IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v116y2018ipap423-437.html
   My bibliography  Save this article

Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade

Author

Listed:
  • Meng, Hang
  • Lien, Fue-Sang
  • Li, Li

Abstract

Wake effect causes fatigue increase on the horizontal axis wind turbine (HAWT) blades. This wake-induced fatigue has significant impacts on the efficiency and lifespan of the whole wind farm. However, conventional aeroelastic codes are deficient in terms of turbulent wake modelling and wake interaction modelling. To accurately carry out the aeroelastic simulation in multi-wake operation, an “elastic actuator line” (EAL) model is proposed. Essentially, this model is the combination of the actuator line (AL) wake model and a finite difference structural model. The present research includes two parts. Firstly, the proposed EAL model is outlined. To better establish the two-way coupling between the structural model and the AL model, the transformation of a set of structural equations is presented. Secondly, numerical structural model is established. To verify the present model, the simulated results by EAL for a single NREL 5 MW turbine are compared with those obtained with the aeroelastic code FAST. And the comparison shows a good agreement for both high and low TSRs (Tip-Speed-Ratios). Another case study for the wake interaction involving two staggered HAWTs is also carried out, which shows that the downstream wind turbine truly experiences an obvious wake-induced fatigue increase based on our equivalent fatigue load analysis.

