A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot

Since wind energy is a key source of clean energy in suburban areas where multiple energy sources complement each other, it is crucial to be able to accurately predict the inlet boundary of wind turbines in order to transform the efficiency of wind turbines. Therefore, in this paper, by setting up t...

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Main Authors: Wenxin Wang, Yun Xu, Xiaoliang Han, Mingliang Gao, Qi Zhang, Jianwen Wang
Format: Article
Language:English
Published: Elsevier 2022-11-01
Series:Energy Reports
Subjects:
Online Access:http://www.sciencedirect.com/science/article/pii/S2352484722005637
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author Wenxin Wang
Yun Xu
Xiaoliang Han
Mingliang Gao
Qi Zhang
Jianwen Wang
author_facet Wenxin Wang
Yun Xu
Xiaoliang Han
Mingliang Gao
Qi Zhang
Jianwen Wang
author_sort Wenxin Wang
collection DOAJ
description Since wind energy is a key source of clean energy in suburban areas where multiple energy sources complement each other, it is crucial to be able to accurately predict the inlet boundary of wind turbines in order to transform the efficiency of wind turbines. Therefore, in this paper, by setting up testing stations in the suburban area of Hohhot and collecting real-time data of wind speed and wind direction in different measurement heights for three years, and using the least squares method to estimate the parameters of the exponential law, logarithmic law, and composite function model, and conducting various goodness-of-fit tests, the optimal composite function is obtained as the wind profile form in the suburban area of the city, which is named as the Suburban Exponential of Wind profile (SE). And the inter-parameter analysis of this function, using linear regression statistical method to regress between parameters and parameters and between parameters and wind speed, summarize the physical significance of each parameter of this function. Respectively, parameter a is the ultimate wind speed under the vertical height of the region, parameter b is the reference height, parameter c and the roughness length z0meet the linear relationship, and effectively reflect the influence of building dynamics roughness on the vertical distribution of wind speed, to make up for the shortcomings of the traditional wind profile formula, and provide a basis for accurate micro-siting of small wind turbines.
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spelling doaj.art-adef3cfad36c4777bf77f276895c72942023-02-21T05:10:46ZengElsevierEnergy Reports2352-48472022-11-01843034318A study of function-based wind profiles based on least squares method: A case in the suburbs of HohhotWenxin Wang0Yun Xu1Xiaoliang Han2Mingliang Gao3Qi Zhang4Jianwen Wang5College of Civil Engineering, Inner Mongolia University of Technology, Hohhot, China; Correspondence to: School of Civil Engineering, Inner Mongolia University of Technology, Hohhot, China.College of Civil Engineering, Inner Mongolia University of Technology, Hohhot, ChinaInner Mongolia Electric Power Survey and Design Institute Company. LTD, Hohhot, ChinaDesign and Research Institute, Inner Mongolia Architectural Survey, Hohhot, ChinaCollege of Civil Engineering, Inner Mongolia University of Technology, Hohhot, ChinaCollege of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot, ChinaSince wind energy is a key source of clean energy in suburban areas where multiple energy sources complement each other, it is crucial to be able to accurately predict the inlet boundary of wind turbines in order to transform the efficiency of wind turbines. Therefore, in this paper, by setting up testing stations in the suburban area of Hohhot and collecting real-time data of wind speed and wind direction in different measurement heights for three years, and using the least squares method to estimate the parameters of the exponential law, logarithmic law, and composite function model, and conducting various goodness-of-fit tests, the optimal composite function is obtained as the wind profile form in the suburban area of the city, which is named as the Suburban Exponential of Wind profile (SE). And the inter-parameter analysis of this function, using linear regression statistical method to regress between parameters and parameters and between parameters and wind speed, summarize the physical significance of each parameter of this function. Respectively, parameter a is the ultimate wind speed under the vertical height of the region, parameter b is the reference height, parameter c and the roughness length z0meet the linear relationship, and effectively reflect the influence of building dynamics roughness on the vertical distribution of wind speed, to make up for the shortcomings of the traditional wind profile formula, and provide a basis for accurate micro-siting of small wind turbines.http://www.sciencedirect.com/science/article/pii/S2352484722005637Functional wind profileLeast squares methodPhysical parameters
spellingShingle Wenxin Wang
Yun Xu
Xiaoliang Han
Mingliang Gao
Qi Zhang
Jianwen Wang
A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot
Energy Reports
Functional wind profile
Least squares method
Physical parameters
title A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot
title_full A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot
title_fullStr A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot
title_full_unstemmed A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot
title_short A study of function-based wind profiles based on least squares method: A case in the suburbs of Hohhot
title_sort study of function based wind profiles based on least squares method a case in the suburbs of hohhot
topic Functional wind profile
Least squares method
Physical parameters
url http://www.sciencedirect.com/science/article/pii/S2352484722005637
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