Journal
ENERGY REPORTS
Volume 8, Issue -, Pages 4303-4318Publisher
ELSEVIER
DOI: 10.1016/j.egyr.2022.03.008
Keywords
Functional wind profile; Least squares method; Physical parameters
Categories
Funding
- National Nature Science Foundation of China [51766014]
- National Natural Science Fund of China [52168006]
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This paper establishes testing stations and collects real-time data in the suburban area of Hohhot to study the optimal composite function form of the wind speed profile. The physical significance of each parameter is analyzed, providing a basis for accurate micro-siting of small wind turbines.
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 z(0) meet 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. (C) 2022 The Author(s). Published by Elsevier Ltd.
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