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Wind over complex terrain – Microscale modelling with two types of mesoscale winds at Nygårdsfjell

Author

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  • Bilal, Muhammad
  • Birkelund, Yngve
  • Homola, Matthew
  • Virk, Muhammad Shakeel

Abstract

Nygårdsfjell, a complex terrain near Norwegian-Swedish border, is characterized by its significant wind resources. The feasibility of using mesoscale winds as input to microscale model is studied in this work. The main objective is to take into account the actual terrain effects on wind flow over complex terrain. First set of mesoscale winds are modelled with Weather Research and Forecasting (WRF) numerical tool whereas second set of mesoscale winds are taken from the Modern-Era Retrospective Analysis for Research and Applications (MERRA) data system. WindSim, a computational fluid dynamics based numerical solver is used as microscale modelling tool. The results suggest that the performance of microscale model is largely dependent upon the quality of mesoscale winds as input. The proposed coupled models achieve improvements in wind speed modelling, especially during cold weather. WRF-WindSim coupling showed better results than MERRA-WindSim coupling in all three test cases, as root mean square error (RMSE) decreased by 70.9% for the February case, 61.5% for October and 14.4% for June case respectively. Raw mesoscale winds from the WRF model were also more correct than the mesoscale winds from MERRA data set when extracted directly at the wind turbine by decreasing the RMSE by 62.6% for the February case, 62.7% for October and 23.7% for June case respectively. The difference of RMSE values between the mesoscale winds directly at wind turbine versus the coupled meso-microscale model outputs are not conclusive enough to indicate any specific trend.

Suggested Citation

  • Bilal, Muhammad & Birkelund, Yngve & Homola, Matthew & Virk, Muhammad Shakeel, 2016. "Wind over complex terrain – Microscale modelling with two types of mesoscale winds at Nygårdsfjell," Renewable Energy, Elsevier, vol. 99(C), pages 647-653.
    • Handle: RePEc:eee:renene:v:99:y:2016:i:c:p:647-653
    DOI: 10.1016/j.renene.2016.07.042
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    References listed on IDEAS

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    2. Wu, Chunlei & Luo, Kun & Wang, Qiang & Fan, Jianren, 2022. "A refined wind farm parameterization for the weather research and forecasting model," Applied Energy, Elsevier, vol. 306(PB).
    3. Radünz, William Corrêa & Mattuella, Jussara M. Leite & Petry, Adriane Prisco, 2020. "Wind resource mapping and energy estimation in complex terrain: A framework based on field observations and computational fluid dynamics," Renewable Energy, Elsevier, vol. 152(C), pages 494-515.
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    6. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Characterization of wind resource in China from a new perspective," Energy, Elsevier, vol. 167(C), pages 994-1010.
    7. Ren, Guorui & Wan, Jie & Liu, Jinfu & Yu, Daren, 2019. "Spatial and temporal assessments of complementarity for renewable energy resources in China," Energy, Elsevier, vol. 177(C), pages 262-275.
    8. Renko Buhr & Hassan Kassem & Gerald Steinfeld & Michael Alletto & Björn Witha & Martin Dörenkämper, 2021. "A Multi-Point Meso–Micro Downscaling Method Including Atmospheric Stratification," Energies, MDPI, vol. 14(4), pages 1-22, February.
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    10. Lattawan Niyomtham & Charoenporn Lertsathittanakorn & Jompob Waewsak & Yves Gagnon, 2022. "Mesoscale/Microscale and CFD Modeling for Wind Resource Assessment: Application to the Andaman Coast of Southern Thailand," Energies, MDPI, vol. 15(9), pages 1-19, April.

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