IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v13y2020i15p3896-d392289.html
   My bibliography  Save this article

Numerical and Experimental Study of Topographic Speed-Up Effects in Complex Terrain

Author

Listed:
  • Takanori Uchida

    (Research Institute for Applied Mechanics (RIAM), Kyushu University, 6-1 Kasuga-kouen, Kasuga, Fukuoka 816-8580, Japan)

  • Kenichiro Sugitani

    (Research Institute for Applied Mechanics (RIAM), Kyushu University, 6-1 Kasuga-kouen, Kasuga, Fukuoka 816-8580, Japan)

Abstract

Our research group is developing computational fluid dynamics (CFD)-based software for wind resource and energy production assessments in complex terrain called RIAM-COMPACT (Research Institute for Applied Mechanics, Kyushu University (RIAM)-Computational Prediction of Airflow over Complex Terrain), based on large eddy simulation (LES). In order to verify the prediction accuracy of RIAM-COMPACT, we conduct a wind tunnel experiment that uses a two-dimensional steep ridge model with a smooth surface. In the wind tunnel experiments, airflow measurements are performed using an I-type hot-wire probe and a split film probe that can detect forward and reverse flows. The results of the numerical simulation by LES are in better agreement with the wind tunnel experiment using the split film probe than the results of the wind tunnel experiment using the I-type hot wire probe. Furthermore, we calculate that the two-dimensional ridge model by changing the length in the spanwise direction, and discussed the instantaneous flow field and the time-averaged flow field for the three-dimensional structure of the flow behind the model. It was shown that the eddies in the downwind flow-separated region formed behind the two-dimensional ridge model were almost the same size in all cases, regardless of the difference in the length in the spanwise direction. In this study, we also perform a calculation with a varying inflow shear at the inflow boundary. It was clear that the size in the vortex region behind the model was almost the same in all the calculation results, regardless of the difference in the inflow shear. Next, we conduct wind tunnel experiments on complex terrain. In the wind tunnel experiments using a 1/2800 scale model, the effect of artificial irregularities on the terrain surface did not significantly appear on the airflow at the hub height of the wind turbine. On the other hand, in order to investigate the three-dimensional structure of the airflow in the swept area in detail, it was clearly shown that LES using a high-resolution computational grid is very effective.

Suggested Citation

  • Takanori Uchida & Kenichiro Sugitani, 2020. "Numerical and Experimental Study of Topographic Speed-Up Effects in Complex Terrain," Energies, MDPI, vol. 13(15), pages 1-38, July.
    • Handle: RePEc:gam:jeners:v:13:y:2020:i:15:p:3896-:d:392289
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/13/15/3896/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/13/15/3896/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Dhunny, A.Z. & Lollchund, M.R. & Rughooputh, S.D.D.V., 2017. "Wind energy evaluation for a highly complex terrain using Computational Fluid Dynamics (CFD)," Renewable Energy, Elsevier, vol. 101(C), pages 1-9.
    2. Takanori Uchida, 2018. "Computational Fluid Dynamics (CFD) Investigation of Wind Turbine Nacelle Separation Accident over Complex Terrain in Japan," Energies, MDPI, vol. 11(6), pages 1-13, June.
    3. Takanori Uchida & Susumu Takakuwa, 2019. "A Large-Eddy Simulation-Based Assessment of the Risk of Wind Turbine Failures Due to Terrain-Induced Turbulence over a Wind Farm in Complex Terrain," Energies, MDPI, vol. 12(10), pages 1-19, May.
    4. Jonathon Sumner & Christophe Sibuet Watters & Christian Masson, 2010. "CFD in Wind Energy: The Virtual, Multiscale Wind Tunnel," Energies, MDPI, vol. 3(5), pages 1-25, May.
    5. Asmae El Bahlouli & Alexander Rautenberg & Martin Schön & Kjell zum Berge & Jens Bange & Hermann Knaus, 2019. "Comparison of CFD Simulation to UAS Measurements for Wind Flows in Complex Terrain: Application to the WINSENT Test Site," Energies, MDPI, vol. 12(10), pages 1-21, May.
    6. Takanori Uchida, 2019. "Numerical Investigation of Terrain-Induced Turbulence in Complex Terrain Using High-Resolution Elevation Data and Surface Roughness Data Constructed with a Drone," Energies, MDPI, vol. 12(19), pages 1-20, October.
    7. Takanori Uchida, 2018. "Computational Fluid Dynamics Approach to Predict the Actual Wind Speed over Complex Terrain," Energies, MDPI, vol. 11(7), pages 1-14, June.
    8. Takanori Uchida, 2018. "LES Investigation of Terrain-Induced Turbulence in Complex Terrain and Economic Effects of Wind Turbine Control," Energies, MDPI, vol. 11(6), pages 1-15, June.
    9. Tang, Xiao-Yu & Zhao, Shumian & Fan, Bo & Peinke, Joachim & Stoevesandt, Bernhard, 2019. "Micro-scale wind resource assessment in complex terrain based on CFD coupled measurement from multiple masts," Applied Energy, Elsevier, vol. 238(C), pages 806-815.
    10. Murthy, K.S.R. & Rahi, O.P., 2017. "A comprehensive review of wind resource assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 72(C), pages 1320-1342.
    11. Takanori Uchida & Yasushi Kawashima, 2019. "New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence," Energies, MDPI, vol. 12(13), pages 1-27, July.
    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. Susumu Takakuwa & Takanori Uchida, 2022. "Improvement of Airflow Simulation by Refining the Inflow Wind Direction and Applying Atmospheric Stability for Onshore and Offshore Wind Farms Affected by Topography," Energies, MDPI, vol. 15(14), pages 1-27, July.
    2. Takanori Uchida & Susumu Takakuwa, 2020. "Numerical Investigation of Stable Stratification Effects on Wind Resource Assessment in Complex Terrain," Energies, MDPI, vol. 13(24), pages 1-32, December.

