IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v10y2017i11p1839-d118381.html
   My bibliography  Save this article

Wind Turbine Loads Induced by Terrain and Wakes: An Experimental Study through Vibration Analysis and Computational Fluid Dynamics

Author

Listed:
  • Francesco Castellani

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy)

  • Marco Buzzoni

    (Department of Engineering, University of Ferrara, Via G. Saragat 1, 44122 Ferrara, Italy)

  • Davide Astolfi

    (Department of Engineering, University of Perugia, Via G. Duranti 93, 06125 Perugia, Italy)

  • Gianluca D’Elia

    (Department of Engineering, University of Ferrara, Via G. Saragat 1, 44122 Ferrara, Italy)

  • Giorgio Dalpiaz

    (Department of Engineering, University of Ferrara, Via G. Saragat 1, 44122 Ferrara, Italy)

  • Ludovico Terzi

    (Renvico s.r.l., Via San Gregorio 34, 20124 Milano, Italy)

Abstract

A wind turbine is a very well-known archetype of energy conversion system working at non-stationary regimes. Despite this, a deep mechanical comprehension of wind turbines operating in complicated conditions is still challenging, especially as regards the analysis of experimental data. In particular, wind turbines in complex terrain represent a very valuable testing ground because of the possible combination of wake effects among nearby turbines and flow accelerations caused by the terrain morphology. For these reasons, in this work, a cluster of four full-scale wind turbines from a very complex site is studied. The object of investigation is vibrations, at the level of the structure (tower) and drive-train. Data collected by the on-board condition monitoring system are analyzed and interpreted in light of the knowledge of wind conditions and operating parameters collected by the Supervisory Control And Data Acquisition (SCADA). A free flow Computational Fluid Dynamics (CFD) simulation is also performed, and it allows one to better interpret the vibration analysis. The main outcome is the interpretation of how wakes and flow turbulences appear in the vibration signals, both at the structural level and at the drive-train level. Therefore, this wind to gear approach builds a connection between flow phenomena and mechanical phenomena in the form of vibrations, representing a precious tool for assessing loads in different working conditions.

Suggested Citation

  • Francesco Castellani & Marco Buzzoni & Davide Astolfi & Gianluca D’Elia & Giorgio Dalpiaz & Ludovico Terzi, 2017. "Wind Turbine Loads Induced by Terrain and Wakes: An Experimental Study through Vibration Analysis and Computational Fluid Dynamics," Energies, MDPI, vol. 10(11), pages 1-19, November.
  • Handle: RePEc:gam:jeners:v:10:y:2017:i:11:p:1839-:d:118381
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/10/11/1839/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/10/11/1839/
    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. van Dijk, Mike T. & van Wingerden, Jan-Willem & Ashuri, Turaj & Li, Yaoyu, 2017. "Wind farm multi-objective wake redirection for optimizing power production and loads," Energy, Elsevier, vol. 121(C), pages 561-569.
    3. Kim, Soo-Hyun & Shin, Hyung-Ki & Joo, Young-Chul & Kim, Keon-Hoon, 2015. "A study of the wake effects on the wind characteristics and fatigue loads for the turbines in a wind farm," Renewable Energy, Elsevier, vol. 74(C), pages 536-543.
    4. Vera-Tudela, Luis & Kühn, Martin, 2017. "Analysing wind turbine fatigue load prediction: The impact of wind farm flow conditions," Renewable Energy, Elsevier, vol. 107(C), pages 352-360.
    5. Hu, Aijun & Yan, Xiaoan & Xiang, Ling, 2015. "A new wind turbine fault diagnosis method based on ensemble intrinsic time-scale decomposition and WPT-fractal dimension," Renewable Energy, Elsevier, vol. 83(C), pages 767-778.
    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. 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.

