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Fuzzy Active Disturbance Rejection-Based Virtual Inertia Control Strategy for Wind Farms

Author

Listed:
  • Tai Li

    (School of Automation, Wuxi University, Wuxi 214105, China)

  • Yanbo Wang

    (Department of Energy Technology, Aalborg University, 22222 Aalborg, Denmark)

  • Sunan Sun

    (College of Automation, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

  • Huimin Qian

    (College of Automation, Jiangsu University of Science and Technology, Zhenjiang 212003, China)

  • Leqiu Wang

    (School of Automation, Wuxi University, Wuxi 214105, China)

  • Lei Wang

    (School of Automation, Wuxi University, Wuxi 214105, China)

  • Yanxia Shen

    (School of Internet of Things Engineering, Jiangnan University, Wuxi 214112, China)

  • Zhicheng Ji

    (School of Internet of Things Engineering, Jiangnan University, Wuxi 214112, China)

Abstract

This paper presents an advanced virtual inertia control strategy for wind farms to provide transient power support in the presence of frequency events, where a fuzzy active disturbance rejection controller is developed to enable the operation of an energy storage system (ESS) so as to provide support for frequency regulation of the power grid. To effectively estimate the system frequency under uncertain noises, fuzzy rules are presented to adaptively tune the parameters of the extended state observer and to realize the power-sharing, to improve the anti-interference ability of the wind power system. Finally, simulation analysis in MATLAB/Simulink is provided to validate the effectiveness of the proposed control strategy. Simulation results show that the developed virtual inertia control strategy based on fuzzy active disturbance rejection control has a good inertia support capability. In addition, the proposed method is able to improve the anti-noise capability of the wind power system.

Suggested Citation

  • Tai Li & Yanbo Wang & Sunan Sun & Huimin Qian & Leqiu Wang & Lei Wang & Yanxia Shen & Zhicheng Ji, 2023. "Fuzzy Active Disturbance Rejection-Based Virtual Inertia Control Strategy for Wind Farms," Energies, MDPI, vol. 16(10), pages 1-16, May.
    • Handle: RePEc:gam:jeners:v:16:y:2023:i:10:p:3991-:d:1142871
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    References listed on IDEAS

    as
    1. Kumar, Dipesh & Chatterjee, Kalyan, 2016. "A review of conventional and advanced MPPT algorithms for wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 957-970.
    2. Tai Li & Leqiu Wang & Yanbo Wang & Guohai Liu & Zhiyu Zhu & Yongwei Zhang & Li Zhao & Zhicheng Ji, 2021. "Data-Driven Virtual Inertia Control Method of Doubly Fed Wind Turbine," Energies, MDPI, vol. 14(17), pages 1-18, September.
    3. Athari, M.H. & Ardehali, M.M., 2016. "Operational performance of energy storage as function of electricity prices for on-grid hybrid renewable energy system by optimized fuzzy logic controller," Renewable Energy, Elsevier, vol. 85(C), pages 890-902.
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