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Multi-lidar wind resource mapping in complex terrain

机译:复杂地形中的多激光器风资源映射

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Scanning Doppler lidars have great potential for reducing uncertainty of wind resource estimation in complex terrain. Due to their scanning capabilities, they can measure at multiple locations over large areas. We demonstrate this ability with dual-Doppler lidar measurements of flow over two parallel ridges. The data have been collected using two pairs of scanning lidars operated in a dual-Doppler mode during the Perdig?o?2017 measurement campaign. There the scanning lidars mapped the flow 80 m above ground level along two ridges, which are considered favorable for wind turbine siting. The measurements are validated with sonic wind measurements at each ridge. By analyzing the collected data, we found that wind speeds are on average 10 % higher over the southwest ridge compared to the northeast ridge. At the southwest ridge, the data show, for approach flow normal to the ridge, a change of 20 % in wind speed along the ridge. Fine differences like these are difficult to reproduce with computational flow models, as we demonstrate by comparing the lidar measurements with Weather Research and Forecasting large-eddy simulation?(WRF-LES) results. For the measurement period, we have simulated the flow over the site using WRF-LES to compare how well the model can capture wind resources along the ridges. We used two model configurations. In the first configuration, surface drag is based purely on aerodynamic roughness, whereas in the second configuration forest canopy drag is also considered. We found that simulated winds are underestimated in WRF-LES runs with forest drag due to an unrealistic forest distribution on the ridge tops. The correlation of simulated and observed winds is, however, improved when the forest parameterization is applied. WRF-LES results without forest drag overestimated the wind resources over the southwest and northeast ridges by 6.5 % and 4.5 %, respectively. Overall, this study demonstrates the ability of scanning lidars to map wind resources in complex terrain.
机译:扫描多普勒利达雷达尔有很大的潜力,可降低复杂地形中风力资源估计的不确定性。由于它们的扫描功能,它们可以在大区域的多个位置测量。我们展示了这种能力,双多普勒激光雷达在两个平行脊上的流量测量。在Perdig期间使用在双多普勒模式下操作的两对扫描引线仪收集数据?2017年测量运动。在那里,扫描引线沿着两个脊映射到地面上方的流量80m,这被认为是有利于风力涡轮机选址的。测量用每个脊的声音风测量验证。通过分析收集的数据,我们发现,与东北山脊相比,西南脊的风速平均较高10%。在西南山脊,数据显示,用于对脊的垂直流动流动,沿着脊的风速变化20%。与计算流程模型相比,这些差异很难再现,因为我们通过将LIDAR测量与天气研究和预测大涡模拟进行了比较了潮流仪(WRF-LES)结果。对于测量期,我们使用WRF-LES模拟了网站上的流量,以比较模型可以沿着脊捕获风力资源的程度。我们使用了两个模型配置。在第一种配置中,表面拖动纯粹基于空气动力学粗糙度,而在第二配置林层中也考虑过林冠层。我们发现,由于脊顶上的不切实际的森林分布,在WRF-LES中低估了模拟风。然而,模拟和观测的风的相关性在应用森林参数化时改善。没有森林拖累的WRF-les结果将在西南和东北山脊上高估了6.5%和4.5%的风力资源。总体而言,本研究表明扫描Lidars在复杂地形中映射风力资源的能力。

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