    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. He, Ruiyang & Yang, Hongxing & Sun, Shilin & Lu, Lin & Sun, Haiying & Gao, Xiaoxia, 2022. "A machine learning-based fatigue loads and power prediction method for wind turbines under yaw control," Applied Energy, Elsevier, vol. 326(C).
    2. He, Ruiyang & Yang, Hongxing & Lu, Lin & Gao, Xiaoxia, 2024. "Site-specific wake steering strategy for combined power enhancement and fatigue mitigation within wind farms," Renewable Energy, Elsevier, vol. 225(C).
    3. 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.
    4. Ge, Mingwei & Wu, Ying & Liu, Yongqian & Li, Qi, 2019. "A two-dimensional model based on the expansion of physical wake boundary for wind-turbine wakes," Applied Energy, Elsevier, vol. 233, pages 975-984.
    5. 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.
    6. Xu, Zongyuan & Gao, Xiaoxia & Zhang, Huanqiang & Lv, Tao & Han, Zhonghe & Zhu, Xiaoxun & Wang, Yu, 2023. "Analysis of the anisotropy aerodynamic characteristics of downstream wind turbine considering the 3D wake expansion based on coupling method," Energy, Elsevier, vol. 263(PD).
    7. 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).
    8. 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.
    9. Yuan Song & Insu Paek, 2020. "Prediction and Validation of the Annual Energy Production of a Wind Turbine Using WindSim and a Dynamic Wind Turbine Model," Energies, MDPI, vol. 13(24), pages 1-15, December.
    10. Dhunny, A.Z. & Allam, Z. & Lobine, D. & Lollchund, M.R., 2019. "Sustainable renewable energy planning and wind farming optimization from a biodiversity perspective," Energy, Elsevier, vol. 185(C), pages 1282-1297.
    11. Jae-ho Jeong & Kwangtae Ha, 2020. "Evaluation of Wind Flow Characteristics by RANS-Based Numerical Site Calibration (NSC) Method with Met-Tower Measurements and Its Application to a Complex Terrain," Energies, MDPI, vol. 13(19), pages 1-16, October.
    12. Kanev, Stoyan, 2020. "Dynamic wake steering and its impact on wind farm power production and yaw actuator duty," Renewable Energy, Elsevier, vol. 146(C), pages 9-15.
    13. He, Ruiyang & Yang, Hongxing & Lu, Lin, 2023. "Optimal yaw strategy and fatigue analysis of wind turbines under the combined effects of wake and yaw control," Applied Energy, Elsevier, vol. 337(C).
    14. Jijian Lian & Ou Cai & Xiaofeng Dong & Qi Jiang & Yue Zhao, 2019. "Health Monitoring and Safety Evaluation of the Offshore Wind Turbine Structure: A Review and Discussion of Future Development," Sustainability, MDPI, vol. 11(2), pages 1-29, January.
    15. Li, Qing'an & Cai, Chang & Kamada, Yasunari & Maeda, Takao & Hiromori, Yuto & Zhou, Shuni & Xu, Jianzhong, 2021. "Prediction of power generation of two 30 kW Horizontal Axis Wind Turbines with Gaussian model," Energy, Elsevier, vol. 231(C).
    16. Timmons, D. & Dhunny, A.Z. & Elahee, K. & Havumaki, B. & Howells, M. & Khoodaruth, A. & Lema-Driscoll, A.K. & Lollchund, M.R. & Ramgolam, Y.K. & Rughooputh, S.D.D.V. & Surroop, D., 2019. "Cost minimization for fully renewable electricity systems: A Mauritius case study," Energy Policy, Elsevier, vol. 133(C).
    17. Khadijah Barashid & Amr Munshi & Ahmad Alhindi, 2023. "Wind Farm Power Prediction Considering Layout and Wake Effect: Case Study of Saudi Arabia," Energies, MDPI, vol. 16(2), pages 1-22, January.
    18. 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.
    19. Cai, Wei & Hu, Yang & Fang, Fang & Yao, Lujin & Liu, Jizhen, 2023. "Wind farm power production and fatigue load optimization based on dynamic partitioning and wake redirection of wind turbines," Applied Energy, Elsevier, vol. 339(C).
    20. Dou, Bingzheng & Qu, Timing & Lei, Liping & Zeng, Pan, 2020. "Optimization of wind turbine yaw angles in a wind farm using a three-dimensional yawed wake model," Energy, Elsevier, vol. 209(C).

    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:10:y:2017:i:11:p:1839-:d:118381. 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.