基于GIS的小尺度城市近地风风力模拟研究
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摘要
在城市的近地风场研究中,盛行的大尺度风向和地形因素往往会成为主要的影响,目前大多数研究都是通过各种不同的插值法来实现风力资源的评估,但是忽略了近地风场的复杂性不能通过单一数学模型来进行,因此本文提出使用克里金插值法和Wind Effect两种数学模型进行模拟研究。本次研究通过气象站数据的克里金插值,输出无地形影响的风力风向的栅格数据,然后通过Wind Effect算法得出风力栅格图。
In the study of urban near-field wind fields, the prevailing large-scale wind direction and topographic factors tend to be the main influences. At present, most studies use different interpolation methods to achieve wind resource assessment, but ignore the near-field complexity of the wind field cannot be performed by a single mathematical model. Therefore, this paper proposes to use the Kriging interpolation method and the Wind Effect two mathematical models for simulation research. In this study, the Kriging interpolation of the weather station data is used to output the raster data of the wind direction without terrain influence, and then the wind raster map is obtained by the Wind Effect algorithm.
In the study of urban near-field wind fields, the prevailing large-scale wind direction and topographic factors tend to be the main influences. At present, most studies use different interpolation methods to achieve wind resource assessment, but ignore the near-field complexity of the wind field cannot be performed by a single mathematical model. Therefore, this paper proposes to use the Kriging interpolation method and the Wind Effect two mathematical models for simulation research. In this study, the Kriging interpolation of the weather station data is used to output the raster data of the wind direction without terrain influence, and then the wind raster map is obtained by the Wind Effect algorithm.
引文
[1]史同广,闫业超,王林林,王智勇.基于DEM的大尺度季风风速空间分布模拟研究[J].地理与地理信息科学, 2007(02):26-29.
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[3]张超,罗伯良.基于GIS技术的湖南风能资源精细化评估[J].湖南电力, 2011, 31(03):11-14.
[4]唐矗,洪冠新.基于地形高程数据的复杂地形风场建模方法[J].北京航空航天大学学报, 2014, 40(03):360-364.
[5]冯俊军,王恩元,沈荣喜,李学龙,朱亚飞,景林波.基于克里金插值法的煤体应力场分布规律研究[J].煤炭科学技术,2013, 41(02):38-41.
[6]王玉璟.空间插值算法的研究及其在空气质量监测中的应用[D].开封:河南大学, 2010:6-19.
[7] Boehner, J., Antonic, O. Land-surface parameters specific to topoclimatology. In:Hengl, T., Reuter, H.[Eds.]:Geomorphometry–Concepts,Software, Applications. Developments in Soil Science, 2009, Volume33, p. 195-226, Elsevier.
[2]高阳华,王堰,邱新法,陈志军,陈艳英,马力,缪启龙,王中.基于GIS的复杂地形风能资源模拟研究[J].太阳能学报,2008(02):163-169.
[3]张超,罗伯良.基于GIS技术的湖南风能资源精细化评估[J].湖南电力, 2011, 31(03):11-14.
[4]唐矗,洪冠新.基于地形高程数据的复杂地形风场建模方法[J].北京航空航天大学学报, 2014, 40(03):360-364.
[5]冯俊军,王恩元,沈荣喜,李学龙,朱亚飞,景林波.基于克里金插值法的煤体应力场分布规律研究[J].煤炭科学技术,2013, 41(02):38-41.
[6]王玉璟.空间插值算法的研究及其在空气质量监测中的应用[D].开封:河南大学, 2010:6-19.
[7] Boehner, J., Antonic, O. Land-surface parameters specific to topoclimatology. In:Hengl, T., Reuter, H.[Eds.]:Geomorphometry–Concepts,Software, Applications. Developments in Soil Science, 2009, Volume33, p. 195-226, Elsevier.