    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. Takanori Uchida, 2019. "Numerical Investigation of Terrain-Induced Turbulence in Complex Terrain Using High-Resolution Elevation Data and Surface Roughness Data Constructed with a Drone," Energies, MDPI, vol. 12(19), pages 1-20, October.
    2. Takanori Uchida & Yasushi Kawashima, 2019. "New Assessment Scales for Evaluating the Degree of Risk of Wind Turbine Blade Damage Caused by Terrain-Induced Turbulence," Energies, MDPI, vol. 12(13), pages 1-27, July.
    3. Takanori Uchida & Susumu Takakuwa, 2019. "A Large-Eddy Simulation-Based Assessment of the Risk of Wind Turbine Failures Due to Terrain-Induced Turbulence over a Wind Farm in Complex Terrain," Energies, MDPI, vol. 12(10), pages 1-19, May.
    4. Takanori Uchida & Susumu Takakuwa, 2020. "Numerical Investigation of Stable Stratification Effects on Wind Resource Assessment in Complex Terrain," Energies, MDPI, vol. 13(24), pages 1-32, December.
    5. Takanori Uchida, 2018. "Numerical Investigation of Terrain-Induced Turbulence in Complex Terrain by Large-Eddy Simulation (LES) Technique," Energies, MDPI, vol. 11(10), pages 1-15, October.
    6. Takanori Uchida, 2020. "Effects of Inflow Shear on Wake Characteristics of Wind-Turbines over Flat Terrain," Energies, MDPI, vol. 13(14), pages 1-31, July.
    7. Takanori Uchida & Tadasuke Yoshida & Masaki Inui & Yoshihiro Taniyama, 2021. "Doppler Lidar Investigations of Wind Turbine Near-Wakes and LES Modeling with New Porous Disc Approach," Energies, MDPI, vol. 14(8), pages 1-33, April.
    8. Takanori Uchida & Yoshihiro Taniyama & Yuki Fukatani & Michiko Nakano & Zhiren Bai & Tadasuke Yoshida & Masaki Inui, 2020. "A New Wind Turbine CFD Modeling Method Based on a Porous Disk Approach for Practical Wind Farm Design," Energies, MDPI, vol. 13(12), pages 1-27, June.
    9. Koichi Watanabe & Yuji Ohya & Takanori Uchida, 2019. "Power Output Enhancement of a Ducted Wind Turbine by Stabilizing Vortices around the Duct," Energies, MDPI, vol. 12(16), pages 1-17, August.
    10. Akintayo T. Abolude & Wen Zhou, 2018. "A Comparative Computational Fluid Dynamic Study on the Effects of Terrain Type on Hub-Height Wind Aerodynamic Properties," Energies, MDPI, vol. 12(1), pages 1-14, December.
    11. 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.
    12. Yang, Lin & Rojas, Jose I. & Montlaur, Adeline, 2020. "Advanced methodology for wind resource assessment near hydroelectric dams in complex mountainous areas," Energy, Elsevier, vol. 190(C).
    13. 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).
    14. Sarah Jamal Mattar & Mohammad Reza Kavian Nezhad & Michael Versteege & Carlos F. Lange & Brian A. Fleck, 2021. "Validation Process for Rooftop Wind Regime CFD Model in Complex Urban Environment Using an Experimental Measurement Campaign," Energies, MDPI, vol. 14(9), pages 1-19, April.
    15. Shaohui Li & Xuejin Sun & Riwei Zhang & Chuanliang Zhang, 2019. "A Feasibility Study of Simulating the Micro-Scale Wind Field for Wind Energy Applications by NWP/CFD Model with Improved Coupling Method and Data Assimilation," Energies, MDPI, vol. 12(13), pages 1-19, July.
    16. Ismail Kamdar & Shahid Ali & Juntakan Taweekun & Hafiz Muhammad Ali, 2021. "Wind Farm Site Selection Using WAsP Tool for Application in the Tropical Region," Sustainability, MDPI, vol. 13(24), pages 1-25, December.
    17. Yan, Bowen & Shen, Ruifang & Li, Ke & Wang, Zhenguo & Yang, Qingshan & Zhou, Xuhong & Zhang, Le, 2023. "Spatio-temporal correlation for simultaneous ultra-short-term wind speed prediction at multiple locations," Energy, Elsevier, vol. 284(C).
    18. Arteaga-López, Ernesto & Angeles-Camacho, César, 2021. "Innovative virtual computational domain based on wind rose diagrams for micrositing small wind turbines," Energy, Elsevier, vol. 220(C).
    19. Takanori Uchida, 2018. "Computational Fluid Dynamics Approach to Predict the Actual Wind Speed over Complex Terrain," Energies, MDPI, vol. 11(7), pages 1-14, June.
    20. Gürdal Ertek & Lakshmi Kailas, 2021. "Analyzing a Decade of Wind Turbine Accident News with Topic Modeling," Sustainability, MDPI, vol. 13(22), pages 1-34, 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:gam:jeners:v:13:y:2020:i:15:p:3896-:d:392289. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.