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  Small-Signal Stability of Multi-Converter Infeed Power Grids with Symmetry

Yu, J., Yang, Z., Kurths, J., Zhan, M. (2021): Small-Signal Stability of Multi-Converter Infeed Power Grids with Symmetry. - Symmetry, 13, 2, 157.
https://doi.org/10.3390/sym13020157

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Item Permalink: https://publications.pik-potsdam.de/pubman/item/item_25473 Version Permalink: https://publications.pik-potsdam.de/pubman/item/item_25473_1
Genre: Journal Article

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 Creators:
Yu, Jiawei1, Author
Yang, Ziqian1, Author
Kurths, Jürgen2, Author              
Zhan, Meng1, Author
Affiliations:
1External Organizations, ou_persistent22              
2Potsdam Institute for Climate Impact Research, ou_persistent13              

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 Abstract: Traditional power systems have been gradually shifting to power-electronic-based ones, with more power electronic devices (including converters) incorporated recently. Faced with much more complicated dynamics, it is a great challenge to uncover its physical mechanisms for system stability and/or instability (oscillation). In this paper, we first establish a nonlinear model of a multi-converter power system within the DC-link voltage timescale, from the first principle. Then, we obtain a linearized model with the associated characteristic matrix, whose eigenvalues determine the system stability, and finally get independent subsystems by using symmetry approximation conditions under the assumptions that all converters’ parameters and their susceptance to the infinite bus (Bg) are identical. Based on these mathematical analyses, we find that the whole system can be decomposed into several equivalent single-converter systems and its small-signal stability is solely determined by a simple converter system connected to an infinite bus under the same susceptance Bg. These results of large-scale multi-converter analysis help to understand the power-electronic-based power system dynamics, such as renewable energy integration. As well, they are expected to stimulate broad interests among researchers in the fields of network dynamics theory and applications.

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 Dates: 2021-01-192021-01-202021-01-20
 Publication Status: Finally published
 Pages: -
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 Table of Contents: -
 Rev. Type: Peer
 Identifiers: DOI: 10.3390/sym13020157
MDB-ID: No data to archive
PIKDOMAIN: RD4 - Complexity Science
Organisational keyword: RD4 - Complexity Science
Research topic keyword: Complex Networks
Research topic keyword: Energy
Research topic keyword: Nonlinear Dynamics
Research topic keyword: Sustainable Development
Model / method: Machine Learning
 Degree: -

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Title: Symmetry
Source Genre: Journal, Scopus, p3, oa
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Pages: - Volume / Issue: 13 (2) Sequence Number: 157 Start / End Page: - Identifier: CoNE: https://publications.pik-potsdam.de/cone/journals/resource/201801261