Artikel

Campus wind environment evaluation in north China: A case study of NCUT

Wind environment research in the populated urban area is an important topic on wind potential evaluation as well as wind comfort analysis. This study took measurement of 57 crossroad spots in the campus in North China University of Technology in Beijing. The data of wind speed and direction were measured at fixed time and fixed place. The spots of static wind zone, wake flow zone and risky zone were examined. The overall measured data in wind scale map was analyzed to find out the changes of wind speed and direction in different seasons and in different locations of the school. Research and analysis show that the overall wind environment of the campus at pedestrian level is in fair comfort: the average wind speed is between 0.04-4.8 m/s, though the overall frequency of campus wind comfort location measurement is not high. In addition, CFD simulations were undertaken in order to help identifying the wind risky points as well as wind potential at a high altitude. Three high-rise buildings were found with exploitable wind energy over roof. Averaged wind velocity on floor plan at 6m and 10m above roof were mostly bigger than 3m/s, which is favorable condition for wind energy exploitation. However, further detailed evaluation is necessary for the wind turbine installation position as there is much varieties on the evaluation level, building roof area and velocity distribution of each building.

Language
Englisch

Bibliographic citation
Journal: Energy Reports ; ISSN: 2352-4847 ; Volume: 6 ; Year: 2020 ; Issue: 1 ; Pages: 787-793 ; Amsterdam: Elsevier

Classification
Wirtschaft
Subject
Campus environment
CFD simulation
Wind energy potential
Wind environment

Event
Geistige Schöpfung
(who)
Wang, B.
Sun, S.
Li, Y.
Xie, Y. N.
Hou, Y. X.
Jin, Q. T.
Ren, Y. Y.
Event
Veröffentlichung
(who)
Elsevier
(where)
Amsterdam
(when)
2020

DOI
doi:10.1016/j.egyr.2019.11.003
Handle
Last update
10.03.2025, 11:41 AM CET

Data provider

This object is provided by:
ZBW - Deutsche Zentralbibliothek für Wirtschaftswissenschaften - Leibniz-Informationszentrum Wirtschaft. If you have any questions about the object, please contact the data provider.

Object type

  • Artikel

Associated

  • Wang, B.
  • Sun, S.
  • Li, Y.
  • Xie, Y. N.
  • Hou, Y. X.
  • Jin, Q. T.
  • Ren, Y. Y.
  • Elsevier

Time of origin

  • 2020

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