Articles | Volume 3, issue 2
https://doi.org/10.5194/wes-3-573-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/wes-3-573-2018
© Author(s) 2018. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Research article
| 
24 Aug 2018
Research article |
| 24 Aug 2018
| 24 Aug 2018
Applications of satellite winds for the offshore wind farm site Anholt
Department of Wind Energy, Technical University of Denmark, Roskilde,
4000, Denmark
Merete Badger
Department of Wind Energy, Technical University of Denmark, Roskilde,
4000, Denmark
Patrick Volker
Department of Wind Energy, Technical University of Denmark, Roskilde,
4000, Denmark
Kurt S. Hansen
Department of Wind Energy, Technical University of Denmark, Roskilde,
4000, Denmark
Charlotte B. Hasager
Department of Wind Energy, Technical University of Denmark, Roskilde,
4000, Denmark
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Before constructing wind farms we need to know how much energy they will produce. This requires knowledge of long-term wind conditions from either measurements or models. At the US East Coast there are few wind measurements and little experience with offshore wind farms. Therefore, we created a satellite-based high-resolution wind resource map to quantify spatial variations in the wind conditions over potential sites for wind farms and found larger variation than modelling suggested.
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Daniel Hatfield, Charlotte Bay Hasager, and Ioanna Karagali
Wind Energ. Sci., 8, 621–637, https://doi.org/10.5194/wes-8-621-2023, https://doi.org/10.5194/wes-8-621-2023, 2023
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Wind observations at heights relevant to the operation of modern offshore wind farms, i.e. 100 m and more, are required to optimize their positioning and layout. Satellite wind retrievals provide observations of the wind field over large spatial areas and extensive time periods, yet their temporal resolution is limited and they are only representative at 10 m height. Machine-learning models are applied to lift these satellite winds to higher heights, directly relevant to wind energy purposes.
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Wind Energ. Sci., 7, 1069–1091, https://doi.org/10.5194/wes-7-1069-2022, https://doi.org/10.5194/wes-7-1069-2022, 2022
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Wind Energ. Sci., 6, 1379–1400, https://doi.org/10.5194/wes-6-1379-2021, https://doi.org/10.5194/wes-6-1379-2021, 2021
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Tobias Ahsbahs, Galen Maclaurin, Caroline Draxl, Christopher R. Jackson, Frank Monaldo, and Merete Badger
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Aemilius A. W. van Vondelen, Sachin T. Navalkar, Alexandros Iliopoulos, Daan C. van der Hoek, and Jan-Willem van Wingerden
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Romanas Puisa, Victor Bolbot, Andrew Newman, and Dracos Vassalos
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Simone Mancini, Koen Boorsma, Marco Caboni, Marion Cormier, Thorsten Lutz, Paolo Schito, and Alberto Zasso
Wind Energ. Sci., 5, 1713–1730, https://doi.org/10.5194/wes-5-1713-2020, https://doi.org/10.5194/wes-5-1713-2020, 2020
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Robbie Herring, Kirsten Dyer, Paul Howkins, and Carwyn Ward
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Tobias Ahsbahs, Galen Maclaurin, Caroline Draxl, Christopher R. Jackson, Frank Monaldo, and Merete Badger
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Anna-Maria Tilg, Charlotte Bay Hasager, Hans-Jürgen Kirtzel, and Poul Hummelshøj
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Aurélien Babarit, Gaël Clodic, Simon Delvoye, and Jean-Christophe Gilloteaux
Wind Energ. Sci., 5, 839–853, https://doi.org/10.5194/wes-5-839-2020, https://doi.org/10.5194/wes-5-839-2020, 2020
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Michael Denis Mifsud, Tonio Sant, and Robert Nicholas Farrugia
Wind Energ. Sci., 5, 601–621, https://doi.org/10.5194/wes-5-601-2020, https://doi.org/10.5194/wes-5-601-2020, 2020
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In offshore wind, it is important to have an accurate wind resource assessment. Measure–correlate–predict (MCP) is a statistical method used in the assessment of the wind resource at a candidate site. Being a statistical method, it is subject to uncertainty, resulting in an uncertainty in the power output from the wind farm. This study involves the use of wind data from the island of Malta and uses a hypothetical wind farm to establish the best MCP methodology for the wind resource assessment.
