Advances in Offshore Wind Resource Estimation

Wind resource mapping is basically a meteorological time-series statistical analysis, to which the features of the landscape such as roughness, topography and local obstacles are integrated. The normal procedure is to use the WAsP program which is de facto standard for wind turbine siting]. The basic principle of the program is to solve the atmospheric flow equation using the logarithmic wind profile law and then to include the effects of the terrain. The optimal situation is to have accurate, long-term wind and turbulence observations from the height in the atmospheric boundary layer at the site where a wind farm is envisioned. This information provides the basis for wind resource mapping, identifying extreme conditions and wind load on the turbines.

[1]  Rebecca J. Barthelmie,et al.  Mesoscale modelling for an offshore wind farm , 2006 .

[2]  Hans Ejsing Jørgensen,et al.  The Profiler Intercomparison Experiment (PIE) , 2004 .

[3]  Pablo Clemente-Colon,et al.  A systematic comparison of QuikSCAT and SAR ocean surface wind speeds , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[4]  R. Barthelmie,et al.  Can Satellite Sampling of Offshore Wind Speeds Realistically Represent Wind Speed Distributions? Part II: Quantifying Uncertainties Associated with Distribution Fitting Methods , 2004 .

[5]  H. Bergström Boundary-Layer Modelling for Wind Climate Estimates , 2001 .

[6]  Charlotte Bay Hasager,et al.  Using airborne and satellite SAR for wake mapping offshore , 2006 .

[7]  Michael Harris,et al.  Site wind field determination using a cw Doppler lidar - comparison with cup anemometers at Risø , 2004 .

[8]  Thierry Ranchin,et al.  Combined extraction of high spatial resolution wind speed and wind direction from SAR images: A new approach using wavelet transform , 2002 .

[9]  M. Nielsen,et al.  Validation of ERS-2 SAR offshore wind-speed maps in the North Sea , 2004 .

[10]  Rebecca J. Barthelmie,et al.  Analytical modelling of wind speed deficit in large offshore wind farms , 2006 .

[11]  A. Dyer A review of flux-profile relationships , 1974 .

[12]  R. Barthelmie,et al.  Can Satellite Sampling of Offshore Wind Speeds Realistically Represent Wind Speed Distributions , 2003 .

[13]  L. Landberg,et al.  Modelling the Wind Climate of Ireland , 1997 .

[14]  A. Smedman,et al.  Low level jets : A decisive factor for off-shore wind energy siting in the Baltic Sea , 1996 .

[15]  F. Fiedler,et al.  1Simulation of unstationary wind and temperature fields over complex terrain and comparison with observations , 1991 .

[16]  Niels Gylling Mortensen,et al.  Response of neutral boundary layers to changes of roughness , 1990 .

[17]  Charlotte Bay Hasager,et al.  Wake effects of large offshore wind farms identified from satellite SAR , 2005 .

[18]  Paris W. Vachon,et al.  Wind direction estimation from SAR images of the ocean using wavelet analysis , 2002 .

[19]  B. Lange,et al.  Offshore wind resource assessment with WAsP and MM5: comparative study for the German Bight , 2007 .

[20]  James F. Manwell,et al.  Comparison of the performance of four measure–correlate–predict algorithms , 2005 .

[21]  Rupert Klein,et al.  Effects Of Changing Surface Heat Flux On Atmospheric Boundary-Layer Flow Over Flat Terrain , 2005 .

[22]  Wolfgang Koch,et al.  Directional analysis of SAR images aiming at wind direction , 2004, IEEE Transactions on Geoscience and Remote Sensing.

[23]  B. Lange,et al.  Comparison of Wake Model Simulations with Offshore Wind Turbine Wake Profiles Measured by Sodar , 2006 .

[24]  William R. Cotton,et al.  A one-dimensional simulation of the stratocumulus-capped mixed layer , 1983 .

[25]  Rebecca J. Barthelmie,et al.  Challenges in Predicting Power Output from Offshore Wind Farms , 2006 .

[26]  M. Nielsen,et al.  Wind resource assessment from C-band SAR , 2006 .

[27]  David L. T. Anderson,et al.  Scatterometer data interpretation: Estimation and validation of the transfer function CMOD4 , 1997 .

[28]  Hans Ejsing Jørgensen,et al.  Comparison of wind speed and power curve measurements using a cup anemometer, a LIDAR and a SODAR , 2004 .

[29]  Pablo Clemente-Colon,et al.  Comparison of SAR-derived wind speed with model predictions and ocean buoy measurements , 2001, IEEE Trans. Geosci. Remote. Sens..

[30]  A. Cohen,et al.  Maximum Likelihood Estimation in the Weibull Distribution Based On Complete and On Censored Samples , 1965 .

[31]  Charlotte Bay Hasager,et al.  Offshore wind resource estimation from satellite SAR wind field maps , 2005 .

[32]  Charlotte Bay Hasager,et al.  Offshore winds observed from space. Issues for planning of offshore wind farms , 2006 .

[33]  R. Barthelmie,et al.  Quantifying offshore wind resources from satellite wind maps: study area the North Sea , 2004 .

[34]  R.A.S. Ratchliffe,et al.  Book reviewBoundary-layer meteorology: A new quarterly journal of physical and biological processes in the atmospheric boundary layer. R. E. Munn (Editor). D. Reidel Publishing Company, Dordrecht, 1969, Volume 1(1). , 1971 .

[35]  Frank Monaldo The Alaska SAR demonstration and near-real-time synthetic aperture radar winds , 2000 .

[36]  Charlotte Bay Hasager,et al.  Wind atlas for Egypt. Measurements and modelling 1991-2005 , 2006 .

[37]  J. Gash,et al.  A note on estimating the effect of a limited fetch on micrometeorological evaporation measurements , 1986 .

[38]  S. Gryning,et al.  Offshore wind profiling using light detection and ranging measurements , 2009 .