, Alfredo; Bredesen, Rolv Erlend; Berge, Erik; Hahmann, Andrea N.; Badger, Jake; Karagali, Ioanna; Hasager, Charlotte Bay; Mikkelsen, Torben Krogh Published in: Proceedings of EWEA 2012 - European Wind Energy Conference & Exhibition Publication date: 2012 Document Version Publisher final version (usually the publisher pdf) Link to publication Citation (APA): Badger, M., Pena Diaz, A., Bredesen, R. E., Berge, E., Hahmann, A. N., Badger, J., ... Mikkelsen, T. (2012). Bringing satellite winds to hub-height. In Proceedings of EWEA 2012 - European Wind Energy Conference & Exhibition. European Wind Energy Association (EWEA). 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Bringing satellite winds to hub-height Merete Badger, DTU Wind Energy, Denmark Rolv Erlend Bredesen, Erik Berge Kjeller Vindteknikk, Norway Alfredo Peña, Andrea Hahmann, Jake Badger, Ioanna Karagali, Charlotte Hasager, Torben Mikkelsen DTU Wind Energy, Denmark Ocean wind fields from satellites Scatterometer Synthetic Aperture Radar (SAR) Wind speed and direction Wind speed Spatial resolution 0.25°lat/lon 500 m Spatial coverage Global Selected areas Up to 70 km from coastline None Temporal resolution Twice daily Variable – less than one per day Temporal coverage Systematically since 1991 ScanSAR since 1995 Current sensors ASCAT, OSCAT, HY2A, MetOp-B Envisat ASAR, Radarsat-1/2 Rain sensitivity High – rain flags provided Low Retrieved parameters Coastal mask 2 DTU Wind Energy, Technical University of Denmark 5/9/2012 Level of detail for scatterometer and SAR winds 3 QuikScat mean wind speed DTU Wind Energy, Technical University of Denmark Envisat ASAR mean wind5/9/2012 speed From radar backscatter to wind A geophysical model function is applied to retrieve 10-meter ocean winds from radar backscatter. 4 DTU Wind Energy, Technical University of Denmark 5/9/2012 Application 1: Wind resource mapping from SAR wind fields 5 DTU Wind Energy, Technical University of Denmark 5/9/2012 Application 2: Wind farm wake analyses and wake model validation Wind speed from ERS-2 SAR, February 25, 2003 From: Christiansen, M. B. & Hasager, C. B. 2005, Wake effects of large offshore wind farms identified 6 DTU Wind Energy, Technical University of Denmark 5/9/2012 from satellite SAR. Remote Sensing of Environment, 98, 251-268 Application 3: Characterizing mesoscale wind phenomena - and validation of mesoscale models Strait of Gibraltar 7 DTU Wind Energy, Technical University of Denmark The Azores 5/9/2012 Challenges for the application of SAR wind fields in offshore wind energy Challenge 1: Dealing with a limited number of samples See: Badger et al. 2010, Wind class sampling of satellite SAR imagery for offshore wind resource mapping. J. Appl. Meteor. Climat., 49, 2474-2491. Challenge 2: Bringing satellite winds from the 10-m vertical level to the hub-height of modern wind turbines - the topic of this presentation 8 DTU Wind Energy, Technical University of Denmark 5/9/2012 Recent advances - which make the lifting of SAR wind fields possible • A validated description of vertical wind profiles at high levels is available (Peña, A. et al. 2008, Measurements and Modelling of the Wind Speed Profile in the Marine Atmospheric Boundary Layer, Bound.-Layer Meteor., 129, pp. 479-495) • Wind retrieval algorithms can produce Equivalent Neutral Winds (ENW) (Hersbach, H. 2010, Comparison of C-band Scatterometer CMOD5.N Equivalent Neutral Winds with ECMWF, J. Atmos. Oceanic Technol., 27, pp. 721-736) • Satellite SAR imagery is available in larger quantities (500-1,000 overlapping scenes over sites in the European Seas) • Mesoscale modeling has been performed for significant areas and time periods • Offshore measurements are available for validation (masts and LiDAR) 9 DTU Wind Energy, Technical University of Denmark 5/9/2012 Bringing satellite winds to hub-height (100 m) • Friction velocity, u* from the satellite ENW: u 10 SAR u 10 = ∗ SAR ln κ z0 , u∗2SAR z0 = α c g • Obukhov length, L - using WRF parameters T2 and HFX: LWRF / SAR 10 − u∗3SAR T2WRF = g κ HFX WRF DTU Wind Energy, Technical University of Denmark LWRF/SAR > 0: stable LWRF/SAR ≤ 0: unstable 5/9/2012 Bringing satellite winds to hub-height (100 m) • Stability function, ψ(z/L): LWRF/SAR > 0 : ψ ( z LWRF / SAR LWRF/SAR ≤ 0 : ψ z L WRF / SAR ) = − 4.7 z LWRF / SAR 1/ 3 3 1+ x + x2 2x +1 π z − 3 arctan = ln + , x = 1 − 12 2 3 3 3 L WRF / SAR • Wind speed at 100 m, u100 - using WRF parameters T2, HFX, PBLH: LWRF/SAR > 0 : u 100 SAR u∗ SAR 100 100 ln = −ψ 100 1 − κ z0 2 PBLH L WRF / SAR LWRF/SAR ≤ 0 : u 100 SAR = u∗ SAR ln 100 −ψ 100 κ z0 LWRF / SAR 11 DTU Wind Energy, Technical University of Denmark 5/9/2012 100-m winds at Fino-1 12 DTU Wind Energy, Technical University of Denmark 5/9/2012 100-m Weibull fit at Fino-1 13 DTU Wind Energy, Technical University of Denmark 5/9/2012 Spatial wind variability over the North Sea 14 DTU Wind Energy, Technical University of Denmark 5/9/2012 Sampling effects over the North Sea 15 DTU Wind Energy, Technical University of Denmark 5/9/2012 Special situation: Low boundary-layer height • The applied wind profile equations are valid within the atmospheric boundary-layer • Data are discarded when the boundary-layer height is <50 m • Up to 4% of the WRF samples are discarded over the North Sea over a year • None of the 80 SAR scenes, and concurrent WRF samples, are discarded 16 DTU Wind Energy, Technical University of Denmark 5/9/2012 Conclusions • Satellite SAR data lifted to 100 m under-estimate the wind speed at Fino-1 • Concurrent WRF simulations also under-estimate the 100-m wind speed at Fino-1 • SAR-WRF agreement is generally good over the North Sea with the largest differences near the coast of Germany • The number of SAR samples (80) is insufficient to describe the mean wind climate accurately • Work is in progress to improve the accuracy of lifted satellite wind fields • Satellite observations represent a valuable source of information for offshore wind energy applications (e.g. wind resource mapping, wind farm wake analyses) 17 DTU Wind Energy, Technical University of Denmark 5/9/2012 Acknowledgements Satellite data: The European Space Agency (ESA) Remote Sensing Systems (RSS) SAR wind field retrieval: Collecte Localisation Satellites (CLS) The Johns Hopkins University, Applied Physics Laboratory (JHU/APL) Fino-1 and Fino-2 mast data: Bundesministerium für Umwelt (BMU), Projektträger Juelich (PTJ), Deutsches Windenergie Institut (DEWI) Funding: EU-NORSEWInD (TREN-FP7EN-21908) 18 DTU Wind Energy, Technical University of Denmark 5/9/2012
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