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A new meso-microscale coupled modelling framework for wind resource assessment: A validation study

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  • Durán, Pablo
  • Meiβner, Cathérine
  • Casso, Pau

Abstract

In this work the simulation results of a newly developed meso-microscale coupling methodology suited for steady-state computational fluid dynamic models (CFD) are compared with mesoscale and standalone microscale simulations at 5 sites. The coupling methodology uses averaged fields of wind speed and potential temperature simulated by the Weather Research and Forecasting model as boundary and initial conditions for the CFD model. In complex terrain, the coupled model reproduces the measured vertical profiles of horizontal wind speed better than the standalone microscale model or the mesoscale model. The coupled model also performs better in the horizontal extrapolation of measurements in complex terrain. In simpler terrain, it is beneficial to use the coupled model when the focus is on areas located downstream of even small terrain features. Otherwise, the mesoscale simulations perform as good or better than the coupled model.

Suggested Citation

  • Durán, Pablo & Meiβner, Cathérine & Casso, Pau, 2020. "A new meso-microscale coupled modelling framework for wind resource assessment: A validation study," Renewable Energy, Elsevier, vol. 160(C), pages 538-554.
    • Handle: RePEc:eee:renene:v:160:y:2020:i:c:p:538-554
    DOI: 10.1016/j.renene.2020.06.074
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    References listed on IDEAS

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    2. Demetri Bouris & Athanasios G. Triantafyllou & Athina Krestou & Elena Leivaditou & John Skordas & Efstathios Konstantinidis & Anastasios Kopanidis & Qing Wang, 2021. "Urban-Scale Computational Fluid Dynamics Simulations with Boundary Conditions from Similarity Theory and a Mesoscale Model," Energies, MDPI, vol. 14(18), pages 1-22, September.
    3. Cheng, Xu & Yan, Bowen & Zhou, Xuhong & Yang, Qingshan & Huang, Guoqing & Su, Yanwen & Yang, Wei & Jiang, Yan, 2024. "Wind resource assessment at mountainous wind farm: Fusion of RANS and vertical multi-point on-site measured wind field data," Applied Energy, Elsevier, vol. 363(C).
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