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A novel adaptive control scheme for dynamic performance improvement of DFIG-Based wind turbines

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  • Song, Zhanfeng
  • Shi, Tingna
  • Xia, Changliang
  • Chen, Wei

Abstract

A novel adaptive current controller for DFIG-based wind turbines is introduced in this paper. The attractiveness of the proposed strategy results from its ability to actively estimate and actively compensate for the plant dynamics and external disturbances in real time. Thus, the control strategy can successfully drive the rotor current to track the reference value, ensuring that the performance degradation caused by grid disturbances, cross-coupling terms and parameter uncertainties can be successfully suppressed. Besides, the two-parameter tuning feature makes the control strategy practical and easy to implement in commercial wind turbines. To quantify the controller performances, the transfer function description of the controller is derived. General disturbance rejection, robustness against parameter uncertainties, bandwidth and stability are also addressed. Simulation results, together with the time-domain responses, proved the stability and the strong robustness of the control system against parameter uncertainties and grid disturbances. Significant tracking and disturbance rejection performances are achieved.

Suggested Citation

  • Song, Zhanfeng & Shi, Tingna & Xia, Changliang & Chen, Wei, 2012. "A novel adaptive control scheme for dynamic performance improvement of DFIG-Based wind turbines," Energy, Elsevier, vol. 38(1), pages 104-117.
    • Handle: RePEc:eee:energy:v:38:y:2012:i:1:p:104-117
    DOI: 10.1016/j.energy.2011.12.029
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    2. Kusiak, Andrew & Zhang, Zijun & Verma, Anoop, 2013. "Prediction, operations, and condition monitoring in wind energy," Energy, Elsevier, vol. 60(C), pages 1-12.
    3. Moradi, Hamed & Vossoughi, Gholamreza, 2015. "Robust control of the variable speed wind turbines in the presence of uncertainties: A comparison between H∞ and PID controllers," Energy, Elsevier, vol. 90(P2), pages 1508-1521.
    4. Taveiros, F.E.V. & Barros, L.S. & Costa, F.B., 2015. "Back-to-back converter state-feedback control of DFIG (doubly-fed induction generator)-based wind turbines," Energy, Elsevier, vol. 89(C), pages 896-906.
    5. Mohd Zin, Abdullah Asuhaimi B. & Pesaran H.A., Mahmoud & Khairuddin, Azhar B. & Jahanshaloo, Leila & Shariati, Omid, 2013. "An overview on doubly fed induction generators′ controls and contributions to wind based electricity generation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 27(C), pages 692-708.
    6. Pichan, Mohammad & Rastegar, Hasan & Monfared, Mohammad, 2013. "Two fuzzy-based direct power control strategies for doubly-fed induction generators in wind energy conversion systems," Energy, Elsevier, vol. 51(C), pages 154-162.
    7. Xie, Wei & Zeng, Pan & Lei, Liping, 2015. "Wind tunnel experiments for innovative pitch regulated blade of horizontal axis wind turbine," Energy, Elsevier, vol. 91(C), pages 1070-1080.
    8. Ren, Lina & Mao, Chenhong & Song, Zeyu & Liu, Fucai, 2019. "Study on active disturbance rejection control with actuator saturation to reduce the load of a driving chain in wind turbines," Renewable Energy, Elsevier, vol. 133(C), pages 268-274.
    9. Belmokhtar, K. & Doumbia, M.L. & Agbossou, K., 2014. "Novel fuzzy logic based sensorless maximum power point tracking strategy for wind turbine systems driven DFIG (doubly-fed induction generator)," Energy, Elsevier, vol. 76(C), pages 679-693.

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