IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v158y2020icp400-409.html
   My bibliography  Save this article

An amplitude- and rate-saturated collective pitch controller for wind turbine systems

Author

Listed:
  • Baiomy, Nehal
  • Kikuuwe, Ryo

Abstract

This paper proposes a new collective pitch controller for wind turbine systems to maintain the generator speed constant at the rated value in the region above the rated wind speed. It provides the command of the collective pitch angle to the wind turbine system, and one can impose explicit limits on the magnitude and the rate-of-change of the pitch angle command. In addition, the controller involves a variable gain that realizes non-overshooting convergence from the large errors in the generator speed and accurate regulation of the generator speed near the rated value. This controller is an extension of an amplitude- and rate-saturated controller previously proposed by the authors. It is combined with a state and disturbance observer and a lookup table-based feedforward. The proposed controller is validated through a software simulator FAST emulating a three-bladed horizontal-axis wind turbine system.

Suggested Citation

  • Baiomy, Nehal & Kikuuwe, Ryo, 2020. "An amplitude- and rate-saturated collective pitch controller for wind turbine systems," Renewable Energy, Elsevier, vol. 158(C), pages 400-409.
  • Handle: RePEc:eee:renene:v:158:y:2020:i:c:p:400-409
    DOI: 10.1016/j.renene.2020.05.112
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120308107
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.renene.2020.05.112?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. Zhu, Hongzhong & Sueyoshi, Makoto & Hu, Changhong & Yoshida, Shigeo, 2019. "A study on a floating type shrouded wind turbine: Design, modeling and analysis," Renewable Energy, Elsevier, vol. 134(C), pages 1099-1113.
    2. Lasheen, Ahmed & Elshafei, Abdel Latif, 2016. "Wind-turbine collective-pitch control via a fuzzy predictive algorithm," Renewable Energy, Elsevier, vol. 87(P1), pages 298-306.
    3. Njiri, Jackson G. & Söffker, Dirk, 2016. "State-of-the-art in wind turbine control: Trends and challenges," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 377-393.
    4. Kaman Thapa Magar & Mark Balas & Susan Frost & Nailu Li, 2017. "Adaptive State Feedback—Theory and Application for Wind Turbine Control," Energies, MDPI, vol. 10(12), pages 1-15, December.
    5. Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Jiang, Di, 2020. "Design and implementation of partial offline fuzzy model-predictive pitch controller for large-scale wind-turbines," Renewable Energy, Elsevier, vol. 145(C), pages 981-996.
    6. Hassan, H.M. & ElShafei, A.L. & Farag, W.A. & Saad, M.S., 2012. "A robust LMI-based pitch controller for large wind turbines," Renewable Energy, Elsevier, vol. 44(C), pages 63-71.
    Full references (including those not matched with items on IDEAS)