Aurélien Babarit, Simon Delvoye, Gaël Clodic, and Jean-Christophe Gilloteaux
Wind Energ. Sci. Discuss., https://doi.org/10.5194/wes-2019-101, https://doi.org/10.5194/wes-2019-101, 2020
Revised manuscript not accepted
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This paper addresses the topic of far-offshore wind energy exploitation. Far-offshore wind energy exploitation is not feasible with current technology because grid-connection cost, installation cost and O&M cost would be prohibitive. An enabling technology for far-offshore wind energy is the energy ship concept, which has been described, modelled and analyzed in a companion paper. This paper provides a cost model and cost estimates for an energy system based on the energy ship concept.
Amber Kapoor, Slimane Ouakka, Sanjay R. Arwade, Julie K. Lundquist, Matthew A. Lackner, Andrew T. Myers, Rochelle P. Worsnop, and George H. Bryan
Wind Energ. Sci., 5, 89–104, https://doi.org/10.5194/wes-5-89-2020, https://doi.org/10.5194/wes-5-89-2020, 2020
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Offshore wind energy is a burgeoning area of renewable energy that is at an early stage of development in the United States. Exposure of offshore wind turbines to hurricanes must be assessed and mitigated to ensure the security of the renewable energy supply. This research assesses the impact of hurricane wind fields on the structural response of wind turbines. Such wind fields have characteristics that may pose heretofore unforeseen structural challenges to offshore wind turbines.
Jakob Ilsted Bech, Charlotte Bay Hasager, and Christian Bak
Wind Energ. Sci., 3, 729–748, https://doi.org/10.5194/wes-3-729-2018, https://doi.org/10.5194/wes-3-729-2018, 2018
Short summary
Short summary
Rain erosion on wind turbine blades is a severe challenge for wind energy today. It causes significant losses in power production, and large sums are spent on inspection and repair.
Blade life can be extended, power production increased and maintenance costs reduced by rotor speed reduction at extreme precipitation events. Combining erosion test results, meteorological data and models of blade performance, we show that a turbine control strategy is a promising new weapon against blade erosion.
Sebastian Schafhirt and Michael Muskulus
Wind Energ. Sci., 3, 25–41, https://doi.org/10.5194/wes-3-25-2018, https://doi.org/10.5194/wes-3-25-2018, 2018
Lisa Ziegler, Ursula Smolka, Nicolai Cosack, and Michael Muskulus
Wind Energ. Sci., 2, 469–476, https://doi.org/10.5194/wes-2-469-2017, https://doi.org/10.5194/wes-2-469-2017, 2017
Short summary
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The first larger offshore wind farms are reaching a mature age. Operators have to take actions for monitoring now in order to have accurate knowledge on structural reserves later. This knowledge is important to make decisions on lifetime extension. Many offshore wind turbines have one set of strain gauges already installed at the transition piece. We present a simple and robust method to extrapolate these measurements to other locations of the monopile without need of additional instrumentation.
Antonio Jarquin Laguna
Wind Energ. Sci., 2, 387–402, https://doi.org/10.5194/wes-2-387-2017, https://doi.org/10.5194/wes-2-387-2017, 2017
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This paper presents the idea of centralized electricity production in a wind farm by means of water technology. A new way of generating and transmitting wind energy is explored with no intermediate electrical conversion until the energy has reached the central offshore platform. This work includes the modelling and simulations of a hypothetical hydraulic wind farm, where results indicate good performance despite the turbulent wind conditions and wake effects.
Steffen Aasen, Ana M. Page, Kristoffer Skjolden Skau, and Tor Anders Nygaard
Wind Energ. Sci., 2, 361–376, https://doi.org/10.5194/wes-2-361-2017, https://doi.org/10.5194/wes-2-361-2017, 2017
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The industry standard for analysis of monopile foundations is inaccurate, and alternative models for foundation behavior are needed. This study investigates how four different soil-foundation models affect the fatigue damage of an offshore wind turbine with a monopile foundation. Stiffness and damping properties have a noticeable effect, in particular for idling cases. At mud-line, accumulated fatigue damage varied up to 22 % depending on the foundation model used.
