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Online Parameter Estimation for Fault Identification in Multi-Terminal DC Distribution Grids

Author

Listed:
  • Ting Wang

    (Institute for Automation of Complex Power Systems, E.ON Energy Research Center, RWTH Aachen University, 52074 Aachen, Germany)

  • Liliuyuan Liang

    (Contemporary Amperex Technology Co., Limited (CATL), Ningde 352100, China)

  • Xinrang Feng

    (Envision Digital Shanghai, Shanghai 200050, China)

  • Ferdinanda Ponci

    (Institute for Automation of Complex Power Systems, E.ON Energy Research Center, RWTH Aachen University, 52074 Aachen, Germany)

  • Antonello Monti

    (Institute for Automation of Complex Power Systems, E.ON Energy Research Center, RWTH Aachen University, 52074 Aachen, Germany)

Abstract

Fast and accurate identification of short-circuit faults is important for post-fault service restoration and maintenance in DC distribution grids. Yet multiple power sources and complex system topologies complicate the fault identification in multi-terminal DC distribution grids. To address this challenge, this paper introduces an approach that achieves fast online identification of both the location and the severity of faults in multi-terminal DC distribution grids. First, a generic model describing the dynamic response of DC lines to both pole-to-ground and pole-to-pole faults with fault currents injected from both line ends is developed. On this basis, a Kalman filter is adopted to estimate both the fault location and resistance. In the real-time simulation of various fault scenarios in a three-terminal DC distribution grid model with Opal-RT platform, the proposed method is proved to be effective with a short response time of less than 1 ms.

Suggested Citation

  • Ting Wang & Liliuyuan Liang & Xinrang Feng & Ferdinanda Ponci & Antonello Monti, 2021. "Online Parameter Estimation for Fault Identification in Multi-Terminal DC Distribution Grids," Energies, MDPI, vol. 14(18), pages 1-15, September.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:18:p:5630-:d:630975
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    References listed on IDEAS

    as
    1. Yan Xu & Jingyan Liu & Weijia Jin & Yuan Fu & Hui Yang, 2018. "Fault Location Method for DC Distribution Systems Based on Parameter Identification," Energies, MDPI, vol. 11(8), pages 1-18, July.
    2. Liye Xiao & Liangzhen Lin & Yi Liu, 2011. "Discussions on the Architecture and Operation Mode of Future Power Grids," Energies, MDPI, vol. 4(7), pages 1-11, July.
    3. Saeed Zaman Jamali & Syed Basit Ali Bukhari & Muhammad Omer Khan & Muhammad Mehdi & Chul-Ho Noh & Gi-Hyeon Gwon & Chul-Hwan Kim, 2018. "Protection Scheme of a Last Mile Active LVDC Distribution Network with Reclosing Option," Energies, MDPI, vol. 11(5), pages 1-20, April.
    4. Waqas Javed & Dong Chen & Mohamed Emad Farrag & Yan Xu, 2019. "System Configuration, Fault Detection, Location, Isolation and Restoration: A Review on LVDC Microgrid Protections," Energies, MDPI, vol. 12(6), pages 1-30, March.
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    Cited by:

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    2. Rodolfo Araneo & Salvatore Celozzi & Stefano Lauria & Erika Stracqualursi & Gianfranco Di Lorenzo & Marco Graziani, 2022. "Recent Trends in Power Systems Modeling and Analysis," Energies, MDPI, vol. 15(23), pages 1-7, December.

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