IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i19p3696-d271445.html
   My bibliography  Save this article

Aerodynamic Performance and Wind-Induced Responses of Large Wind Turbine Systems with Meso-Scale Typhoon Effects

Author

Listed:
  • Shitang Ke

    (Department of Civil Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China
    Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

  • Lu Xu

    (China Energy Engineering Group Guangdong Electric Power Design Institute Co., Ltd., Guangzhou 510663, China)

  • Tongguang Wang

    (Department of Civil Engineering, Nanjing University of Aeronautics and Astronautics, 29 Yudao Road, Nanjing 210016, China
    Jiangsu Key Laboratory of Hi-Tech Research for Wind Turbine Design, Nanjing University of Aeronautics and Astronautics, Nanjing 210016, China)

Abstract

The theoretical system of existing civil engineering typhoon models is too simplified and the simulation accuracy is very low. Therefore, in this work a meso-scale weather forecast model (WRF) based on the non-static Euler equation model was introduced to simulate typhoon “Nuri” with high spatial and temporal resolution, focusing on the comparison of wind direction and wind intensity characteristics before, during and after the landing of the typhoon. Moreover, the effectiveness of the meso-scale typhoon “Nuri” simulation was verified by a comparison between the track of the typhoon center based on minimum sea level pressure and the measured track. In this paper, the aerodynamic performance of large wind turbines under typhoon loads is studied using WRF and CFD nesting technology. A 5 MW wind turbine located in a wind power plant on the southeast coast of China has been chosen as the research object. The average and fluctuating wind pressure distributions as well as airflow around the tower body and eddy distribution on blade and tower surface were compared. A dynamic and time-historical analysis of wind-induced responses under different stop positions was implemented by considering the finite element complete transient method. The influence of the stop position on the wind-induced responses and wind fluttering factor of the system were analyzed. Finally, under a typhoon process, the most unfavorable stop position of the large wind turbine was concluded. The results demonstrated that the internal force and wind fluttering factor of the tower body increased significantly under the typhoon effect. The wind-induced response of the blade closest to the tower body was affected mostly. The wind fluttering factor of this blade was increased by 35%. It was concluded from the analysis that the large wind turbine was stopped during the typhoon. The most unfavorable stop position was at the complete overlapping of the lower blade and the tower body (Condition 1). The safety redundancy reached the maximum when the upper blade overlapped with the tower body completely (Condition 5). Therefore, it is suggested that during typhoons the blade of the wind turbine be rotated to Condition 5.