Cited articles
Ahsbahs, T., Badger, M., Karagali, I., and Larsén, X. G.: Validation of
Sentinel-1A SAR Coastal Wind Speeds Against Scanning LiDAR, Remote Sens.,
9, p. 552, 2017.
Alpers, W. R., Ross, D. B., and Rufenach, C. L.: On the detectability of
ocean surface waves by real and synthetic aperture radar, J.
Geophys. Res., 86, 6481–6498,
https://doi.org/10.1029/JC086iC07p06481, 1981.
Badger, M., Peña, A., Hahmann, A. N., Mouche, A. A., and Hasager, C. B.:
Extrapolating Satellite Winds to Turbine Operating Heights, J. Appl.
Meteorol. Climatol., 55, 975–991, 2016.
Barthelmie, R. J., Badger, J., Pryor, S. C., Hasager, C. B., Christiansen, M.
B., and Jørgensen, B. H.: Offshore Coastal Wind Speed Gradients: issues
for the design and development of large offshore windfarms, Wind Engin.,
31, 369–382, 2007.
Barthelmie, R. J., Pryor, S. C., Frandsen, S. T., Hansen, K. S., Schepers, J.
G., Rados, K., and Neckelmann, S.: Quantifying the Impact of Wind Turbine
Wakes on Power Output at Offshore Wind Farms, J. Atmos. Ocean. Technol.,
27, 1302–1317, 2010.
Christiansen, M. B. and Hasager, C. B.: Wake effects of large offshore wind
farms identified from satellite SAR, Remote Sens. Environ., 98, 251–268,
2005.
Christiansen, M. B., Koch, W., Horstmann, J., Hasager, C. B., and Nielsen,
M.: Wind resource assessment from C-band SAR, Remote Sens. Environ., 105,
68–81, 2006.
Dagestad, K.-F., Horstmann, J., Mouche, A., Perrie, W., and Shen, H.: Wind
Retrieval From Synthetic Aperture Radar, an Overview, in: Seasar 2012
Oceanography Workshop, European Space Agency, ESA, 2013.
Dee, D. P., Uppala, S. M., Simmons, A. J., Berrisford, P., Poli, P.,
Kobayashi, S., and Vitart, F.: The ERA-Interim reanalysis: Configuration and
performance of the data assimilation system, Q. J. Roy. Meteor. Soc., 137,
553–597, 2011.
Dörenkämper, M., Optis, M., Monahan, A., and Steinfeld, G.: On the
Offshore Advection of Boundary-Layer Structures and the Influence on Offshore
Wind Conditions, Bound.-Lay. Meteorol., 155, 459–482,
https://doi.org/10.1007/s10546-015-0008-x, 2015.
DTU Wind Energy: Satellite Winds, available at: https://satwinds.windenergy.dtu.dk/ last access:
20 August 2018.
Fitch, A. C., Olson, J. B., Lundquist, J. K., Dudhia, J., Gupta, A. K.,
Michalakes, J., and Barstad, I.: Local and Mesoscale Impacts of Wind Farms as
Parameterized in a Mesoscale NWP Model, Mon. Weather Rev., 140, 3017–3038,
https://doi.org/10.1175/MWR-D-11-00352.1, 2012.
Floors, R., Gryning, S. E., Pena, A., and Batchvarova, E.: Analysis of
diabatic flow modification in the internal boundary layer, Meteorol. Z.,
20, 649–659, 2011.
Gade, M. and Alpers, W.: Using ERS-2 SAR images for routine observation
of marine pollution in European coastal waters, Sci. Total
Environ., 237/238, 441–448, 1997.
Gash, J. H. C.: A Note on Estimating the Effect of a Limited Fetch on
Micrometeorological Evaporation Measurements, Bound.-Lay. Meteorol., 35, 409–413, 1986.
