首页> 外文期刊>Renewable energy >Mapping the wind resource over UK cities
【24h】

Mapping the wind resource over UK cities

机译:绘制英国城市的风能资源图

获取原文
获取原文并翻译 | 示例
       

摘要

Decentralised energy sources, such as small-scale-wind energy, have a number of well-known advantages. However, within urban areas, the potential for energy generation from the wind is not currently fully utilised. One of the most significant reasons for this is that the complexity of air flows within the urban boundary layer makes accurate predictions of the wind resource difficult to achieve. Without sufficiently accurate methods of predicting this resource, there is a danger that wind turbines will either be installed at unsuitable locations or that many viable sites will be overlooked. In this paper, we compare the accuracy of three different analytical methodologies for predicting above-roof mean wind speeds across a number of UK cities. The first is based upon a methodology developed by the UK Meteorological Office. We then implement two more complex methods which utilise maps of surface aerodynamic parameters derived from detailed building data. The predictions are compared with measured mean wind speeds from a wide variety of UK urban locations. The results show that the methodologies are generally more accurate when more complexity is used in the approach, particularly for the sites which are well exposed to the wind. The best agreement with measured data is achieved when the influence of wind direction is thoroughly considered and aerodynamic parameters are derived from detailed building data. However, some uncertainties in the building data add to the errors inherent within the methodologies. Consequently, it is suggested that a detailed description of both the shapes and heights of the local building roofs is required to maximise the accuracy of wind speed predictions.
机译:分散能源,例如小规模风能,具有许多众所周知的优势。但是,在城市地区,目前尚未充分利用风能发电的潜力。造成这种情况的最重要原因之一是,城市边界层内气流的复杂性使得难以准确预测风资源。如果没有足够准确的方法来预测这种资源,则存在将风力涡轮机安装在不合适的位置或忽视许多可行地点的危险。在本文中,我们比较了三种不同分析方法的准确性,这些方法可用于预测英国许多城市的屋顶平均风速。第一种是基于英国气象局开发的方法。然后,我们实施两种更复杂的方法,这些方法利用从详细建筑数据中得出的表面空气动力学参数图。将这些预测与来自英国各种城市地点的测得的平均风速进行比较。结果表明,在该方法中使用更复杂的方法时,尤其是对于暴露在风中的场所,方法通常更准确。充分考虑风向的影响,并从详细的建筑数据中得出空气动力学参数,即可获得与测量数据的最佳一致性。但是,建筑数据中的一些不确定性增加了方法内部固有的误差。因此,建议需要详细描述本地建筑物屋顶的形状和高度,以最大程度地提高风速预测的准确性。

著录项

  • 来源
    《Renewable energy》 |2013年第7期|202-211|共10页
  • 作者单位

    Energy Research Institute, University of Leeds, Leeds LS2 9JT, UK,Energy Technology and Innovation Initiative (ETII), University of Leeds, Leeds LS2 9JT, UK;

    Energy Research Institute, University of Leeds, Leeds LS2 9JT, UK;

    Energy Technology and Innovation Initiative (ETII), University of Leeds, Leeds LS2 9JT, UK;

    Energy Technology and Innovation Initiative (ETII), University of Leeds, Leeds LS2 9JT, UK;

    Energy Technology and Innovation Initiative (ETII), University of Leeds, Leeds LS2 9JT, UK;

  • 收录信息 美国《科学引文索引》(SCI);美国《工程索引》(EI);
  • 原文格式 PDF
  • 正文语种 eng
  • 中图分类
  • 关键词

    building mounted wind turbine; micro-generation; wind resource assessment; small-scale-wind; urban wind energy;

    机译:固定式风力发电机微型发电风资源评估;小规模风城市风能;

相似文献

  • 外文文献
  • 中文文献
  • 专利
获取原文

客服邮箱:kefu@zhangqiaokeyan.com

京公网安备:11010802029741号 ICP备案号:京ICP备15016152号-6 六维联合信息科技 (北京) 有限公司©版权所有
  • 客服微信

  • 服务号