Following publications have been announced by our department Hydrodynamics and Data Assimilation. For further information please contact Dr. Bughsin Djath, co-author of the publications:
von Brandis, A., Centurelli, G., Schmidt, J., Vollmer, L., Djath, B., & Dörenkämper, M. (2023): An investigation of spatial wind direction variability and its consideration in engineering models. Wind Energ. Sci., 8, 589–606, doi:10.5194/wes-8-589-2023
Abstract:
We propose that considering mesoscale wind direction changes in the computation of wind farm cluster wakes could reduce the uncertainty of engineering wake modeling tools. The relevance of mesoscale wind direction changes is investigated using a wind climatology of the German Bight area covering 30 years, derived from the New European Wind Atlas (NEWA). Furthermore, we present a new solution for engineering modeling tools that accounts for the effect of such changes on the propagation of cluster wakes. The mesoscale wind direction changes relevant to the operation of wind farm clusters in the German Bight are found to exceed 11∘ in 50 % of all cases. Particularly in the lower partial load range, which is associated with strong wake formation, the wind direction changes are the most pronounced, with quartiles reaching up to 20∘. Especially on a horizontal scale of several tens of kilometers to 100 km, wind direction changes are relevant. Both the temporal and spatial scales at which large wind direction changes occur depend on the presence of synoptic pressure systems. Furthermore, atmospheric conditions which promote far-reaching wakes were found to align with a strong turning in 14.6 % of the cases. In order to capture these mesoscale wind direction changes in engineering model tools, a wake propagation model was implemented in the Fraunhofer IWES wind farm and wake modeling software “flappy” (Farm Layout Program in Python). The propagation model derives streamlines from the horizontal velocity field and forces the single turbine wakes along these streamlines. This model has been qualitatively evaluated by simulating the flow around wind farm clusters in the German Bight with data from the mesoscale atlas of the NEWA and comparing the results to synthetic aperture radar (SAR) measurements for selected situations. The comparison reveals that the flow patterns are in good agreement if the underlying mesoscale data capture the velocity field well. For such cases, the new model provides an improvement compared to the baseline approach of engineering models, which assumes a straight-line propagation of wakes. The streamline and the baseline models have been further compared in terms of their quantitative effect on the energy yield. Simulating two neighboring wind farm clusters over a time period of 10 years, it is found that there are no significant differences across the models when computing the total energy yield of both clusters. However, extracting the wake effect of one cluster on the other, the two models show a difference of about 1 %. Even greater differences are commonly observed when comparing single situations. Therefore, we claim that the model has the potential to reduce uncertainty in applications such as site assessment and short-term power forecasting.
Cañadillas, B., Wang, S., Ahlert, Y., Djath, B., Barekzai, M., Foreman, R., & Lampert, A. (2023): Coastal horizontal wind speed gradients in the North Sea based on observations and ERA5 reanalysis data. Meteorologische Zeitschrift (2023), doi:10.1127/metz/2022/1166
Abstract:
The transition from land to sea affects the wind field in coastal regions. From the perspective of near-coastal offshore wind farms, the coastal transition complicates the task of energy resource assessment by, for example, introducing non-homogeneity into the free wind field. To help elucidate the matter, we quantify the average horizontal wind speed gradients at progressively increasing distances from the German coast using two years of hourly ERA5 reanalysis data, and further describe the dependence of wind speed gradients on the measurement height, atmospheric stability, and season. A vertical wind lidar located on Norderney Island near the German mainland acts as our observational reference for the ERA5 data, where a good agreement ( R 2 = 0 . 9 3 $R^2 =\nobreak 0.93$ ) is found despite the relatively coarse ERA5 data resolution. Interestingly, the comparison of lidar data with the higher-resolution Weather Research and Forecasting (WRF) mesoscale model yields good but relatively weaker agreement ( R 2 = 0 . 8 5 $R^2 =\nobreak 0.85$ ). The ERA5 data reveal that, for flow over the North Sea originating from the German mainland from the south, the wind speed at 10 m (110 m) above sea level increases by 30 % (20 %) some 80 km from the coast on average, and by 5 % at larger heights. An increased stratification increases the horizontal wind speed gradient at 10 m above sea level but decreases it at 110 m. Case studies using satellite and flight measurements are first analyzed to help reveal some of the underlying mechanisms governing horizontal wind speed gradients, including cases of decreasing wind speed with increasing distance from the coast, in which stable flow of warm air over the colder sea leads to an overall deceleration of the flow. The accuracy of offshore resource assessment appears to profit from utilising the horizontal wind speed gradient information contained in ERA5 reanalysis data.