Grachev, A. A. and Fairall, C. W.: Dependence of the Monin-Obukhov
Stability Parameter on the Bulk Richardson Number over the Ocean,
J. Appl. Meteorol., 36, 406–414, 1996.
Hahmann, A. N., Vincent, C. L., Peña, A., Lange, J., and Hasager, C. B.:
Wind climate estimation using WRF model output: Method and model
sensitivities over the sea, Int. J. Climatol., 35, 3422–3439, 2015.
Hansen, K. S., Barthelmie, R. J., Jensen, L. E., and Sommer, A.: The impact
of turbulence intensity and atmospheric stability on power deficits due to
wind turbine wakes at Horns Rev wind farm, Wind Energy, 15, 183–196, 2012.
Hansen, K. S., Réthoré, P. E., Palma, J., Hevia, B. G.,
Prospathopoulos, J., Peña, A., and Volker, P.: Simulation of wake effects
between two wind farms, J. Phys.-Conf. Ser., 625, 012008,
https://doi.org/10.1088/1742-6596/625/1/012008, 2015.
Hasager, C. B., Dellwik, E., Nielsen, M., and Furevik, B. R.: Validation of
ERS-2 SAR offshore wind-speed maps in the North Sea, Int. J. Remote Sens.,
25, 3817–3841, 2004.
Hasager, C. B., Badger, M., Peña, A., Larsén, X. G., and Bingöl,
F.: SAR-based wind resource statistics in the Baltic Sea, Remote Sens., 3,
117–144, 2011.
Hasager, C. B., Mouche, A., Badger, M., Bingöl, F., Karagali, I.,
Driesenaar, T., and Longépé, N.: Offshore wind climatology based on
synergetic use of Envisat ASAR, ASCAT and QuikSCAT, Remote Sens. Environ.,
156, 247–263, 2015a.
Hasager, C. B., Vincent, P., Badger, J., Badger, M., Di Bella, A., Peña,
A., and Volker, P.: Using Satellite SAR to Characterize the Wind Flow around
Offshore Wind Farms, Energies, 8, 5413–5439, 2015b.
Hersbach, H.: Comparison of C-Band Scatterometer CMOD5.N Equivalent
Neutral Winds with ECMWF, J. Atmos. Ocean. Technol., 27, 721–736, 2010.
Hong, S.-Y., Noh, Y., and Dudhia, J.: A New Vertical Diffusion Package
with an Explicit Treatment of Entrainment Processes, Month. Weather
Rev., 134, 2318–2341, 2006.
Jensen, N. O.: A note on wind generator interaction (Risø-M-2411), Roskilde, 1983.
Lange, B., Larsen, S., Højstrup, J., and Barthelmie, R.: The influence of
thermal effects on the wind speed profile of the coastal marine boundary
layer, Bound.-Lay. Meteorol., 112, 587–617, 2004.
Larsen, G. C.: A simple stationary semi-analytical wake model, Risø National Laboratory for Sustainable Energy,
Technical University of Denmark, 2009.
Li, X. and Lehner, S.: Observation of TerraSAR-X for Studies on
Offshore Wind Turbine Wake in Near and Far Fields, IEEE J.
Sel. Top. Appl., 6,
1757–1768, 2013.
Monaldo, F. M., Jackson, C. R., Pichel, W. G., and Li, X.: A Weather Eye on
Coastal Winds, Eos, 96, 1–8, 2015.
Nygaard, N. G.: Wakes in very large wind farms and the effect of neighbouring
wind farms, J. Phys. Conf. Ser., 524, 12162,
https://doi.org/10.1088/1742-6596/524/1/012162, 2014.
Nygaard, N. G. and Hansen, S. D.: Wake effects between two neighbouring wind
farms, J. Phys. Conf. Ser., 753, 32020,
https://doi.org/10.1088/1742-6596/753/3/032020, 2016.
Ott, S., Berg, J., and Nielsen, M.: Linearised CFD Models for
Wakes, Danmarks Tekniske Universitet, Risø Nationallaboratoriet for
Bæredygtig Energi, 2011.
Peña, A. and Hahmann, A. N.: Atmospheric stability and turbulence fluxes
at Horns Rev – an intercomparison of sonic, bulk and WRF model data, Wind
Energy, 15 , 717–731, 2012.
