Data-Light Oscillation Mode Identification for Fast Stability Assessment of Grid-Tied Converters

Rui Kong; Subham Sahoo; Shuyu Ou; Xiangyu Meng; Guoqing Gao; Frede Blaabjerg

doi:10.1109/TPEL.2025.3556387

Data-Light Oscillation Mode Identification for Fast Stability Assessment of Grid-Tied Converters

Rui Kong^*, Subham Sahoo, Shuyu Ou, Xiangyu Meng, Guoqing Gao, Frede Blaabjerg

^*Corresponding author for this work

Research output: Contribution to journal › Journal article › Research › peer-review

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Abstract

Dynamic mode decomposition (DMD) is an effective data-driven oscillation mode identification method for instability identification in grid-tied converters. However, time-consuming computation and empirical setting of parameters limit its practical application in rapid stability assessment. This article introduces data-light dynamic mode decomposition (DL-DMD) by integrating the conventional dynamic mode decomposition (DMD) algorithm with harmonic state space theory, which significantly improves computational speed while providing a bandwidth-oriented interpretation for parameter selection in correspondence with the identifiable frequency range of modes. The effectiveness and advantages of the proposed method are verified through offline analysis and online tests based on an experimental platform.

Original language	English
Article number	10946229
Journal	I E E E Transactions on Power Electronics
Volume	40
Issue number	8
Pages (from-to)	11170 - 11181
Number of pages	12
ISSN	0885-8993
DOIs	https://doi.org/10.1109/TPEL.2025.3556387
Publication status	Published - 31 Mar 2025

Bibliographical note

Publisher Copyright:
© 1986-2012 IEEE.

Keywords

Dynamic Mode Decomposition
Grid-tied converter
Harmonic State Space
Oscillation modes
Stability assessment
oscillation mode identification
grid-tied converter
Dynamic mode decomposition (DMD)
harmonic state space (HSS)

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10.1109/TPEL.2025.3556387

Accepted Author ManuscriptAccepted author manuscript, 2.78 MBLicence: CC BY 4.0

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title = "Data-Light Oscillation Mode Identification for Fast Stability Assessment of Grid-Tied Converters",

abstract = "Dynamic mode decomposition (DMD) is an effective data-driven oscillation mode identification method for instability identification in grid-tied converters. However, time-consuming computation and empirical setting of parameters limit its practical application in rapid stability assessment. This article introduces data-light dynamic mode decomposition (DL-DMD) by integrating the conventional dynamic mode decomposition (DMD) algorithm with harmonic state space theory, which significantly improves computational speed while providing a bandwidth-oriented interpretation for parameter selection in correspondence with the identifiable frequency range of modes. The effectiveness and advantages of the proposed method are verified through offline analysis and online tests based on an experimental platform.",

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author = "Rui Kong and Subham Sahoo and Shuyu Ou and Xiangyu Meng and Guoqing Gao and Frede Blaabjerg",

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AU - Sahoo, Subham

AU - Ou, Shuyu

AU - Meng, Xiangyu

AU - Gao, Guoqing

AU - Blaabjerg, Frede

PY - 2025/3/31

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N2 - Dynamic mode decomposition (DMD) is an effective data-driven oscillation mode identification method for instability identification in grid-tied converters. However, time-consuming computation and empirical setting of parameters limit its practical application in rapid stability assessment. This article introduces data-light dynamic mode decomposition (DL-DMD) by integrating the conventional dynamic mode decomposition (DMD) algorithm with harmonic state space theory, which significantly improves computational speed while providing a bandwidth-oriented interpretation for parameter selection in correspondence with the identifiable frequency range of modes. The effectiveness and advantages of the proposed method are verified through offline analysis and online tests based on an experimental platform.

AB - Dynamic mode decomposition (DMD) is an effective data-driven oscillation mode identification method for instability identification in grid-tied converters. However, time-consuming computation and empirical setting of parameters limit its practical application in rapid stability assessment. This article introduces data-light dynamic mode decomposition (DL-DMD) by integrating the conventional dynamic mode decomposition (DMD) algorithm with harmonic state space theory, which significantly improves computational speed while providing a bandwidth-oriented interpretation for parameter selection in correspondence with the identifiable frequency range of modes. The effectiveness and advantages of the proposed method are verified through offline analysis and online tests based on an experimental platform.

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KW - Grid-tied converter

KW - Harmonic State Space

KW - Oscillation modes

KW - Stability assessment

KW - oscillation mode identification

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Data-Light Oscillation Mode Identification for Fast Stability Assessment of Grid-Tied Converters

Abstract

Bibliographical note

Keywords

UN SDGs

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AUB Link

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Modeling, Analysis and Suppression of Wide band Instability in Large Scale Power Systems with Single Phase and Three Phase VSCs

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Data-Light Oscillation Mode Identification for Fast Stability Assessment of Grid-Tied Converters

Abstract

Bibliographical note

Keywords

UN SDGs

Access to Document

AUB Link

Other files and links

Fingerprint

Projects

Modeling, Analysis and Suppression of Wide band Instability in Large Scale Power Systems with Single Phase and Three Phase VSCs

Cite this