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A novel Koopman-inspired method for the secondary control of microgrids with grid-forming and grid-following sources

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  • Gong, Xun
  • Wang, Xiaozhe

Abstract

This paper proposes an online data-driven Koopman-inspired identification and control method for microgrid secondary voltage and frequency control. Unlike typical data-driven methods, the proposed method requires no warm-up training yet with guaranteed bounded-input–bounded-output (BIBO) stability and even asymptotic stability under some mild conditions. The proposed method estimates the Koopman state space model adaptively so as to perform effective secondary voltage and frequency control that can handle microgrid nonlinearity and uncertainty. Case studies in the 4-bus and 13-bus microgrid test systems (with grid-forming and grid-following sources) demonstrate the effectiveness and robustness of the proposed identification and control method subject to the change of operating conditions and large disturbances (e.g., microgrid mode transitions, generation/load variations) even with measurement noises and time delays.

Suggested Citation

  • Gong, Xun & Wang, Xiaozhe, 2023. "A novel Koopman-inspired method for the secondary control of microgrids with grid-forming and grid-following sources," Applied Energy, Elsevier, vol. 333(C).
    • Handle: RePEc:eee:appene:v:333:y:2023:i:c:s0306261922018888
    DOI: 10.1016/j.apenergy.2022.120631
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    References listed on IDEAS

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    1. Jinyoung Lee & Jung-Su Kim & Hyungbo Shim, 2012. "Disc margins of the discrete-time LQR and its application to consensus problem," International Journal of Systems Science, Taylor & Francis Journals, vol. 43(10), pages 1891-1900.
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    Cited by:

    1. Mario Versaci & Fabio La Foresta, 2024. "Fuzzy Approach for Managing Renewable Energy Flows for DC-Microgrid with Composite PV-WT Generators and Energy Storage System," Energies, MDPI, vol. 17(2), pages 1-31, January.
    2. Irani, Fatemeh Negar & Soleimani, Mohammadjavad & Yadegar, Meysam & Meskin, Nader, 2024. "Deep transfer learning strategy in intelligent fault diagnosis of gas turbines based on the Koopman operator," Applied Energy, Elsevier, vol. 365(C).
    3. Gong, Xun & Wang, Xiaozhe & Cao, Bo, 2023. "On data-driven modeling and control in modern power grids stability: Survey and perspective," Applied Energy, Elsevier, vol. 350(C).

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