Dynamic interaction analysis of power systems connected with grid-forming converters

Renewable energy sources (RESs) have been widely integrated into power systems to reduce carbon emissions. However, the increased penetration of RESs has led to a significant reduction in system inertia. Grid-forming converters (GFMs) have emerged as a promising technology to enhance grid inertia and improve system stability. Due to their dynamic similarity with synchronous generators (SGs), GFMs can interact with AC grids among multiple control-loops. In this paper, a detailed state-space model of power system is developed to analyze the complex interactions between GFMs and AC grids. A relative interaction array (RIA) is proposed to quantify the interaction between GFMs and AC grids. The results reveal that strong interactions occur in the low-frequency range. Both variations in the GFM’s active power reference and load disturbances in the AC grid can trigger these interactions and result in system oscillations. Key parameters affecting the interaction degree are identified, and a supplementary damping controller is designed for the GFM to mitigate the interactions and enhance system damping. The effectiveness of the proposed RIA method and controller design is validated through time-domain simulations in two test systems. • A state space model of a two-area system with GFMs is derived for dynamic analysis. • An RIA method is proposed to quantify the interaction between different subsystems. • An damping controller is designed for GFMs to mitigate the negative interactions.

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Publication Details

Journal
International Journal of Electrical Power & Energy Systems
Published
2025-08-08
DOI
https://doi.org/10.1016/j.ijepes.2025.110908
Citations
2
Primary Topic
Microgrid Control and Optimization
Type
article
Field-Weighted Citation Impact
2.43

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article

Dynamic interaction analysis of power systems connected with grid-forming converters

Fang Chen, Wenjia Zhao, Weiyu Wang, Jun Wei Yan et al.
2 citations
International Journal of Electrical Power & Energy Systems
Microgrid Control and Optimization
2.43
article

Dynamic interaction analysis of power systems connected with grid-forming converters

Fang Chen, Wenjia Zhao, Weiyu Wang, Jun Wei Yan, Zhilin Yang, Xinchi Wei
article en
2 citations

Abstract

Renewable energy sources (RESs) have been widely integrated into power systems to reduce carbon emissions. However, the increased penetration of RESs has led to a significant reduction in system inertia. Grid-forming converters (GFMs) have emerged as a promising technology to enhance grid inertia and improve system stability. Due to their dynamic similarity with synchronous generators (SGs), GFMs can interact with AC grids among multiple control-loops. In this paper, a detailed state-space model of power system is developed to analyze the complex interactions between GFMs and AC grids. A relative interaction array (RIA) is proposed to quantify the interaction between GFMs and AC grids. The results reveal that strong interactions occur in the low-frequency range. Both variations in the GFM’s active power reference and load disturbances in the AC grid can trigger these interactions and result in system oscillations. Key parameters affecting the interaction degree are identified, and a supplementary damping controller is designed for the GFM to mitigate the interactions and enhance system damping. The effectiveness of the proposed RIA method and controller design is validated through time-domain simulations in two test systems. • A state space model of a two-area system with GFMs is derived for dynamic analysis. • An RIA method is proposed to quantify the interaction between different subsystems. • An damping controller is designed for GFMs to mitigate the negative interactions.

International Journal of Electrical Power & Energy SystemsVol. 171
Changsha University of Science and Technology (CN)
Science and Technology Commission of Shanghai Municipality, State Grid Shanghai Municipal Electric Power Company, Science and Technology Innovation Plan Of Shanghai Science and Technology Commission
Affordable and clean energy
Openalex Percentile: Top 10%
Microgrid Control and Optimization
2.43
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