Energy saving, reduction of greenhouse gasses and increased use of renewables are keypolicies to achieve the European 2020 targets. In particular, distributed renewable energy sources,integrated with spatial planning, require novel methods to optimise supply and demand. In contrastwith large scale wind turbines, small and medium wind turbines (SMWTs) have a less extensiveimpact on the use of space and the power system, nevertheless, a significant spatial footprint is stillpresent and the need for good spatial planning is a necessity. To optimise the location of SMWTs,detailed knowledge of the spatial distribution of the average wind speed is essential, hence, in thisarticle, wind measurements and roughness maps were used to create a reliable annual mean windspeed map of Flanders at 10 m above the Earth’s surface. Via roughness transformation, the surfacewind speed measurements were converted into meso- and macroscale wind data. The data werefurther processed by using seven different spatial interpolation methods in order to develop regionalwind resource maps. Based on statistical analysis, it was found that the transformation into mesoscalewind, in combination with Simple Kriging, was the most adequate method to create reliable maps fordecision-making on optimal production sites for SMWTs in Flanders (Belgium).
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