Suggested Citation

  • Shitang Ke & Lu Xu & Tongguang Wang, 2019. "Aerodynamic Performance and Wind-Induced Responses of Large Wind Turbine Systems with Meso-Scale Typhoon Effects," Energies, MDPI, vol. 12(19), pages 1-24, September.
  • Handle: RePEc:gam:jeners:v:12:y:2019:i:19:p:3696-:d:271445
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/19/3696/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/12/19/3696/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "WRF wind simulation and wind energy production estimates forced by different reanalyses: Comparison with observed data for Portugal," Applied Energy, Elsevier, vol. 117(C), pages 116-126.
    2. Dimitrov, Nikolay & Natarajan, Anand & Mann, Jakob, 2017. "Effects of normal and extreme turbulence spectral parameters on wind turbine loads," Renewable Energy, Elsevier, vol. 101(C), pages 1180-1193.
    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. Cai, Chang & Yang, Yingjian & Jia, Yan & Wu, Guangxing & Zhang, Hairui & Yuan, Feiqi & Qian, Quan & Li, Qing'an, 2023. "Aerodynamic load evaluation of leading edge and trailing edge windward states of large-scale wind turbine blade under parked condition," Applied Energy, Elsevier, vol. 350(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. Xsitaaz T. Chadee & Naresh R. Seegobin & Ricardo M. Clarke, 2017. "Optimizing the Weather Research and Forecasting (WRF) Model for Mapping the Near-Surface Wind Resources over the Southernmost Caribbean Islands of Trinidad and Tobago," Energies, MDPI, vol. 10(7), pages 1-23, July.
    2. Cuevas-Figueroa, Gabriel & Stansby, Peter K. & Stallard, Timothy, 2022. "Accuracy of WRF for prediction of operational wind farm data and assessment of influence of upwind farms on power production," Energy, Elsevier, vol. 254(PB).
    3. Alain Ulazia & Ander Nafarrate & Gabriel Ibarra-Berastegi & Jon Sáenz & Sheila Carreno-Madinabeitia, 2019. "The Consequences of Air Density Variations over Northeastern Scotland for Offshore Wind Energy Potential," Energies, MDPI, vol. 12(13), pages 1-18, July.
    4. Ritter, Matthias & Shen, Zhiwei & López Cabrera, Brenda & Odening, Martin & Deckert, Lars, 2015. "Designing an index for assessing wind energy potential," Renewable Energy, Elsevier, vol. 83(C), pages 416-424.
    5. He, Yuhang & Han, Xingxing & Xu, Chang & Cheng, Zhe & Wang, Jincheng & Liu, Wei & Xu, Dong, 2023. "Sensitivity of simulated wind power under diverse spatial scales and multiple terrains using the weather research and forecasting model," Energy, Elsevier, vol. 285(C).
    6. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegi, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2019. "Global estimations of wind energy potential considering seasonal air density changes," Energy, Elsevier, vol. 187(C).
    7. Dhunny, A.Z. & Timmons, D.S. & Allam, Z. & Lollchund, M.R. & Cunden, T.S.M., 2020. "An economic assessment of near-shore wind farm development using a weather research forecast-based genetic algorithm model," Energy, Elsevier, vol. 201(C).
    8. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2017. "Offshore winds and wind energy production estimates derived from ASCAT, OSCAT, numerical weather prediction models and buoys – A comparative study for the Iberian Peninsula Atlantic coast," Renewable Energy, Elsevier, vol. 102(PB), pages 433-444.
    9. Tuy, Soklin & Lee, Han Soo & Chreng, Karodine, 2022. "Integrated assessment of offshore wind power potential using Weather Research and Forecast (WRF) downscaling with Sentinel-1 satellite imagery, optimal sites, annual energy production and equivalent C," Renewable and Sustainable Energy Reviews, Elsevier, vol. 163(C).
    10. 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).
    11. Carvalho, D. & Rocha, A. & Gómez-Gesteira, M. & Silva Santos, C., 2014. "Sensitivity of the WRF model wind simulation and wind energy production estimates to planetary boundary layer parameterizations for onshore and offshore areas in the Iberian Peninsula," Applied Energy, Elsevier, vol. 135(C), pages 234-246.
    12. Ulazia, Alain & Saenz, Jon & Ibarra-Berastegui, Gabriel, 2016. "Sensitivity to the use of 3DVAR data assimilation in a mesoscale model for estimating offshore wind energy potential. A case study of the Iberian northern coastline," Applied Energy, Elsevier, vol. 180(C), pages 617-627.
    13. Santos, F. & Gómez-Gesteira, M. & deCastro, M. & Añel, J.A. & Carvalho, D. & Costoya, Xurxo & Dias, J.M., 2018. "On the accuracy of CORDEX RCMs to project future winds over the Iberian Peninsula and surrounding ocean," Applied Energy, Elsevier, vol. 228(C), pages 289-300.
    14. González-Alonso de Linaje, N. & Mattar, C. & Borvarán, D., 2019. "Quantifying the wind energy potential differences using different WRF initial conditions on Mediterranean coast of Chile," Energy, Elsevier, vol. 188(C).
    15. Yuan, Renyu & Ji, Wenju & Luo, Kun & Wang, Jianwen & Zhang, Sanxia & Wang, Qiang & Fan, Jianren & Ni, MingJiang & Cen, Kefa, 2017. "Coupled wind farm parameterization with a mesoscale model for simulations of an onshore wind farm," Applied Energy, Elsevier, vol. 206(C), pages 113-125.
    16. D Carvalho & S Cardoso Pereira & A Rocha, 2021. "Future surface temperatures over Europe according to CMIP6 climate projections: an analysis with original and bias-corrected data," Climatic Change, Springer, vol. 167(1), pages 1-17, July.
    17. Assowe Dabar, Omar & Awaleh, Mohamed Osman & Kirk-Davidoff, Daniel & Olauson, Jon & Söder, Lennart & Awaleh, Said Ismael, 2019. "Wind resource assessment and economic analysis for electricity generation in three locations of the Republic of Djibouti," Energy, Elsevier, vol. 185(C), pages 884-894.
    18. Liu, Lei & Shi, Yu & Zhang, Zhe & Zhang, Kang & Hu, Fei, 2023. "Analysis of turbulence intensity in the megacity of Beijing by High-frequency observations on a 325-m Tower," Renewable Energy, Elsevier, vol. 217(C).
    19. Ulazia, Alain & Sáenz, Jon & Ibarra-Berastegui, Gabriel & González-Rojí, Santos J. & Carreno-Madinabeitia, Sheila, 2017. "Using 3DVAR data assimilation to measure offshore wind energy potential at different turbine heights in the West Mediterranean," Applied Energy, Elsevier, vol. 208(C), pages 1232-1245.
    20. Jan Frederick Unnewehr & Hans-Peter Waldl & Thomas Pahlke & Iván Herráez & Anke Weidlich, 2020. "Reducing Operational Costs of Offshore HVDC Energy Export Systems Through Optimized Maintenance," Energies, MDPI, vol. 13(5), pages 1-20, March.

    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:12:y:2019:i:19:p:3696-:d:271445. 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.