广西风速资源的时空分布特征分析
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1.广西师范学院;2.广西壮族自治区气象减灾研究所

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K909

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北部湾环境演变与资源利用教育部重点实验室(广西师范学院)和广西地表过程与智能模拟重点实验室(广西师范学院)开放或系统基金(项目编号:GTEU-KLOP-K1702)


Analysis on Temporal and Spatial Distribution Characteristics of Wind Resources in Guangxi
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Guangxi Teachers Education University

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    摘要:

    选取广西1971~2015年91气象站点风速数据,辅以DEM与遥感本底信息数据,运用气候学方法和指数空间推算法,构建广西不同时间尺度的风速资源空间分析模型,模拟广西近地层年均、季度风速,利用交叉验证法进行对比验证,选出较高精度的模拟结果,分析广西风速资源时空分布特征。研究结果表明,基于指数空间推算法的风速空间分析模型,综合考虑海拔高度及下垫面类型等因素的影响,可模拟精度较高的风速资源分布情况。广西近地表风能资源丰富区主要位于钦州市、防城港市、北海市等沿海一带以及由大山脉的主脉与周围大片谷地构成的地形区,且该区域春季风速较高,冬季次之,秋夏季最低。

    Abstract:

    Selecting the wind speed data of Guangxi meteorological stations from 1971 to 2015, supplemented by DEM and remote sensing background information data, using climatological method and index spatial predicted method, a spatial analysis model of wind speed resources of different time scales in Guangxi is constructed, which simulates the annual and quarterly wind speed in the near stratum of Guangxi, and compares and verifies by cross validation method, and selects higher accuracy. Based on the simulation results, the temporal and spatial distribution characteristics of wind speed resources in Guangxi are analyzed.The results show that the wind speed spatial analysis model based on index spatial predicted method method can simulate the distribution of wind speed resources with high precision considering the influence of altitude and the type of underlying surface.The rich areas of wind energy resources near the surface of Guangxi are mainly located in the coastal areas of Qinzhou City, Fangchenggang City, Beihai City and other coastal areas, as well as the topographic areas composed of the main veins of the great mountains and the surrounding large valleys. The wind speed in this region is higher in spring, followed by the wind speed in winter. Autumn and summer are the lowest.

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引用本文

蒙良莉,莫建飞,陈燕丽,等. 广西风速资源的时空分布特征分析[J]. 科学技术与工程, 2019, 19(21): 71-78.
MengLiangLi,, and. Analysis on Temporal and Spatial Distribution Characteristics of Wind Resources in Guangxi[J]. Science Technology and Engineering,2019,19(21):71-78.

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  • 收稿日期:2018-11-13
  • 最后修改日期:2019-02-24
  • 录用日期:2019-03-13
  • 在线发布日期: 2019-08-08
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