空间风向变化的研究及其在工程模型中的考虑

IF 3.6 Q3 GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY
Anna von Brandis, G. Centurelli, Jonas Schmidt, L. Vollmer, B. Djath, M. Dörenkämper
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引用次数: 0

摘要

摘要我们提出,在计算风电场集群尾流时考虑中尺度风向变化可以降低工程尾流建模工具的不确定性。使用来自新欧洲风图集(NEWA)的德国湾地区30年的风气候学,研究了中尺度风向变化的相关性。此外,我们为工程建模工具提供了一种新的解决方案,该解决方案考虑了这种变化对集群尾流传播的影响。发现与德国湾风电场集群运行相关的中尺度风向变化超过了50% % 在所有情况下。特别是在与强尾流形成相关的较低部分载荷范围内,风向变化最为明显,四分位数高达20∘。尤其是在几十公里到100公里的水平尺度上 公里,风向变化是相关的。大风向变化发生的时间和空间尺度都取决于天气压力系统的存在。此外,发现促进深远尾流的大气条件与14.6年的强烈转向一致 % 案件中。为了在工程模型工具中捕捉这些中尺度风向变化,在Fraunhofer IWES风电场和尾流建模软件flappy(Python中的农场布局程序)中实现了尾流传播模型。传播模型从水平速度场导出流线,并迫使单个涡轮机沿着这些流线尾迹。通过使用NEWA中尺度图谱中的数据模拟德国湾风电场集群周围的气流,并将结果与选定情况下的合成孔径雷达(SAR)测量结果进行比较,对该模型进行了定性评估。比较表明,如果潜在的中尺度数据很好地捕捉到速度场,则流型是一致的。对于这种情况,与工程模型的基线方法相比,新模型提供了改进,后者假设尾流的直线传播。流线模型和基线模型在其对能量产出的定量影响方面进行了进一步比较。在10年的时间段内模拟两个相邻的风电场集群,发现在计算两个集群的总发电量时,模型之间没有显著差异。然而,提取一个星团对另一个星团的尾流效应,两个模型显示出大约1的差异 %. 在比较单个情况时,通常会观察到更大的差异。因此,我们声称该模型有可能减少现场评估和短期电力预测等应用中的不确定性。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
An investigation of spatial wind direction variability and its consideration in engineering models
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.
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来源期刊
Wind Energy Science
Wind Energy Science GREEN & SUSTAINABLE SCIENCE & TECHNOLOGY-
CiteScore
6.90
自引率
27.50%
发文量
115
审稿时长
28 weeks
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