Wind and Structures

  • 제20권1호
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  • Pages.59-74
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  • 2015
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  • 1226-6116(pISSN)
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  • 1598-6225(eISSN)
테크노프레스 (Techno-Press)
권호 표지
DOI QR코드

DOI QR Code

Refined numerical simulation in wind resource assessment

  • Cheng, Xue-Ling (State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences) ;
  • Li, Jun (State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences) ;
  • Hu, Fei (State Key Laboratory of Atmospheric Boundary Layer Physics and Atmospheric Chemistry, Institute of Atmospheric Physics, Chinese Academy of Sciences) ;
  • Xu, Jingjing (International Center for Climate and Environment Sciences, Institute of Atmospheric Physics, Chinese Academy of Sciences) ;
  • Zhu, Rong (Public Weather Service Center China Meteorological Administration)
  • 투고 : 2014.07.08
  • 심사 : 2014.11.27
  • 발행 : 2015.01.25
⟨ 이전 논문 다음 논문 ⟩

초록

A coupled model system for Wind Resource Assessment (WRA) was studied. Using a mesoscale meteorological model, the Weather Research and Forecasting (WRF) model, global-scale data were downscaled to the inner nested grid scale (typically a few kilometers), and then through the coupling Computational Fluid Dynamics (CFD) mode, FLUENT. High-resolution results (50 m in the horizontal direction; 10 m in the vertical direction below 150 m) of the wind speed distribution data and ultimately refined wind farm information, were obtained. The refined WRF/FLUENT system was then applied to assess the wind resource over complex terrain in the northern Poyang Lake region. The results showed that the approach is viable for the assessment of wind energy.

키워드

과제정보

연구 과제번호 : Refined Numerical Simulation of wind farm base on CFD downscaling method

연구 과제 주관 기관 : National Natural Science Foundation of China

참고문헌

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피인용 문헌

  1. Spatial correlation-based WRF observation-nudging approach in simulating regional wind field vol.28, pp.2, 2015, https://doi.org/10.12989/was.2019.28.2.129
  2. Nonlinear Kalman filter bias correction for wind ramp event forecasts at wind turbine height vol.30, pp.4, 2015, https://doi.org/10.12989/was.2020.30.4.393
  3. Improving the Near-Surface Wind Forecast around the Turpan Basin of the Northwest China by Using the WRF_TopoWind Model vol.12, pp.12, 2015, https://doi.org/10.3390/atmos12121624