Peña, A. and Hahmann, A. N.: 30-year mesoscale model simulations for the
“Noise from wind turbines and risk of cardiovascular disease” project, DTU
Wind Energy, 55, 1–27, 2017.
Peña, A., Floors, R., Sathe, A., Gryning, S. E., Wagner, R., Courtney, M.
S., and Hasager, C. B.: Ten Years of Boundary-Layer and Wind-Power
Meteorology at Hovsore, Denmark, Bound.-Lay. Meteorol., 158, 1–26, 2016.
Peña, A., Hansen, K. S., Ott, S., and van der Laan, M. P.: On wake
modeling, wind-farm gradients, and AEP predictions at the Anholt wind farm,
Wind Energ. Sci., 3, 191–202, https://doi.org/10.5194/wes-3-191-2018, 2018.
Platis, A., Siedersleben, S. K., Bange, J., Lampert, A., Bärfuss, K.,
Hankers, R., and Emeis, S.: First in situ evidence of wakes in the far field
behind offshore wind farms, Sci. Rep., 8, 1–10, 2018.
Porté-Agel, F., Wu, Y.-T., Lu, H., and Conzemius, R. J.: Large-eddy
simulation of atmospheric boundary layer flow through wind turbines and wind
farms, J. Wind Eng. Ind. Aerod., 99, 154–168, 2011.
Quilfen, Y., Chapron, B., Elfouhaily, T., Katsaros, K., and Tournadre, J.:
Observation of tropical cyclones by high-resolution scatterometry, J.
Geophys. Res.-Ocean., 103, 2156–2202, 1998.
Reynolds, R. W., Gentemann, C. L., and Corlett, G. K.: Evaluation of AATSR
and TMI satellite SST data, J. Clim., 23, 152–165, 2010.
Skamarock, W. C., Klemp, J. B., Dudhi, J., Gill, D. O., Barker, D. M., Duda,
M. G., and Powers, J. G.: A Description of the Advanced Research WRF Version
3, NCAR Technical Note NCAR/TN-475+STR, 2008.
Smedman, A.-S., Bergström, H., and Grisogono, B.: Evolution of stable
internal boundary layers over a cold sea, J. Geophys. Res.-Ocean., 102,
1091–1099, https://doi.org/10.1029/96JC02782, 1997.
Stoffelen, A. and Anderson, D.: Scatterometer data interpretation: Estimation
and validation of the transfer function CMOD4, J. Geophys. Res., 102,
5767–2780, 1997.
Valenzuela, G. R.: Theories for the interaction of electromagnetic and
oceanic waves-A review, Bound.-Lay. Meteorol., 13, 61–85, 1978.
Van Der Laan, M. P., Pena, A., Volker, P., Hansen, K. S., Sorensen, N. N.,
Ott, S., and Hasager, C. B.: Challenges in simulating coastal effects on an
offshore wind farm, J. Phys. Conf. Ser., 854, 012046,
https://doi.org/10.1088/1742-6596/854/1/012046, 2017.
Volker, P. J. H., Badger, J., Hahmann, A. N., and Ott, S.: The Explicit Wake
Parametrisation V1.0: a wind farm parametrisation in the mesoscale model WRF,
Geosci. Model Dev., 8, 3715–3731, https://doi.org/10.5194/gmd-8-3715-2015,
2015.
Wind Europe: Offshore Wind in Europe: Key trends and statistics, available
at:
https://windeurope.org/wp-content/uploads/files/about-wind/statistics/WindEurope-Annual-Offshore-Statistics-2017.pdf,
last access: 14 August 2018.
Wyngaard, J. C.: Turbulence in the Atmosphere, Cambridge University Press,
2010.
Short summary
Satellites offer wind measurements offshore and can resolve the wind speed on scales of up to 500 m. To date, this data is not routinely used in the industry for planning wind farms. We show that this data can be used to predict local differences in the mean wind speed around the Anholt offshore wind farm. With satellite data, site-specific wind measurements can be introduced early in the planning phase of an offshore wind farm and help decision makers.
Satellites offer wind measurements offshore and can resolve the wind speed on scales of up to...
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