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Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations

Author

Listed:
  • He, J.Y.
  • Chan, P.W.
  • Li, Q.S.
  • Huang, Tao
  • Yim, Steve Hung Lam

Abstract

Urban wind power is an appealing alternative for electricity supply. Comprehensive urban wind resource assessment is a prerequisite for cost-efficient deployment of wind turbines. Based on observations from multiple instruments, including a Doppler lidar (light detection and ranging) system, a microwave radiometer, and a cup anemometer/wind vane set, this study investigates the temporal (interannual, seasonal, and diurnal) variations of wind resources at various heights in a metropolitan city, Hong Kong. The long-term statistical distributions of wind speed, wind shear coefficient, and air density are analyzed, and their variations with height, wind direction, season, and time of day are thoroughly examined. Moreover, the wind power density and capacity factor of prototype wind turbines are estimated. It is observed that the statistical distributions of wind speed and air density are best represented by the Kappa and Normal-Weibull mixture distributions, respectively. There is a significant diurnal variation of wind shear coefficient, from 0.1 in the daytime to 0.4 at night. Moreover, a moderate potential for wind energy harvesting with wind power density of 110 W/m2 is found at the height of 120 m. This is the first known study that jointly uses lidar, microwave radiometer, and anemometer/wind vane for urban wind resource assessment. These instruments enable the investigation of the temporal variations of wind shear coefficient, air density, and wind power density at multiple heights, which were rarely examined in urban wind energy studies before.

Suggested Citation

  • He, J.Y. & Chan, P.W. & Li, Q.S. & Huang, Tao & Yim, Steve Hung Lam, 2024. "Assessment of urban wind energy resource in Hong Kong based on multi-instrument observations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 191(C).
  • Handle: RePEc:eee:rensus:v:191:y:2024:i:c:s1364032123009814
    DOI: 10.1016/j.rser.2023.114123
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