Department of Civil, Environmental and Geodetic Engineering, The Ohio State University, Columbus, Ohio, USA.
PLoS One. 2013;8(2):e56036. doi: 10.1371/journal.pone.0056036. Epub 2013 Feb 8.
The location of a wind turbine is critical to its power output, which is strongly affected by the local wind field. Turbine operators typically seek locations with the best wind at the lowest level above ground since turbine height affects installation costs. In many urban applications, such as small-scale turbines owned by local communities or organizations, turbine placement is challenging because of limited available space and because the turbine often must be added without removing existing infrastructure, including buildings and trees. The need to minimize turbine hazard to wildlife compounds the challenge. We used an exclusion zone approach for turbine-placement optimization that incorporates spatially detailed maps of wind distribution and wildlife densities with power output predictions for the Ohio State University campus. We processed public GIS records and airborne lidar point-cloud data to develop a 3D map of all campus buildings and trees. High resolution large-eddy simulations and long-term wind climatology were combined to provide land-surface-affected 3D wind fields and the corresponding wind-power generation potential. This power prediction map was then combined with bird survey data. Our assessment predicts that exclusion of areas where bird numbers are highest will have modest effects on the availability of locations for power generation. The exclusion zone approach allows the incorporation of wildlife hazard in wind turbine siting and power output considerations in complex urban environments even when the quantitative interaction between wildlife behavior and turbine activity is unknown.
风力涡轮机的位置对其输出功率至关重要,而输出功率又受到当地风场的强烈影响。风力涡轮机运营商通常会选择在地面以上最低处风力最大的位置,因为涡轮机的高度会影响安装成本。在许多城市应用中,例如由当地社区或组织拥有的小型风力涡轮机,由于可用空间有限,而且通常必须在不拆除现有基础设施(包括建筑物和树木)的情况下添加涡轮机,因此涡轮机的放置位置具有挑战性。需要将涡轮机对野生动物的危害降到最低,这增加了挑战的难度。我们使用了一种排除区方法来优化涡轮机的放置位置,该方法将详细的风分布图和野生动物密度图与俄亥俄州立大学校园的功率输出预测相结合。我们处理了公共 GIS 记录和机载激光雷达点云数据,以开发一个包含所有校园建筑物和树木的 3D 地图。高分辨率大涡模拟和长期风气候学被结合起来,以提供受地面影响的 3D 风场和相应的风力发电潜力。然后,将这个功率预测图与鸟类调查数据结合起来。我们的评估预测,排除鸟类数量最高的区域对发电地点的可用性影响不大。即使野生动物行为和涡轮机活动之间的定量相互作用未知,排除区方法也允许在复杂的城市环境中,将野生动物危害纳入风力涡轮机选址和功率输出考虑因素。