IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v126y2017icp821-829.html
   My bibliography  Save this article

A novel composite calculation model for power coefficient and flapping moment coefficient of wind turbine

Author

Listed:
  • Peng, Chao
  • Zou, Jianxiao
  • Li, Yan
  • Xu, Hongbing
  • Li, Liying

Abstract

In recent years, with continuous increasing capacity of wind turbine, mechanical fatigue problems caused by the vibration of load on wind turbine have become more and more serious. The load is composed mainly by oscillating load and flapping load, which can be measured by power coefficient and flapping moment coefficient. Both of them are important for wind turbine load analysis and operational control to reduce these load vibration. The existing calculation models for wind turbine load only focus on the power coefficient and always neglect flapping moment coefficient. In this paper, a novel composite power coefficient and flapping moment coefficient calculation model based on Blade Element Momentum Theory is proposed. A modified Blade Element Momentum model is built to calculate axial induction factor, tangent induction factor and torque force coefficient of wind turbine. By using them, a new calculation model for power coefficient and flapping moment coefficient is presented. Then, a composite calculation model based on iteration procedure and nonlinear fitting is built for calculating power coefficient and flapping moment coefficient simultaneously. Finally, the proposed calculation model is implemented to calculate the power coefficient and flapping moment coefficient of NREL 5 MW wind turbine and the results demonstrate its effectiveness.

