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An Adaptive Inertia and Damping Control Strategy Based on Enhanced Virtual Synchronous Generator Model

Author

Listed:
  • Aleksey Suvorov

    (School of Energy & Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Alisher Askarov

    (School of Energy & Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Nikolay Ruban

    (School of Energy & Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Vladimir Rudnik

    (School of Energy & Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Pavel Radko

    (School of Energy & Power Engineering, National Research Tomsk Polytechnic University, Tomsk 634050, Russia)

  • Andrey Achitaev

    (Department of Hydropower, Hydroelectric Power Plants, Electricity Systems and Electricity Networks, Siberian Federal University, Krasnoyarsk 660041, Russia)

  • Konstantin Suslov

    (Department of Power Supply and Electrical Engineering, Irkutsk National Research Technical University, Irkutsk 664074, Russia)

Abstract

In modern converter-dominated power systems, total inertia is very variable and depends on the share of power generated by renewable-based converter-interfaced generation (CIG) at each specific moment. As a result, the limits required by the grid codes on the rate of change of frequency and its nadir or zenith during disturbances become challenging to achieve with conventional control approaches. Therefore, the transition to a novel control strategy of CIG with a grid-forming power converter is relevant. For this purpose, a control algorithm based on a virtual synchronous generator (VSG) is used, which simulates the properties and capabilities of a conventional synchronous generation. However, due to continuously changing operating conditions in converter-dominated power systems, the virtual inertia formed by VSG must be adaptive. At the same time, the efficiency of adaptive algorithms strongly depends on the used VSG structure. In this connection, this paper proposes an enhanced VSG structure for which the transfer function of the active power control loop was formed. With the help of it, the advantages over the conventional VSG structure were proven, which are necessary for the effective adaptive control of the VSG parameters. Then, the analysis of the impact of the VSG parameters on the dynamic response using the transient characteristics in the time domain was performed. Based on the results obtained, adaptive algorithms for independent control of the virtual inertia and the parameters of the VSG damper winding were developed. The performed mathematical modeling confirmed the reliable and effective operation of the developed adaptive control algorithms and the enhanced VSG structure. The theoretical and experimental results obtained in this paper indicate the need for simultaneous development and improvement of both adaptive control algorithms and VSG structures used for this purpose.

Suggested Citation

  • Aleksey Suvorov & Alisher Askarov & Nikolay Ruban & Vladimir Rudnik & Pavel Radko & Andrey Achitaev & Konstantin Suslov, 2023. "An Adaptive Inertia and Damping Control Strategy Based on Enhanced Virtual Synchronous Generator Model," Mathematics, MDPI, vol. 11(18), pages 1-29, September.
    • Handle: RePEc:gam:jmathe:v:11:y:2023:i:18:p:3938-:d:1241303
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    References listed on IDEAS

    as
    1. Pavel Ilyushin & Vladislav Volnyi & Konstantin Suslov & Sergey Filippov, 2023. "State-of-the-Art Literature Review of Power Flow Control Methods for Low-Voltage AC and AC-DC Microgrids," Energies, MDPI, vol. 16(7), pages 1-35, March.
    2. Cheng, Yi & Azizipanah-Abarghooee, Rasoul & Azizi, Sadegh & Ding, Lei & Terzija, Vladimir, 2020. "Smart frequency control in low inertia energy systems based on frequency response techniques: A review," Applied Energy, Elsevier, vol. 279(C).
    3. Rajan, Rijo & Fernandez, Francis M. & Yang, Yongheng, 2021. "Primary frequency control techniques for large-scale PV-integrated power systems: A review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
    4. Xuhong Yang & Hui Li & Wei Jia & Zhongxin Liu & Yu Pan & Fengwei Qian, 2022. "Adaptive Virtual Synchronous Generator Based on Model Predictive Control with Improved Frequency Stability," Energies, MDPI, vol. 15(22), pages 1-13, November.
    5. Pavel Ilyushin & Vladislav Volnyi & Konstantin Suslov & Sergey Filippov, 2022. "Review of Methods for Addressing Challenging Issues in the Operation of Protection Devices in Microgrids with Voltages of up to 1 kV That Integrates Distributed Energy Resources," Energies, MDPI, vol. 15(23), pages 1-22, December.
    6. Pavel Ilyushin & Sergey Filippov & Aleksandr Kulikov & Konstantin Suslov & Dmitriy Karamov, 2022. "Intelligent Control of the Energy Storage System for Reliable Operation of Gas-Fired Reciprocating Engine Plants in Systems of Power Supply to Industrial Facilities," Energies, MDPI, vol. 15(17), pages 1-21, August.
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