Suggested Citation

  • Meng, Hang & Lien, Fue-Sang & Li, Li, 2018. "Elastic actuator line modelling for wake-induced fatigue analysis of horizontal axis wind turbine blade," Renewable Energy, Elsevier, vol. 116(PA), pages 423-437.
    • Handle: RePEc:eee:renene:v:116:y:2018:i:pa:p:423-437
    DOI: 10.1016/j.renene.2017.08.074
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148117308364
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2017.08.074?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. Sarlak, H. & Meneveau, C. & Sørensen, J.N., 2015. "Role of subgrid-scale modeling in large eddy simulation of wind turbine wake interactions," Renewable Energy, Elsevier, vol. 77(C), pages 386-399.
    2. Storey, R.C. & Cater, J.E. & Norris, S.E., 2016. "Large eddy simulation of turbine loading and performance in a wind farm," Renewable Energy, Elsevier, vol. 95(C), pages 31-42.
    3. Jang, Yun Jung & Choi, Chan Woong & Lee, Jang Ho & Kang, Ki Weon, 2015. "Development of fatigue life prediction method and effect of 10-minute mean wind speed distribution on fatigue life of small wind turbine composite blade," Renewable Energy, Elsevier, vol. 79(C), pages 187-198.
    4. Castellani, Francesco & Vignaroli, Andrea, 2013. "An application of the actuator disc model for wind turbine wakes calculations," Applied Energy, Elsevier, vol. 101(C), pages 432-440.
    5. Adaramola, M.S. & Krogstad, P.-Å., 2011. "Experimental investigation of wake effects on wind turbine performance," Renewable Energy, Elsevier, vol. 36(8), pages 2078-2086.
    6. Kecskemety, Krista M. & McNamara, Jack J., 2016. "Influence of wake dynamics on the performance and aeroelasticity of wind turbines," Renewable Energy, Elsevier, vol. 88(C), pages 333-345.
    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. Fei, Zhao & Tengyuan, Wang & Xiaoxia, Gao & Haiying, Sun & Hongxing, Yang & Zhonghe, Han & Yu, Wang & Xiaoxun, Zhu, 2020. "Experimental study on wake interactions and performance of the turbines with different rotor-diameters in adjacent area of large-scale wind farm," Energy, Elsevier, vol. 199(C).
    2. Meng, Hang & Lien, Fue-Sang & Yee, Eugene & Shen, Jingfang, 2020. "Modelling of anisotropic beam for rotating composite wind turbine blade by using finite-difference time-domain (FDTD) method," Renewable Energy, Elsevier, vol. 162(C), pages 2361-2379.
    3. Della Posta, Giacomo & Leonardi, Stefano & Bernardini, Matteo, 2022. "A two-way coupling method for the study of aeroelastic effects in large wind turbines," Renewable Energy, Elsevier, vol. 190(C), pages 971-992.
    4. Wei Li & Shinai Xu & Baiyun Qian & Xiaoxia Gao & Xiaoxun Zhu & Zeqi Shi & Wei Liu & Qiaoliang Hu, 2022. "Large-Scale Wind Turbine’s Load Characteristics Excited by the Wind and Grid in Complex Terrain: A Review," Sustainability, MDPI, vol. 14(24), pages 1-29, December.
    5. Mou Lin & Fernando Porté-Agel, 2023. "Power Production and Blade Fatigue of a Wind Turbine Array Subjected to Active Yaw Control," Energies, MDPI, vol. 16(6), pages 1-17, March.
    6. 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).
    7. Lu, Liang & Wu, Haijun & Wu, Jianzhong, 2021. "A case study for the optimization of moment-matching in wind turbine blade fatigue tests with a resonant type exciting approach," Renewable Energy, Elsevier, vol. 174(C), pages 769-785.
    8. Zheng, Jiancai & Wang, Nina & Wan, Decheng & Strijhak, Sergei, 2023. "Numerical investigations of coupled aeroelastic performance of wind turbines by elastic actuator line model," Applied Energy, Elsevier, vol. 330(PB).
    9. Meng, Hang & Li, Li & Zhang, Jinhua, 2020. "A preliminary numerical study of the wake effects on the fatigue load for wind farm based on elastic actuator line model," Renewable Energy, Elsevier, vol. 162(C), pages 788-801.
    10. Jiménez, Alfredo Arcos & García Márquez, Fausto Pedro & Moraleda, Victoria Borja & Gómez Muñoz, Carlos Quiterio, 2019. "Linear and nonlinear features and machine learning for wind turbine blade ice detection and diagnosis," Renewable Energy, Elsevier, vol. 132(C), pages 1034-1048.
    11. Zhe Ma & Liping Lei & Earl Dowell & Pan Zeng, 2020. "An Experimental Study on the Actuator Line Method with Anisotropic Regularization Kernel," Energies, MDPI, vol. 13(4), pages 1-19, February.
    12. Fei Zhao & Yihan Gao & Tengyuan Wang & Jinsha Yuan & Xiaoxia Gao, 2020. "Experimental Study on Wake Evolution of a 1.5 MW Wind Turbine in a Complex Terrain Wind Farm Based on LiDAR Measurements," Sustainability, MDPI, vol. 12(6), pages 1-14, March.
    13. Kang, Yujoo & Kim, Hyebin & Lee, Sang, 2023. "Benefits of individual pitch control on offshore wind turbine submerged in upstream wake," Renewable Energy, Elsevier, vol. 217(C).
    14. Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
    15. Christian Santoni & Fotis Sotiropoulos & Ali Khosronejad, 2024. "A Comparative Analysis of Actuator-Based Turbine Structure Parametrizations for High-Fidelity Modeling of Utility-Scale Wind Turbines under Neutral Atmospheric Conditions," Energies, MDPI, vol. 17(3), pages 1-16, February.