    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. Li, Jianshen & Wang, Shuangxin, 2021. "Dual multivariable model-free adaptive individual pitch control for load reduction in wind turbines with actuator faults," Renewable Energy, Elsevier, vol. 174(C), pages 293-304.
    2. Pablo Zambrana & Javier Fernandez-Quijano & J. Jesus Fernandez-Lozano & Pedro M. Mayorga Rubio & Alfonso J. Garcia-Cerezo, 2021. "Improving the Performance of Controllers for Wind Turbines on Semi-Submersible Offshore Platforms: Fuzzy Supervisor Control," Energies, MDPI, vol. 14(19), pages 1-17, September.
    3. Tiwari, Ramji & Babu, N. Ramesh, 2016. "Recent developments of control strategies for wind energy conversion system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 66(C), pages 268-285.
    4. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2017. "Continuous-time tube-based explicit model predictive control for collective pitching of wind turbines," Energy, Elsevier, vol. 118(C), pages 1222-1233.
    5. Li, Jianshen & Wang, Shuangxin & Li, Yaguang, 2020. "A model-free adaptive controller with tracking error differential for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 161(C), pages 435-447.
    6. Hawari, Qusay & Kim, Taeseong & Ward, Christopher & Fleming, James, 2022. "A robust gain scheduling method for a PI collective pitch controller of multi-MW onshore wind turbines," Renewable Energy, Elsevier, vol. 192(C), pages 443-455.
    7. Habibi, Hamed & Howard, Ian & Simani, Silvio, 2019. "Reliability improvement of wind turbine power generation using model-based fault detection and fault tolerant control: A review," Renewable Energy, Elsevier, vol. 135(C), pages 877-896.
    8. Tanvir Ahmad & Abdul Basit & Muneeb Ahsan & Olivier Coupiac & Nicolas Girard & Behzad Kazemtabrizi & Peter C. Matthews, 2019. "Implementation and Analyses of Yaw Based Coordinated Control of Wind Farms," Energies, MDPI, vol. 12(7), pages 1-15, April.
    9. Kuang, Limin & Su, Jie & Chen, Yaoran & Han, Zhaolong & Zhou, Dai & Zhang, Kai & Zhao, Yongsheng & Bao, Yan, 2022. "Wind-capture-accelerate device for performance improvement of vertical-axis wind turbines: External diffuser system," Energy, Elsevier, vol. 239(PB).
    10. Bon-Yong Koo & Dae-Yi Jung, 2019. "A Comparative Study on Primary Bearing Rating Life of a 5-MW Two-Blade Wind Turbine System Based on Two Different Control Domains," Energies, MDPI, vol. 12(13), pages 1-16, July.
    11. Kong, Xiaobing & Ma, Lele & Wang, Ce & Guo, Shifan & Abdelbaky, Mohamed Abdelkarim & Liu, Xiangjie & Lee, Kwang Y., 2022. "Large-scale wind farm control using distributed economic model predictive scheme," Renewable Energy, Elsevier, vol. 181(C), pages 581-591.
    12. Yolanda Vidal & Leonardo Acho & Ningsu Luo & Mauricio Zapateiro & Francesc Pozo, 2012. "Power Control Design for Variable-Speed Wind Turbines," Energies, MDPI, vol. 5(8), pages 1-18, August.
    13. Fang, Jianhao & Hu, Weifei & Liu, Zhenyu & Chen, Weiyi & Tan, Jianrong & Jiang, Zhiyu & Verma, Amrit Shankar, 2022. "Wind turbine rotor speed design optimization considering rain erosion based on deep reinforcement learning," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    14. Truong, Hoai Vu Anh & Dang, Tri Dung & Vo, Cong Phat & Ahn, Kyoung Kwan, 2022. "Active control strategies for system enhancement and load mitigation of floating offshore wind turbines: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    15. Igliński, Bartłomiej & Iglińska, Anna & Koziński, Grzegorz & Skrzatek, Mateusz & Buczkowski, Roman, 2016. "Wind energy in Poland – History, current state, surveys, Renewable Energy Sources Act, SWOT analysis," Renewable and Sustainable Energy Reviews, Elsevier, vol. 64(C), pages 19-33.
    16. Afef Fekih & Saleh Mobayen & Chih-Chiang Chen, 2021. "Adaptive Robust Fault-Tolerant Control Design for Wind Turbines Subject to Pitch Actuator Faults," Energies, MDPI, vol. 14(6), pages 1-13, March.
    17. Menon, Muraleekrishnan & Ponta, Fernando L., 2017. "Dynamic aeroelastic behavior of wind turbine rotors in rapid pitch-control actions," Renewable Energy, Elsevier, vol. 107(C), pages 327-339.
    18. Baisthakur, Shubham & Fitzgerald, Breiffni, 2024. "Physics-Informed Neural Network surrogate model for bypassing Blade Element Momentum theory in wind turbine aerodynamic load estimation," Renewable Energy, Elsevier, vol. 224(C).
    19. Azizi, Askar & Nourisola, Hamid & Shoja-Majidabad, Sajjad, 2019. "Fault tolerant control of wind turbines with an adaptive output feedback sliding mode controller," Renewable Energy, Elsevier, vol. 135(C), pages 55-65.
    20. Wang, Hao & Wang, Tongguang & Ke, Shitang & Hu, Liang & Xie, Jiaojie & Cai, Xin & Cao, Jiufa & Ren, Yuxin, 2023. "Assessing code-based design wind loads for offshore wind turbines in China against typhoons," Renewable Energy, Elsevier, vol. 212(C), pages 669-682.

    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:158:y:2020:i:c:p:400-409. 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.