1 Risø National Laboratory for Sustainable Energy, Technical University of Denmark2 Wind Energy Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark3 Meteorology, Wind Energy Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark4 Wind Energy Systems, Wind Energy Division, Risø National Laboratory for Sustainable Energy, Technical University of Denmark5 Department of Wind Energy, Technical University of Denmark6 unknown
As part of the “Meso-Scale and Micro-Scale Modelling in China” project, also known as the CMA component of the Sino-Danish Wind Energy Development Programme (WED), microscale modelling and analyses have been carried out for 12 meteorological stations in NE China. Wind speed and direction data from the twelve 70-m masts have been analysed using the Wind Atlas Analysis and Application Program (WAsP 10). The wind-climatological inputs are the observed wind climates derived from the WAsP Climate Analyst. Topographical inputs are elevation maps constructed from SRTM 3 data and roughness length maps constructed from Google Earth satellite imagery. The maps have been compared to Chinese topographical maps and adjusted accordingly. Summaries are given of the data measured at the 12 masts for the reference period 2009. The main result of the microscale modelling is an observational wind atlas for NE China which can be used for verification of the mesoscale modelling. In addition, the microscale modelling itself has been verified by comparing observed and modelled vertical wind profiles at the 12 sites. WAsP generally works well in Dongbei, even in its default set-up, though forested hilly and complex sites are less well modelled. Modelling of the wind profiles can be improved by using project-specific wind atlas heights and also sometimes by changing the heat flux parameters of WAsP. The southernmost sites seem to be slightly more unstable on average than the default settings in WAsP; the northern and most elevated sites seem somewhat more stable. The sensitivity of the WAsP modelling to 11 different input parameters has been investigated and it is found that the modelling is rather robust to changes in input data and parameters, when using the 70-m level anemometer as predictor. Site-specific air density (power curve) and calibrated anemometers are confirmed to be prerequisites for reliable predictions; project-specific wind atlas heights are highly recommended.
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Risø National Laboratory for Sustainable Energy, Technical University of Denmark, 2010