    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. Amiri, Mojtaba Maali & Shadman, Milad & Estefen, Segen F., 2024. "A review of physical and numerical modeling techniques for horizontal-axis wind turbine wakes," Renewable and Sustainable Energy Reviews, Elsevier, vol. 193(C).
    2. Li, Qing'an & Murata, Junsuke & Endo, Masayuki & Maeda, Takao & Kamada, Yasunari, 2016. "Experimental and numerical investigation of the effect of turbulent inflow on a Horizontal Axis Wind Turbine (part II: Wake characteristics)," Energy, Elsevier, vol. 113(C), pages 1304-1315.
    3. Dai, Juchuan & Yang, Xin & Hu, Wei & Wen, Li & Tan, Yayi, 2018. "Effect investigation of yaw on wind turbine performance based on SCADA data," Energy, Elsevier, vol. 149(C), pages 684-696.
    4. Huilai Ren & Xiaodong Zhang & Shun Kang & Sichao Liang, 2018. "Actuator Disc Approach of Wind Turbine Wake Simulation Considering Balance of Turbulence Kinetic Energy," Energies, MDPI, vol. 12(1), pages 1-19, December.
    5. Micallef, Daniel & Rezaeiha, Abdolrahim, 2021. "Floating offshore wind turbine aerodynamics: Trends and future challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 152(C).
    6. Bashirzadeh Tabrizi, Amir & Whale, Jonathan & Lyons, Thomas & Urmee, Tania & Peinke, Joachim, 2017. "Modelling the structural loading of a small wind turbine at a highly turbulent site via modifications to the Kaimal turbulence spectra," Renewable Energy, Elsevier, vol. 105(C), pages 288-300.
    7. Liang Lu & Minyan Zhu & Haijun Wu & Jianzhong Wu, 2022. "A Review and Case Analysis on Biaxial Synchronous Loading Technology and Fast Moment-Matching Methods for Fatigue Tests of Wind Turbine Blades," Energies, MDPI, vol. 15(13), pages 1-34, July.
    8. 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.
    9. Ma, Hongliang & Ge, Mingwei & Wu, Guangxing & Du, Bowen & Liu, Yongqian, 2021. "Formulas of the optimized yaw angles for cooperative control of wind farms with aligned turbines to maximize the power production," Applied Energy, Elsevier, vol. 303(C).
    10. Shen, Wen Zhong & Lin, Jian Wei & Jiang, Yu Hang & Feng, Ju & Cheng, Li & Zhu, Wei Jun, 2023. "A novel yaw wake model for wind farm control applications," Renewable Energy, Elsevier, vol. 218(C).
    11. 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.
    12. Rubel C. Das & Yu-Lin Shen, 2023. "Analysis of Wind Farms under Different Yaw Angles and Wind Speeds," Energies, MDPI, vol. 16(13), pages 1-19, June.
    13. Gao, Xiaoxia & Chen, Yao & Xu, Shinai & Gao, Wei & Zhu, Xiaoxun & Sun, Haiying & Yang, Hongxing & Han, Zhonghe & Wang, Yu & Lu, Hao, 2022. "Comparative experimental investigation into wake characteristics of turbines in three wind farms areas with varying terrain complexity from LiDAR measurements," Applied Energy, Elsevier, vol. 307(C).
    14. Brown, S.A. & Ransley, E.J. & Greaves, D.M., 2020. "Developing a coupled turbine thrust methodology for floating tidal stream concepts: Verification under prescribed motion," Renewable Energy, Elsevier, vol. 147(P1), pages 529-540.
    15. Dou, Bingzheng & Guala, Michele & Lei, Liping & Zeng, Pan, 2019. "Experimental investigation of the performance and wake effect of a small-scale wind turbine in a wind tunnel," Energy, Elsevier, vol. 166(C), pages 819-833.
    16. Rezaeiha, Abdolrahim & Micallef, Daniel, 2021. "Wake interactions of two tandem floating offshore wind turbines: CFD analysis using actuator disc model," Renewable Energy, Elsevier, vol. 179(C), pages 859-876.
    17. 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).
    18. Li, Qing'an & Maeda, Takao & Kamada, Yasunari & Mori, Naoya, 2017. "Investigation of wake characteristics of a Horizontal Axis Wind Turbine in vertical axis direction with field experiments," Energy, Elsevier, vol. 141(C), pages 262-272.
    19. Sarlak, H. & Nishino, T. & Martínez-Tossas, L.A. & Meneveau, C. & Sørensen, J.N., 2016. "Assessment of blockage effects on the wake characteristics and power of wind turbines," Renewable Energy, Elsevier, vol. 93(C), pages 340-352.
    20. Hayat, Imran & Chatterjee, Tanmoy & Liu, Huiwen & Peet, Yulia T. & Chamorro, Leonardo P., 2019. "Exploring wind farms with alternating two- and three-bladed wind turbines," Renewable Energy, Elsevier, vol. 138(C), pages 764-774.

    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:116:y:2018:i:pa:p:423-437. 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.