Suggested Citation

  • Peng, Chao & Zou, Jianxiao & Li, Yan & Xu, Hongbing & Li, Liying, 2017. "A novel composite calculation model for power coefficient and flapping moment coefficient of wind turbine," Energy, Elsevier, vol. 126(C), pages 821-829.
    • Handle: RePEc:eee:energy:v:126:y:2017:i:c:p:821-829
    DOI: 10.1016/j.energy.2017.03.086
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544217304619
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2017.03.086?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. Vesel, Richard W. & McNamara, Jack J., 2014. "Performance enhancement and load reduction of a 5 MW wind turbine blade," Renewable Energy, Elsevier, vol. 66(C), pages 391-401.
    2. Li, Qing'an & Kamada, Yasunari & Maeda, Takao & Murata, Junsuke & Iida, Kohei & Okumura, Yuta, 2016. "Fundamental study on aerodynamic force of floating offshore wind turbine with cyclic pitch mechanism," Energy, Elsevier, vol. 99(C), pages 20-31.
    3. La Cava, William & Danai, Kourosh & Spector, Lee & Fleming, Paul & Wright, Alan & Lackner, Matthew, 2016. "Automatic identification of wind turbine models using evolutionary multiobjective optimization," Renewable Energy, Elsevier, vol. 87(P2), pages 892-902.
    4. Dai, J.C. & Hu, Y.P. & Liu, D.S. & Long, X., 2011. "Aerodynamic loads calculation and analysis for large scale wind turbine based on combining BEM modified theory with dynamic stall model," Renewable Energy, Elsevier, vol. 36(3), pages 1095-1104.
    5. Petković, Dalibor & Ćojbašič, Žarko & Nikolić, Vlastimir, 2013. "Adaptive neuro-fuzzy approach for wind turbine power coefficient estimation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 28(C), pages 191-195.
    6. Vaz, Jerson Rogério Pinheiro & Pinho, João Tavares & Mesquita, André Luiz Amarante, 2011. "An extension of BEM method applied to horizontal-axis wind turbine design," Renewable Energy, Elsevier, vol. 36(6), pages 1734-1740.
    7. Huang, Chang-Chi & Bai, Chi-Jeng & Shiah, Y.C. & Chen, Yu-Jen, 2016. "Optimal design of protuberant blades for small variable-speed horizontal axis wind turbine-experiments and simulations," Energy, Elsevier, vol. 115(P1), pages 1156-1167.
    8. Goh, Seach Chyr & Boopathy, Sethu Raman & Krishnaswami, Chidambaresan & Schlüter, Jörg Uwe, 2016. "Tow testing of Savonius wind turbine above a bluff body complemented by CFD simulation," Renewable Energy, Elsevier, vol. 87(P1), pages 332-345.
    9. Muhando, Endusa Billy & Senjyu, Tomonobu & Kinjo, Hiroshi & Funabashi, Toshihisa, 2008. "Augmented LQG controller for enhancement of online dynamic performance for WTG system," Renewable Energy, Elsevier, vol. 33(8), pages 1942-1952.
    10. Sedaghat, Ahmad & El Haj Assad, M. & Gaith, Mohamed, 2014. "Aerodynamics performance of continuously variable speed horizontal axis wind turbine with optimal blades," Energy, Elsevier, vol. 77(C), pages 752-759.
    11. Karthikeyan, N. & Kalidasa Murugavel, K. & Arun Kumar, S. & Rajakumar, S., 2015. "Review of aerodynamic developments on small horizontal axis wind turbine blade," Renewable and Sustainable Energy Reviews, Elsevier, vol. 42(C), pages 801-822.
    12. Song, Dongran & Yang, Jian & Cai, Zili & Dong, Mi & Su, Mei & Wang, Yinghua, 2017. "Wind estimation with a non-standard extended Kalman filter and its application on maximum power extraction for variable speed wind turbines," Applied Energy, Elsevier, vol. 190(C), pages 670-685.
    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. Wen, Hao & Sang, Song & Qiu, Chenhui & Du, Xiangrui & Zhu, Xiao & Shi, Qian, 2019. "A new optimization method of wind turbine airfoil performance based on Bessel equation and GABP artificial neural network," Energy, Elsevier, vol. 187(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. Bai, Chi-Jeng & Wang, Wei-Cheng, 2016. "Review of computational and experimental approaches to analysis of aerodynamic performance in horizontal-axis wind turbines (HAWTs)," Renewable and Sustainable Energy Reviews, Elsevier, vol. 63(C), pages 506-519.
    2. Zhang, Sanxia & Luo, Kun & Yuan, Renyu & Wang, Qiang & Wang, Jianwen & Zhang, Liru & Fan, Jianren, 2018. "Influences of operating parameters on the aerodynamics and aeroacoustics of a horizontal-axis wind turbine," Energy, Elsevier, vol. 160(C), pages 597-611.
    3. Li, Qing'an & Wang, Ye & Kamada, Yasunari & Maeda, Takao & Xu, Jianzhong & Zhou, Shuni & Zhang, Fanghong & Cai, Chang, 2022. "Diagonal inflow effect on the wake characteristics of a horizontal axis wind turbine with Gaussian model and field measurements," Energy, Elsevier, vol. 238(PB).
    4. Sedaghat, Ahmad & Hassanzadeh, Arash & Jamali, Jamaloddin & Mostafaeipour, Ali & Chen, Wei-Hsin, 2017. "Determination of rated wind speed for maximum annual energy production of variable speed wind turbines," Applied Energy, Elsevier, vol. 205(C), pages 781-789.
    5. Alkhabbaz, Ali & Yang, Ho-Seong & Weerakoon, A.H Samitha & Lee, Young-Ho, 2021. "A novel linearization approach of chord and twist angle distribution for 10 kW horizontal axis wind turbine," Renewable Energy, Elsevier, vol. 178(C), pages 1398-1420.
    6. Ponta, Fernando L. & Otero, Alejandro D. & Lago, Lucas I. & Rajan, Anurag, 2016. "Effects of rotor deformation in wind-turbine performance: The Dynamic Rotor Deformation Blade Element Momentum model (DRD–BEM)," Renewable Energy, Elsevier, vol. 92(C), pages 157-170.
    7. Kyoungboo Yang, 2020. "Geometry Design Optimization of a Wind Turbine Blade Considering Effects on Aerodynamic Performance by Linearization," Energies, MDPI, vol. 13(9), pages 1-18, May.
    8. O'Rourke, Fergal & Boyle, Fergal & Reynolds, Anthony & Kennedy, David M., 2015. "Hydrodynamic performance prediction of a tidal current turbine operating in non-uniform inflow conditions," Energy, Elsevier, vol. 93(P2), pages 2483-2496.
    9. Sedaghat, Ahmad & El Haj Assad, M. & Gaith, Mohamed, 2014. "Aerodynamics performance of continuously variable speed horizontal axis wind turbine with optimal blades," Energy, Elsevier, vol. 77(C), pages 752-759.
    10. Anurag Rajan & Fernando L. Ponta, 2019. "A Novel Correlation Model for Horizontal Axis Wind Turbines Operating at High-Interference Flow Regimes," Energies, MDPI, vol. 12(6), pages 1-20, March.
    11. Govind, Bala, 2017. "Increasing the operational capability of a horizontal axis wind turbine by its integration with a vertical axis wind turbine," Applied Energy, Elsevier, vol. 199(C), pages 479-494.
    12. Lanzafame, R. & Messina, M., 2013. "Advanced brake state model and aerodynamic post-stall model for horizontal axis wind turbines," Renewable Energy, Elsevier, vol. 50(C), pages 415-420.
    13. Hassan, Syed Saddam ul & Javaid, M. Tariq & Rauf, Umar & Nasir, Sheharyar & Shahzad, Aamer & Salamat, Shuaib, 2023. "Systematic investigation of power enhancement of Vertical Axis Wind Turbines using bio-inspired leading edge tubercles," Energy, Elsevier, vol. 270(C).
    14. Rocha, P. A. Costa & Rocha, H. H. Barbosa & Carneiro, F. O. Moura & da Silva, M. E. Vieira & de Andrade, C. Freitas, 2016. "A case study on the calibration of the k–ω SST (shear stress transport) turbulence model for small scale wind turbines designed with cambered and symmetrical airfoils," Energy, Elsevier, vol. 97(C), pages 144-150.
    15. Xiao, Qing & Zhou, Shaowu, 2018. "Probabilistic power flow computation considering correlated wind speeds," Applied Energy, Elsevier, vol. 231(C), pages 677-685.
    16. Fathabadi, Hassan, 2019. "Recovering waste vibration energy of an automobile using shock absorbers included magnet moving-coil mechanism and adding to overall efficiency using wind turbine," Energy, Elsevier, vol. 189(C).
    17. N. Aravindhan & M. P. Natarajan & S. Ponnuvel & P.K. Devan, 2023. "Recent developments and issues of small-scale wind turbines in urban residential buildings- A review," Energy & Environment, , vol. 34(4), pages 1142-1169, June.
    18. Ikeda, Teruaki & Tanaka, Hiroto & Yoshimura, Ryosuke & Noda, Ryusuke & Fujii, Takeo & Liu, Hao, 2018. "A robust biomimetic blade design for micro wind turbines," Renewable Energy, Elsevier, vol. 125(C), pages 155-165.
    19. Zhu, Wei Jun & Shen, Wen Zhong & Sørensen, Jens Nørkær & Yang, Hua, 2017. "Verification of a novel innovative blade root design for wind turbines using a hybrid numerical method," Energy, Elsevier, vol. 141(C), pages 1661-1670.
    20. Wang, Xinbao & Cai, Chang & Cai, Shang-Gui & Wang, Tengyuan & Wang, Zekun & Song, Juanjuan & Rong, Xiaomin & Li, Qing'an, 2023. "A review of aerodynamic and wake characteristics of floating offshore wind turbines," Renewable and Sustainable Energy Reviews, Elsevier, vol. 175(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:eee:energy:v:126:y:2017:i:c:p:821-829. 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/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.