Correlation analysis of three-parameter Weibull distribution parameters with wind energy characteristics in a semi-urban environment

被引:19
|
作者
Wang, Wenxin [1 ]
Qin, Chaofan [1 ]
Zhang, Jiuyu [1 ]
Wen, Caifeng [2 ,4 ]
Xu, Guoqiang [3 ]
机构
[1] Inner Mongolia Univ Technol, Sch Civil Engn, Hohhot, Peoples R China
[2] Inner Mongolia Univ Technol, Coll Energy & Power Engn, Hohhot, Peoples R China
[3] Inner Mongolia Univ Technol, Coll Architecture, Hohhot, Peoples R China
[4] Inner Mongolia Autonomous Reg Key Lab Wind & Solar, Hohhot, Peoples R China
关键词
Wind resource assessment; Suburban areas; Three-parameters Weibull distribution; Wind energy characteristics; TURBULENCE INTENSITY; RESOURCE ASSESSMENT; FARM;
D O I
10.1016/j.egyr.2022.06.043
中图分类号
TE [石油、天然气工业]; TK [能源与动力工程];
学科分类号
0807 ; 0820 ;
摘要
Suburban areas are rich in wind resources, but wind energy characteristics are complicated by the strong turbulence disturbance of buildings. Current work on wind resource assessment is focused on the fitting of the wind speed distribution function and the measurement of wind energy abundance. The mathematical relationship between the distribution function and the main wind energy characteristics under suburban wind field conditions needs to be studied. In this study, a ZephIR 300 LiDAR wind measurement system is built in a suburban area, and wind speed data samples from heights of 11-199 m are obtained. The functional relationship between parameters is derived through a comparative analysis, which reveals that the variation of shape parameter k in the range of 1.05-1.25 causes abrupt changes in wind power density (WPD). The positive proportional relationship between the scale parameter and WPD and its correlation with height are also obtained. Turbulence intensity (TI) decrease as the scale parameter increases from 1.18 to 2.50 and fluctuates within 10.54% as the scale parameter c continues to increase from 2.50 to 5.58. The scale parameter corresponding to the minimum value of TI at each height is provided. (c) 2022 The Author(s). Published by Elsevier Ltd. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/).
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页码:8480 / 8498
页数:19
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