This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Original article
wang Wenxin
Inner Mongolia University of Technology
Corresponding Author
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background：Given the increasing trend of using wind energy in cities, the utilization of distributed wind energy in cities has been widely concerned by researchers. The related research on the micro-site selection of wind turbines, a sub-project of the Task27 project of the International energy agency, was continued in this paper.
Methods：The wind speed data of an observation station near Hohhot, Inner Mongolia, with a range of 10-19 m were collected. The evaluation included wind direction, Weibull parameter characteristics, and turbulence intensity. The potential energy output in 10 different heights was estimated using commercial horizontal and vertical axis wind turbines of the same power.
Results：The three-parameter Weibull distribution model can well describe the statistical properties of the wind speed in this site. The wind speed distribution model constructed from extrapolation parameters reflects the wind speed statistical properties out of detection positions to a certain extent.
Conclusions：The wind energy density of the vertical axis wind turbine is slightly lower than that of the horizontal axis wind turbine. Furthermore, more power can be generated from March to May.
Keywords
Wind energy potential, Urban suburbs, Evaluation of wind resource, Extrapolated wind speed probability distribution, Turbulence in the Suburbs of a city
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This is a preprint, a preliminary version of a manuscript that has not completed peer review at a journal. Research Square does not conduct peer review prior to posting preprints. The posting of a preprint on this server should not be interpreted as an endorsement of its validity or suitability for dissemination as established information or for guiding clinical practice.
Original article
wang Wenxin
Inner Mongolia University of Technology
Corresponding Author
Badges
Prescreen
This manuscript passed our Prescreen assessment
Complete author information
Appropriate declaration statements
Potential risks to human health
Prescreen
History
CURRENT STATUS: Posted
Version 1
Posted 07 Dec, 2020
No community comments so far
Metrics
Comments: 0
PDF Downloads: ...
HTML Views: ...
Subject Areas
Energy Engineering
License:
This work is licensed under a CC BY 4.0 License. Read Full License
Background：Given the increasing trend of using wind energy in cities, the utilization of distributed wind energy in cities has been widely concerned by researchers. The related research on the micro-site selection of wind turbines, a sub-project of the Task27 project of the International energy agency, was continued in this paper.
Methods：The wind speed data of an observation station near Hohhot, Inner Mongolia, with a range of 10-19 m were collected. The evaluation included wind direction, Weibull parameter characteristics, and turbulence intensity. The potential energy output in 10 different heights was estimated using commercial horizontal and vertical axis wind turbines of the same power.
Results：The three-parameter Weibull distribution model can well describe the statistical properties of the wind speed in this site. The wind speed distribution model constructed from extrapolation parameters reflects the wind speed statistical properties out of detection positions to a certain extent.
Conclusions：The wind energy density of the vertical axis wind turbine is slightly lower than that of the horizontal axis wind turbine. Furthermore, more power can be generated from March to May.
Figure 1
Figure 2
Figure 3
Figure 4
Figure 5
Figure 6
Figure 7
Figure 8
Figure 9
Figure 10
Figure 11
Figure 12
Figure 13
Figure 14
Figure 15
Figure 16
Figure 17
Figure 18
Figure 19
Figure 20
Figure 21
Figure 22
The full text of this article is available to read as a PDF.
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