Comprehensive small-signal modeling and Prony analysis-based validation of synchronous interconnected microgrids

Mobin Naderi, Yousef Khayat, Qobad Shafiee, Tomislav Dragicevic, Hassan Bevrani, Frede Blaabjerg*

*Corresponding author for this work

    Research output: Contribution to journalJournal articleResearchpeer-review

    174 Downloads (Pure)

    Abstract

    The small-signal stability of large-scale interconnected microgrids needs to be analyzed to find the most dominant dynamic behaviors. In this paper, a comprehensive and easy-expandable module-based modeling method is proposed, which is expandable to many interconnected AC microgrids through circuit breakers, i.e. synchronous microgrids. Another certain requirement is validating such a large model, which is satisfied using a well-known Prony analysis method. The large-scale interconnected AC microgrids are implemented in a real-time digital simulator to provide input waveforms for the Prony analysis. On the other hand, the dynamic modes of the proposed model are calculated by eigenvalue analysis, and their contributions in each state variable are identified using the participation matrix. In the proposed validation method, the participating modes in each state variable are compared with the natural frequencies of its estimated waveform by Prony analysis. It is concluded that there is a good matching between the participating modes in the state variables and the contributing frequencies in their waveforms that verifies the proposed modeling method. (C) 2021 The Authors. Published by Elsevier Ltd.
    Original languageEnglish
    JournalEnergy Reports
    Volume7
    Pages (from-to)6677-6689
    DOIs
    Publication statusPublished - 2021

    Keywords

    • Interconnected microgrids
    • Small-signal modeling
    • Prony analysis
    • Eigenvalue analysis
    • Model validation

    Fingerprint

    Dive into the research topics of 'Comprehensive small-signal modeling and Prony analysis-based validation of synchronous interconnected microgrids'. Together they form a unique fingerprint.

    Cite this