Analysis of Stability Stationary Point for Virtual Parameters of Grid-Forming Converter Integrated Power Systems Based on Small-Signal Model

The power grid is often assumed as an infinite bus in the research of grid-forming (GFM) converters. However, with increasing integration of renewable energy resources, the inertia and damping of actual power grids dominated by synchronous generators (SGs) are continually decreasing. The integration of large-scale GFM converters will inevitably interact with SGs in low-frequency oscillation (LFO) mode. In this paper, the small-signal model for LFO analysis of two-machine system is firstly established. The explicit analytical expressions for the dominant poles and damping ratio of LFO mode in different scenarios of two-machine system are derived using classified discussion approach with unique contributions obtained: 1) The existence of stability maximum/minimum stationary point for virtual damping/inertia of the GFM converter is proved, where the selected corresponding parameters will lead to the best/worst system stability. 2) The impact of the GFM converter on the system stability under different power grid strength is proved with a straightforward mathematical approach. 3) The theoretical analysis is extended to a generalized multi-machine system. The analytical results indicate that there exist stability stationary points for the virtual parameters of any GFM converter in any LFO mode. Finally, case studies are established to verify the validity of the analysis.

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Publication Details

Journal
IEEE Transactions on Energy Conversion
Published
2024-09-13
DOI
https://doi.org/10.1109/tec.2024.3460071
Citations
1
Primary Topic
Power Systems and Renewable Energy
Type
article
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article

Analysis of Stability Stationary Point for Virtual Parameters of Grid-Forming Converter Integrated Power Systems Based on Small-Signal Model

Tianming Gu, Jianyu Wang, Puyu Wang, Xiaoping Zhang et al.
1 citations
IEEE Transactions on Energy Conversion
Power Systems and Renewable Energy
0.17
article

Analysis of Stability Stationary Point for Virtual Parameters of Grid-Forming Converter Integrated Power Systems Based on Small-Signal Model

Tianming Gu, Jianyu Wang, Puyu Wang, Xiaoping Zhang, Xinzhou Dong, Dengpan Sun
article en
1 citations

Abstract

The power grid is often assumed as an infinite bus in the research of grid-forming (GFM) converters. However, with increasing integration of renewable energy resources, the inertia and damping of actual power grids dominated by synchronous generators (SGs) are continually decreasing. The integration of large-scale GFM converters will inevitably interact with SGs in low-frequency oscillation (LFO) mode. In this paper, the small-signal model for LFO analysis of two-machine system is firstly established. The explicit analytical expressions for the dominant poles and damping ratio of LFO mode in different scenarios of two-machine system are derived using classified discussion approach with unique contributions obtained: 1) The existence of stability maximum/minimum stationary point for virtual damping/inertia of the GFM converter is proved, where the selected corresponding parameters will lead to the best/worst system stability. 2) The impact of the GFM converter on the system stability under different power grid strength is proved with a straightforward mathematical approach. 3) The theoretical analysis is extended to a generalized multi-machine system. The analytical results indicate that there exist stability stationary points for the virtual parameters of any GFM converter in any LFO mode. Finally, case studies are established to verify the validity of the analysis.

IEEE Transactions on Energy ConversionVol. 40(2)
Nanjing University of Science and Technology (CN), University of Birmingham (GB), Tsinghua University (CN)
Affordable and clean energy
Openalex Percentile: Top 46%
Power Systems and Renewable Energy
0.17
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Analysis of Stability Stationary Point for Virtual Parameters of Grid-Forming Converter Integrated Power Systems Based on Small-Signal Model — Tianming Gu, Jianyu Wang, et al. · IEEE Transactions on Energy Conversion (2024) | TGRS Research Map | TGRS