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An Improved Virtual Inertia Control Strategy for Low Voltage AC Microgrids with Hybrid Energy Storage Systems

Author

Listed:
  • Ruiming Liu

    (College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)

  • Shengtie Wang

    (College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)

  • Guangchen Liu

    (College of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China)

  • Sufang Wen

    (College of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China)

  • Jianwei Zhang

    (College of Electric Power, Inner Mongolia University of Technology, Hohhot 010080, China)

  • Yuechao Ma

    (College of Energy and Power Engineering, Inner Mongolia University of Technology, Hohhot 010051, China)

Abstract

This paper proposes a novel virtual inertia control (VIC) method based on a feedforward decoupling strategy to address the low inertia issue of power-converter-interfaced microgrids. The feedforward control scheme is employed to eliminate the coupling between active and reactive power caused by line impedance. The active power-voltage droop can be applied to the battery converter in the hybrid energy storage system (HESS). A novel VIC method is developed for the supercapacitor (SC) converter of HESS to increase the inertia of the microgrid. Detailed small-signal modeling of the SC converter with the proposed VIC was conducted, and the transfer function model was obtained. Parameter analysis of the virtual inertia and virtual damping was carried out with the pole-zero map method, and the step response characteristic of output voltage amplitude with power variation was analyzed in detail, deriving the parameter design principle. The simulation study verifies the effectiveness and validity of the proposed control strategy. The proposed feedforward decoupling method and VIC can be widely applied in microgrids to enhance inertia and improve their power quality.

Suggested Citation

  • Ruiming Liu & Shengtie Wang & Guangchen Liu & Sufang Wen & Jianwei Zhang & Yuechao Ma, 2022. "An Improved Virtual Inertia Control Strategy for Low Voltage AC Microgrids with Hybrid Energy Storage Systems," Energies, MDPI, vol. 15(2), pages 1-21, January.
    • Handle: RePEc:gam:jeners:v:15:y:2022:i:2:p:442-:d:720686
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    Citations

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    Cited by:

    1. Guodong Liu & Maximiliano F. Ferrari & Thomas B. Ollis & Kevin Tomsovic, 2022. "An MILP-Based Distributed Energy Management for Coordination of Networked Microgrids," Energies, MDPI, vol. 15(19), pages 1-20, September.
    2. Farhad Amiri & Mohsen Eskandari & Mohammad Hassan Moradi, 2023. "Virtual Inertia Control in Autonomous Microgrids via a Cascaded Controller for Battery Energy Storage Optimized by Firefly Algorithm and a Comparison Study with GA, PSO, ABC, and GWO," Energies, MDPI, vol. 16(18), pages 1-22, September.
    3. Guodong Liu & Maximiliano F. Ferrari & Thomas B. Ollis & Aditya Sundararajan & Mohammed Olama & Yang Chen, 2023. "Distributed Energy Management for Networked Microgrids with Hardware-in-the-Loop Validation," Energies, MDPI, vol. 16(7), pages 1-27, March.
    4. Amr Saleh & Hany M. Hasanien & Rania A. Turky & Balgynbek Turdybek & Mohammed Alharbi & Francisco Jurado & Walid A. Omran, 2023. "Optimal Model Predictive Control for Virtual Inertia Control of Autonomous Microgrids," Sustainability, MDPI, vol. 15(6), pages 1-25, March.
    5. Hamid Saeed Khan & Attaullah Y. Memon, 2022. "Robust Output Feedback Control of the Voltage Source Inverter in an AC Microgrid," Energies, MDPI, vol. 15(15), pages 1-21, August.
    6. Guodong Liu & Zhi Li & Yaosuo Xue & Kevin Tomsovic, 2022. "Microgrid Assisted Design for Remote Areas," Energies, MDPI, vol. 15(10), pages 1-23, May.
    7. Guodong Liu & Thomas B. Ollis & Maximiliano F. Ferrari & Aditya Sundararajan & Kevin Tomsovic, 2022. "Robust Scheduling of Networked Microgrids for Economics and Resilience Improvement," Energies, MDPI, vol. 15(6), pages 1-19, March.

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