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Converter-Based Power Line Emulators for Testing Grid-Forming Converters Under Various Grid Strength Conditions

Author

Listed:
  • Chul-Sang Hwang

    (Smart Grid Research Division, The Korea Electrotechnology Research Institute, 27 Dosi-Cheomdan Saneop-ro, Nam-gu, Gwangju-si 61751, Republic of Korea)

  • Young-Woo Youn

    (Smart Grid Research Division, The Korea Electrotechnology Research Institute, 27 Dosi-Cheomdan Saneop-ro, Nam-gu, Gwangju-si 61751, Republic of Korea)

  • Heung-Kwan Choi

    (Smart Grid Research Division, The Korea Electrotechnology Research Institute, 27 Dosi-Cheomdan Saneop-ro, Nam-gu, Gwangju-si 61751, Republic of Korea)

  • Tae-Jin Kim

    (Smart Grid Research Division, The Korea Electrotechnology Research Institute, 27 Dosi-Cheomdan Saneop-ro, Nam-gu, Gwangju-si 61751, Republic of Korea)

Abstract

Grid-forming (GFM) converters have been critical in DER-dominant power systems, ensuring stability, but their performance is highly sensitive to grid conditions such as system strength. Testing GFM converters under a wide range of grid strengths (from strong high-inertia systems to very weak grids) and fault scenarios is challenging, as traditional test facilities and static grid simulators have limitations. To address this problem, this paper proposes a converter-based power line emulator that provides a flexible, programmable grid environment for GFM converter testing. The emulator uses power electronic converters to mimic transmission line characteristics, allowing for the adjustment of effective grid strength (e.g., short-circuit ratio changes). The proposed approach is validated through detailed PSCAD simulations, demonstrating its ability to provide scalable weak-grid emulation and comprehensive validation of GFM converter control strategies and stability under various grid conditions. This research highlights that the converter-based emulator offers enhanced flexibility and cost-effectiveness over traditional testing setups, making it an effective tool for GFM converter performance test.

Suggested Citation

  • Chul-Sang Hwang & Young-Woo Youn & Heung-Kwan Choi & Tae-Jin Kim, 2025. "Converter-Based Power Line Emulators for Testing Grid-Forming Converters Under Various Grid Strength Conditions," Sustainability, MDPI, vol. 17(15), pages 1-18, July.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:15:p:6690-:d:1707474
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    References listed on IDEAS

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    1. Wilkinson, Sam & Maticka, Martin J. & Liu, Yue & John, Michele, 2021. "The duck curve in a drying pond: The impact of rooftop PV on the Western Australian electricity market transition," Utilities Policy, Elsevier, vol. 71(C).
    2. Huber, Matthias & Dimkova, Desislava & Hamacher, Thomas, 2014. "Integration of wind and solar power in Europe: Assessment of flexibility requirements," Energy, Elsevier, vol. 69(C), pages 236-246.
    3. Hou, Qingchun & Zhang, Ning & Du, Ershun & Miao, Miao & Peng, Fei & Kang, Chongqing, 2019. "Probabilistic duck curve in high PV penetration power system: Concept, modeling, and empirical analysis in China," Applied Energy, Elsevier, vol. 242(C), pages 205-215.
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