Wind field variability in high-resolution simulations for wind energy forecasts and resource assessment
Abstract
Wind farm resource assessment, operational wind power forecasting, and wind turbine micrositing may benefit from high-resolution simulations of atmospheric flow over complex terrain. Domains can be refined from mesoscale to finer scales using grid nesting to adequately resolve turbulence and terrain in the atmospheric boundary layer. In previous work, we showed that nesting down to fine resolutions (~100 m horizontal spacing) using the WRF model does not clearly improve mean wind forecasts for our case study wind farm when modeling either synoptically or locally driven events. Differences due to increased vertical resolution or using one- vs. two-way nesting were also minimal. The LES models we tested gave similar results and were only slightly closer to the observations than the RANS models. For this particular domain, it appears that key topographic features are well resolved even at coarser resolutions, so that there is minimal change in mean winds at finer resolutions. In this work, we investigate temporal and spatial variability of predicted fields to gain further insight into possible differences due to changes in grid configuration. We also perform week-long simulations at fine resolutions of 300 or 100 meters to determine if we can obtain more detailed results for wind energy resource assessment. High-resolution representation of the spatial structure of the wind flow might be able to better capture variations in wind velocity that are relevant to wind resource assessment. Improved turbulence closure schemes will also be tested and should be able to better capture the fluctuations in the wind fields which may contribute to turbine fatigue. Long term, fine resolution runs should provide more insight into wind patterns and yield frequency distributions of wind speed, wind shear, TKE, and other factors that are invaluable to wind farm operators in determining appropriate sites for turbines and times for greatest power output.
- Publication:
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AGU Fall Meeting Abstracts
- Pub Date:
- December 2010
- Bibcode:
- 2010AGUFM.A41F0165M
- Keywords:
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- 3307 ATMOSPHERIC PROCESSES / Boundary layer processes;
- 3329 ATMOSPHERIC PROCESSES / Mesoscale meteorology;
- 3355 ATMOSPHERIC PROCESSES / Regional modeling;
- 3379 ATMOSPHERIC PROCESSES / Turbulence