IDEAS home Printed from https://ideas.repec.org/a/eee/renene/v161y2020icp435-447.html
   My bibliography  Save this article

A model-free adaptive controller with tracking error differential for collective pitching of wind turbines

Author

Listed:
  • Li, Jianshen
  • Wang, Shuangxin
  • Li, Yaguang

Abstract

The aerodynamic power captured by wind turbines is generally limited by pitch control when it operates above rated wind speed. However, problems such as actuator constraints, unmeasured system states, and stochastic wind speed fluctuations, make it difficult to establish an accurate model of the controlled collective pitch system. This paper proposes an improved model-free adaptive controller (MFAC) by considering the differential of tracking error in cost function (MFAC with the differential of tracking error, DE-MFAC), to compensate for potential effect of the system dynamic characteristics under random disturbance. Meanwhile, a new parameter β is introduced to adjust the impact of the compensation module to alleviate the contradiction between rapidity and hypertonicity. Then, the bounded-input bounded-output (BIBO) stability and monotonic convergence of the tracking error are derived by the contraction mapping. Furthermore, a Simulink/FAST platform is established and simulated under various wind conditions. The results show that, compared with the baseline PI and the MFAC based on compact form dynamic linearization (CFDL-MFAC), the proposed DE-MFAC is capable of handling the time-delay and large inertia of collective pitch systems, which not only significantly makes improvements in robustness and dynamic response, but also limits the average fluctuating amplitude of generator power within 1%.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:renene:v:161:y:2020:i:c:p:435-447
    DOI: 10.1016/j.renene.2020.06.140
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0960148120310624
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.renene.2020.06.140?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. 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.
    2. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2019. "Tube-based explicit model predictive output-feedback controller for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 131(C), pages 549-562.
    3. Dong Liu & Guang-Hong Yang, 2018. "Model-free adaptive control design for nonlinear discrete-time processes with reinforcement learning techniques," International Journal of Systems Science, Taylor & Francis Journals, vol. 49(11), pages 2298-2308, August.
    4. Jain, Achin & Schildbach, Georg & Fagiano, Lorenzo & Morari, Manfred, 2015. "On the design and tuning of linear model predictive control for wind turbines," Renewable Energy, Elsevier, vol. 80(C), pages 664-673.
    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.
    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. 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.

    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. 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.
    3. Lasheen, Ahmed & Saad, Mohamed S. & Emara, Hassan M. & Elshafei, Abdel Latif, 2019. "Tube-based explicit model predictive output-feedback controller for collective pitching of wind turbines," Renewable Energy, Elsevier, vol. 131(C), pages 549-562.
    4. 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.
    5. 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.
    6. Arabgolarcheh, Alireza & Rouhollahi, Amirhossein & Benini, Ernesto, 2023. "Analysis of middle-to-far wake behind floating offshore wind turbines in the presence of multiple platform motions," Renewable Energy, Elsevier, vol. 208(C), pages 546-560.
    7. Zhicheng Lin & Song Zheng & Zhicheng Chen & Rong Zheng & Wang Zhang, 2019. "Application Research of the Parallel System Theory and the Data Engine Approach in Wind Energy Conversion System," Energies, MDPI, vol. 12(5), pages 1-20, March.
    8. Xiaobing Kong & Lele Ma & Xiangjie Liu & Mohamed Abdelkarim Abdelbaky & Qian Wu, 2020. "Wind Turbine Control Using Nonlinear Economic Model Predictive Control over All Operating Regions," Energies, MDPI, vol. 13(1), pages 1-21, January.
    9. Amira Elkodama & Amr Ismaiel & A. Abdellatif & S. Shaaban & Shigeo Yoshida & Mostafa A. Rushdi, 2023. "Control Methods for Horizontal Axis Wind Turbines (HAWT): State-of-the-Art Review," Energies, MDPI, vol. 16(17), pages 1-32, September.
    10. Hongmin Meng & Tingting Yang & Ji-zhen Liu & Zhongwei Lin, 2017. "A Flexible Maximum Power Point Tracking Control Strategy Considering Both Conversion Efficiency and Power Fluctuation for Large-inertia Wind Turbines," Energies, MDPI, vol. 10(7), pages 1-19, July.
    11. Nitin S. Solke & Pritesh Shah & Ravi Sekhar & T. P. Singh, 2022. "Machine Learning-Based Predictive Modeling and Control of Lean Manufacturing in Automotive Parts Manufacturing Industry," Global Journal of Flexible Systems Management, Springer;Global Institute of Flexible Systems Management, vol. 23(1), pages 89-112, March.
    12. Karijadi, Irene & Chou, Shuo-Yan & Dewabharata, Anindhita, 2023. "Wind power forecasting based on hybrid CEEMDAN-EWT deep learning method," Renewable Energy, Elsevier, vol. 218(C).
    13. Pan, Lin & Wang, Xudong, 2020. "Variable pitch control on direct-driven PMSG for offshore wind turbine using Repetitive-TS fuzzy PID control," Renewable Energy, Elsevier, vol. 159(C), pages 221-237.
    14. Abdoos, Ali Akbar & Abdoos, Hatef & Kazemitabar, Javad & Mobashsher, Mohammad Mehdi & Khaloo, Hooman, 2023. "An intelligent hybrid method based on Monte Carlo simulation for short-term probabilistic wind power prediction," Energy, Elsevier, vol. 278(PA).
    15. Guo, Wencheng & Yang, Jiandong, 2018. "Dynamic performance analysis of hydro-turbine governing system considering combined effect of downstream surge tank and sloping ceiling tailrace tunnel," Renewable Energy, Elsevier, vol. 129(PA), pages 638-651.
    16. Li, Juan & Wang, Yinan & Zhao, Xiaowei & Qi, Pengyuan, 2021. "Model free adaptive control of large and flexible wind turbine rotors with controllable flaps," Renewable Energy, Elsevier, vol. 180(C), pages 68-82.
    17. Hu, Ruiqi & Le, Conghuan & Gao, Zhen & Ding, Hongyan & Zhang, Puyang, 2021. "Implementation and evaluation of control strategies based on an open controller for a 10 MW floating wind turbine," Renewable Energy, Elsevier, vol. 179(C), pages 1751-1766.
    18. Alhassan H. Alattar & S. I. Selem & Hamid M. B. Metwally & Ahmed Ibrahim & Raef Aboelsaud & Mohamed A. Tolba & Ali M. El-Rifaie, 2019. "Performance Enhancement of Micro Grid System with SMES Storage System Based on Mine Blast Optimization Algorithm," Energies, MDPI, vol. 12(16), pages 1-23, August.
    19. 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.
    20. Jayalakshmi N. Sabhahit & Sanjana Satish Solanke & Vinay Kumar Jadoun & Hasmat Malik & Fausto Pedro García Márquez & Jesús María Pinar-Pérez, 2022. "Contingency Analysis of a Grid Connected EV's for Primary Frequency Control of an Industrial Microgrid Using Efficient Control Scheme," Energies, MDPI, vol. 15(9), pages 1-24, April.

    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:161:y:2020:i:c:p:435-447. 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.