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Adaptive virtual inertia-based frequency regulation in wind power systems

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  • Pradhan, Chittaranjan
  • Bhende, Chandrashekhar Narayan
  • Samanta, Anik Kumar

Abstract

In this paper, frequency sensitive-based virtual inertia control techniques are discussed, to extract the kinetic energy of the wind turbine and stored energy from the DC-link capacitor for short-term frequency regulation. This paper presents a comparative analysis between the permanent magnet synchronous generator and doubly fed induction generator-based wind power system on the basis of virtual inertia control. The gains of the kinetic energy-based and DC-link capacitor-based inertia controls are varied dynamically with system events to improve the primary frequency response of the wind energy system. Two control schemes are proposed on the basis of modulating the inertia gains, one is a dynamic equation-based scheme and other is an adaptive fuzzy-based scheme. The proposed schemes modulate the gains of inertia controls dynamically for a wide range of wind speeds on the perspectives of wind turbine stability and frequency security. The efficacy of the proposed control schemes are validated by MATLAB/SIMULINK platform. Further, the results based on hardware-in-the-loop (HIL) simulations are presented in support of the proposed schemes. The HIL is implemented with two units of the real-time simulator (RTS) manufactured by OPAL-RT Technologies.

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  • Pradhan, Chittaranjan & Bhende, Chandrashekhar Narayan & Samanta, Anik Kumar, 2018. "Adaptive virtual inertia-based frequency regulation in wind power systems," Renewable Energy, Elsevier, vol. 115(C), pages 558-574.
    • Handle: RePEc:eee:renene:v:115:y:2018:i:c:p:558-574
    DOI: 10.1016/j.renene.2017.08.065
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    Cited by:

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    6. Ting-Hsuan Chien & Yu-Chuan Huang & Yuan-Yih Hsu, 2020. "Neural Network-Based Supplementary Frequency Controller for a DFIG Wind Farm," Energies, MDPI, vol. 13(20), pages 1-15, October.
    7. Wang, Huaizhi & Liu, Yangyang & Zhou, Bin & Voropai, Nikolai & Cao, Guangzhong & Jia, Youwei & Barakhtenko, Evgeny, 2020. "Advanced adaptive frequency support scheme for DFIG under cyber uncertainty," Renewable Energy, Elsevier, vol. 161(C), pages 98-109.
    8. Haixin Wang & Junyou Yang & Zhe Chen & Weichun Ge & Shiyan Hu & Yiming Ma & Yunlu Li & Guanfeng Zhang & Lijian Yang, 2018. "Gain Scheduled Torque Compensation of PMSG-Based Wind Turbine for Frequency Regulation in an Isolated Grid," Energies, MDPI, vol. 11(7), pages 1-19, June.
    9. Xiangwu Yan & Xuewei Sun, 2020. "Inertia and Droop Frequency Control Strategy of Doubly-Fed Induction Generator Based on Rotor Kinetic Energy and Supercapacitor," Energies, MDPI, vol. 13(14), pages 1-19, July.
    10. 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.
    11. Kheshti, Mostafa & Ding, Lei & Nayeripour, Majid & Wang, Xiaowei & Terzija, Vladimir, 2019. "Active power support of wind turbines for grid frequency events using a reliable power reference scheme," Renewable Energy, Elsevier, vol. 139(C), pages 1241-1254.
    12. Vasudevan, Krishnakumar R. & Ramachandaramurthy, Vigna K. & Venugopal, Gomathi & Guerrero, Josep M. & David Agundis Tinajero, Gibran, 2022. "Synergizing pico hydel and battery energy storage with adaptive synchronverter control for frequency regulation of autonomous microgrids," Applied Energy, Elsevier, vol. 325(C).
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