GC43F-01
Simulating wind energy resources with mesoscale models: Intercomparison of state-of-the-art models over Northern Europe

Thursday, 17 December 2015: 13:40
2022-2024 (Moscone West)
Andrea N Hahmann, Technical University of Denmark, Wind Energy, Roskilde, Denmark
Abstract:
Mesoscale models are increasingly being used to estimate wind conditions to identify perspective areas and sites where to develop wind farm projects. Mesoscale models are useful because they give information over extensive areas with various terrain complexities where measurements are scarce and measurement campaigns costly. Various mesoscale models and families of mesoscale models are being used, with thousands of setup options. Since long-term integrations are expensive and tedious to carry out, only limited comparisons exist. We have carried out a blind benchmarking study to evaluate the capabilities of mesoscale models used in wind energy to estimate site wind conditions: to highlight common issues on mesoscale modeling of wind conditions on sites with different characteristics, and to identify gaps and strengths of models and understand the root conditions for further evaluating uncertainties. Three experimental sites with tall mast measurements were selected: FINO3 (offshore), Høvsøre (coastal), and Cabauw (land-based). The participants were asked to provide hourly time series of wind speed and direction, temperature, etc., at various heights for 2011. The methods used were left to the choice of the participants, but they were asked for a detailed description of their model and many other parameters (e.g., horizontal and vertical resolution, model parameterizations, surface roughness length) that could be used to group the models and interpret the results of the intercomparison. The analysis of the time series includes comparison to observations, summarized with well-known measures such as biases, RMSE, correlations, and of sector-wise statistics, and the temporal spectra. The statistics were grouped by the models, their spatial resolution, forcing data, various integration methods, etc. The results show high fidelity of the various entries in simulating the wind climate at the offshore and coastal site. Over land and the statistics of other derived fields (e.g. wind shear distributions) show much less similarities among the models and with the observations. Cloud computing now allows the use of mesoscale models by non-experts for site assessment. This tool is very useful and powerful, but users must be aware of the different issues that might be encountered in working with different setups.