The wind is a natural, renewable energy resource, which offers potential solutions to the worldwide energy challenges we are facing today: the demand for energy is growing rapidly; we wish to eliminate our dependence on fossil fuel and incentives have been set up to reduce greenhouse gas emissions. Key topics in wind energy management include the design of wind turbines and blades, power grid connection, wind farm siting according to the wind resource, and evaluation of environmental impacts. Recently, large-scale wind power has been installed offshore. Ocean wind fields, derived from satellite and airborne synthetic aperture radar (SAR), are therefore useful for wind energy applications. At Risų National Laboratory in Denmark, work is being carried out to estimate wind resources from SAR and to quantify the impact of large offshore wind farms on the marine wind climate. In this paper, objectives and results of these offshore wind energy studies are presented.

In order to estimate the wind resource at any given site, observations of wind speed and direction are needed. Conventionally, such observations are obtained from meteorological towers for at least a one-year period. Construction and maintenance of a meteorological mast offshore is costly, therefore remote sensing techniques are attractive alternative data sources. A further advantage of SAR measurements is the gain of spatial information, whereas a meteorological mast provides measurements at one point in space. The high temporal resolution available from in situ measurements is not achievable with SAR but wind resource estimates can be produced if a sufficient number of scenes are available. For example, the annual mean wind speed can be determined from 60-70 randomly selected SAR scenes with an accuracy of ±10% at the 90% confidence interval.

For wind resource estimation, satellite SAR images were obtained from the ERS-2 and ENVISAT missions, the latter in alternating polarization mode (APP), image mode (IMP) and wide swath mode (WSM). The images provide coverage in near-shore areas where offshore wind farms are typically located. Wind speeds at 10 m were retrieved from the satellite images using the CMOD algorithms (e.g. CMOD4, CMOD5, CMOD-IFR2). The wind direction, required as model input, was obtained from existing offshore masts or from spectral analysis of the SAR images, as most scenes showed streaks aligned with the wind vector. The Risų WEMSAR Tool (RWT) has been developed for retrieval of a probability density function from SAR-derived wind maps using footprint analysis. The function is described by its Weibull A (scale) and k (shape) parameters, the parameters necessary for wind resource estimation with software packages such as the Wind Atlas Analysis and Application Program (WAsP). Our results show good consistency between A and k values derived from satellite SAR and in situ measurements.

The two largest offshore wind farms in the world are located at the Danish sites Horns Rev and Nysted. The wind farm at Horns Rev became operational in late 2002 with 80 turbines and a total capacity 160 MW. The wind farm at Nysted became operational in mid-2003 with 72 turbines and a total capacity 166 MW. At both sites, the total turbine height is 110 m above mean sea level. A series of satellite and airborne SAR images were analyzed to determine the downstream distance over which the two large-scale wind farms impact the marine wind climate. Of particular interest was the magnitude and extend of wind wakes, characterized by a reduced mean wind speed and enhanced turbulence intensity. Knowledge about the wake effect is valuable in environmental impact studies and further, it is useful in the planning of new wind farms. Construction of multiple wind farms at the same site is attractive because maintenance costs and grid connections can be shared. Micro-siting and environmental impact studies are currently in progress at Horns Rev and Nysted, as the development of two additional wind farms is scheduled.

For the wake study, wind maps were generated from selected high-resolution ERS-2 and ENVISAT scenes and from airborne E-SAR scenes acquired over Horns Rev on October 12, 2003 by the German Aerospace Center (DLR). The E-SAR data have a much higher spatial resolution (2 m) than the satellite SAR images (25 m). A disadvantage is the longer acquisition time (2-4 minutes per scene) that allows the wind speed and direction to fluctuate within a single E-SAR scene. Spatial averages of wind speed were obtained upstream, within, and downstream of the turbine arrays and turbulence intensity was calculated from the standard deviation of wind speed. Velocity deficits up to 10% of the ambient wind speed were found downstream of the wind farms. Wake effects were observed for downstream distances of 5-20 km, depending on the ambient wind speed, the atmospheric stability and the fraction of turbines operating during SAR data acquisitions. Enhanced turbulence intensity was found downstream of the wind farms for ~50% of the cases studied. This ambiguity may result from a lack of turbine-generated turbulence near the sea surface, where SAR measurements are obtained.