IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v160y2020icp538-554.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120309848
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2020.06.074?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Shives, Michael & Crawford, Curran, 2016. "Adapted two-equation turbulence closures for actuator disk RANS simulations of wind & tidal turbine wakes," Renewable Energy, Elsevier, vol. 92(C), pages 273-292.
    2. Javier Sanz Rodrigo & Roberto Aurelio Chávez Arroyo & Patrick Moriarty & Matthew Churchfield & Branko Kosović & Pierre‐Elouan Réthoré & Kurt Schaldemose Hansen & Andrea Hahmann & Jeffrey D. Mirocha & , 2017. "Mesoscale to microscale wind farm flow modeling and evaluation," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 6(2), March.
    3. Archer, Cristina L. & Vasel-Be-Hagh, Ahmadreza & Yan, Chi & Wu, Sicheng & Pan, Yang & Brodie, Joseph F. & Maguire, A. Eoghan, 2018. "Review and evaluation of wake loss models for wind energy applications," Applied Energy, Elsevier, vol. 226(C), pages 1187-1207.
    4. Peter Bachant & Martin Wosnik, 2016. "Effects of Reynolds Number on the Energy Conversion and Near-Wake Dynamics of a High Solidity Vertical-Axis Cross-Flow Turbine," Energies, MDPI, vol. 9(2), pages 1-18, January.
    5. 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.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. 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.
    2. Castorrini, Alessio & Gentile, Sabrina & Geraldi, Edoardo & Bonfiglioli, Aldo, 2023. "Investigations on offshore wind turbine inflow modelling using numerical weather prediction coupled with local-scale computational fluid dynamics," Renewable and Sustainable Energy Reviews, Elsevier, vol. 171(C).
    3. Yildiz, Anil & Mern, John & Kochenderfer, Mykel J. & Howland, Michael F., 2023. "Towards sequential sensor placements on a wind farm to maximize lifetime energy and profit," Renewable Energy, Elsevier, vol. 216(C).

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. 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.
    2. 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.
    3. Gauvin-Tremblay, Olivier & Dumas, Guy, 2022. "Hydrokinetic turbine array analysis and optimization integrating blockage effects and turbine-wake interactions," Renewable Energy, Elsevier, vol. 181(C), pages 851-869.
    4. 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.
    5. Cao, Lichao & Ge, Mingwei & Gao, Xiaoxia & Du, Bowen & Li, Baoliang & Huang, Zhi & Liu, Yongqian, 2022. "Wind farm layout optimization to minimize the wake induced turbulence effect on wind turbines," Applied Energy, Elsevier, vol. 323(C).
    6. Pollini, Nicolò, 2022. "Topology optimization of wind farm layouts," Renewable Energy, Elsevier, vol. 195(C), pages 1015-1027.
    7. Abdullah Al-Shereiqi & Amer Al-Hinai & Mohammed Albadi & Rashid Al-Abri, 2021. "Optimal Sizing of Hybrid Wind-Solar Power Systems to Suppress Output Fluctuation," Energies, MDPI, vol. 14(17), pages 1-16, August.
    8. 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.
    9. Radünz, William Corrêa & de Almeida, Everton & Gutiérrez, Alejandro & Acevedo, Otávio Costa & Sakagami, Yoshiaki & Petry, Adriane Prisco & Passos, Júlio César, 2022. "Nocturnal jets over wind farms in complex terrain," Applied Energy, Elsevier, vol. 314(C).
    10. Ali M. H. A. Khajah & Simon P. Philbin, 2022. "Techno-Economic Analysis and Modelling of the Feasibility of Wind Energy in Kuwait," Clean Technol., MDPI, vol. 4(1), pages 1-21, January.
    11. Gu, Bo & Meng, Hang & Ge, Mingwei & Zhang, Hongtao & Liu, Xinyu, 2021. "Cooperative multiagent optimization method for wind farm power delivery maximization," Energy, Elsevier, vol. 233(C).
    12. Clemente Gotelli & Mirko Musa & Michele Guala & Cristián Escauriaza, 2019. "Experimental and Numerical Investigation of Wake Interactions of Marine Hydrokinetic Turbines," Energies, MDPI, vol. 12(16), pages 1-17, August.
    13. Joongjin Shin & Seokheum Baek & Youngwoo Rhee, 2020. "Wind Farm Layout Optimization Using a Metamodel and EA/PSO Algorithm in Korea Offshore," Energies, MDPI, vol. 14(1), pages 1-15, December.
    14. Luis M. López-Manrique & E. V. Macias-Melo & O. May Tzuc & A. Bassam & K. M. Aguilar-Castro & I. Hernández-Pérez, 2018. "Assessment of Resource and Forecast Modeling of Wind Speed through An Evolutionary Programming Approach for the North of Tehuantepec Isthmus (Cuauhtemotzin, Mexico)," Energies, MDPI, vol. 11(11), pages 1-22, November.
    15. Wang, Tengyuan & Cai, Chang & Wang, Xinbao & Wang, Zekun & Chen, Yewen & Song, Juanjuan & Xu, Jianzhong & Zhang, Yuning & Li, Qingan, 2023. "A new Gaussian analytical wake model validated by wind tunnel experiment and LiDAR field measurements under different turbulent flow," Energy, Elsevier, vol. 271(C).
    16. Dimitris Drikakis & Talib Dbouk, 2022. "The Role of Computational Science in Wind and Solar Energy: A Critical Review," Energies, MDPI, vol. 15(24), pages 1-20, December.
    17. Villeneuve, Thierry & Boudreau, Matthieu & Dumas, Guy, 2020. "Improving the efficiency and the wake recovery rate of vertical-axis turbines using detached end-plates," Renewable Energy, Elsevier, vol. 150(C), pages 31-45.
    18. Sun, Haiying & Qiu, Changyu & Lu, Lin & Gao, Xiaoxia & Chen, Jian & Yang, Hongxing, 2020. "Wind turbine power modelling and optimization using artificial neural network with wind field experimental data," Applied Energy, Elsevier, vol. 280(C).
    19. Rafael V. Rodrigues & Corinne Lengsfeld, 2019. "Development of a Computational System to Improve Wind Farm Layout, Part I: Model Validation and Near Wake Analysis," Energies, MDPI, vol. 12(5), pages 1-24, March.
    20. Chuhua Jiang & Xuedao Shu & Junhua Chen & Lingjie Bao & Hao Li, 2020. "Research on Performance Evaluation of Tidal Energy Turbine under Variable Velocity," Energies, MDPI, vol. 13(23), pages 1-14, November.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:renene:v:160:y:2020:i:c:p:538-554. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/renewable-energy .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.