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The increasing integration of inverter-based resources (IBRs) into power systems is essential for reducing greenhouse gas emissions; however, it introduces instability mechanisms that have not been encountered in synchronous generator (SG)-based systems. These instabilities arise from interactions between the characteristics of the connected power grid and the parameters of IBRs, including both control and system parameters. State-space modeling (SSM) effectively represents small-scale systems and their dynamics. However, it struggles with inaccessible grid data and high-dimensional complexity. Conversely, impedance-based stability analysis identifies instability even when system information is confidential or before faults occur. However, it lacks a direct link to adjustable IBR parameters. To address these limitations, this study integrates impedance-based analysis with analytical modeling of IBRs. The major finding of this study is that measuring the impedance of both the system and the IBR, while adjusting only the IBR parameters, effectively mitigates instability and stabilizes the system. The IBR model tuning is verified by comparing MATLAB/Simulink numerical impedance with that measured in a university lab-scale microgrid (MG), where the IBR connects via a grid-following (GFL) inverter to a primary grid-forming (GFM) inverter.

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System Stability Enhancement Via Impedance Shaping Based on Eigenvalue Sensitivity Analysis of Grid-Connected Inverters

  • 会议论文

  • 发表日期：

    2025年

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  • Yuko Hirase,
  • Tomoya Ide,
  • Hajime Urai,
  • Hiroshi Kikusato,
  • Dai Orihara,
  • Jun Hashimoto

摘要

The increasing integration of inverter-based resources (IBRs) into power systems is essential for reducing greenhouse gas emissions; however, it introduces instability mechanisms that have not been encountered in synchronous generator (SG)-based systems. These instabilities arise from interactions between the characteristics of the connected power grid and the parameters of IBRs, including both control and system parameters. State-space modeling (SSM) effectively represents small-scale systems and their dynamics. However, it struggles with inaccessible grid data and high-dimensional complexity. Conversely, impedance-based stability analysis identifies instability even when system information is confidential or before faults occur. However, it lacks a direct link to adjustable IBR parameters. To address these limitations, this study integrates impedance-based analysis with analytical modeling of IBRs. The major finding of this study is that measuring the impedance of both the system and the IBR, while adjusting only the IBR parameters, effectively mitigates instability and stabilizes the system. The IBR model tuning is verified by comparing MATLAB/Simulink numerical impedance with that measured in a university lab-scale microgrid (MG), where the IBR connects via a grid-following (GFL) inverter to a primary grid-forming (GFM) inverter.