Real-time transient stability prediction and coherency identification in power systems using Koopman mode analysis

Sevda Jafarzadeh, Istemihan Genc*, Arye Nehorai

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

17 Citations (Scopus)

Abstract

In this paper, we propose a novel methodology based on Koopman mode analysis to predict the transient stability of a power system in real-time. The method assesses the stability of the system based on a sliding sampling window of PMU measurements, and it detects the evolving instabilities by predicting future samples and investigating the computed Koopman eigenvalues. This approach is also able to identify alarm conditions, which include slowly evolving instabilities that may not be detected by predicting future samples in a limited time horizon. Identifying these conditions provides additional time to prepare a proper set of emergency control actions to be performed when necessary. Using the proposed method, groups of coherent generators that play roles in the evolving instabilities can also be identified, contributing to the design of a defensive islanding scheme for unstable cases. The efficacy of the proposed approach is demonstrated by simulating its performance with three test systems of different scales.

Original languageEnglish
Article number107565
JournalElectric Power Systems Research
Volume201
DOIs
Publication statusPublished - Dec 2021

Bibliographical note

Publisher Copyright:
© 2021

Funding

The study is supported by The Scientific Research Projects (BAP) Coordination Unit of Istanbul Technical University (ITU) under project no. 41538. The authors would like to thank ITU for supporting the project and to the Turkish Electricity Transmission Company TEIAS for providing the model of the Turkish power system.

FundersFunder number
Istanbul Teknik Üniversitesi41538

    Keywords

    • Dynamic mode decomposition
    • Koopman mode analysis
    • Transient stability prediction

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