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A Multi-Stage Resilience Enhancement Method for Distribution Networks Employing Transportation and Hydrogen Energy Systems

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  • Xi Chen

    (Tianjin Key Laboratory of New Energy Power Conversion, Transmission and Intelligent Control, Tianjin University of Technology, Tianjin 300384, China)

  • Jiancun Liu

    (Tianjin Key Laboratory of New Energy Power Conversion, Transmission and Intelligent Control, Tianjin University of Technology, Tianjin 300384, China)

  • Pengfei Li

    (Tianjin Key Laboratory of New Energy Power Conversion, Transmission and Intelligent Control, Tianjin University of Technology, Tianjin 300384, China)

  • Junzhi Ren

    (State Key Laboratory of Intelligent Power Distribution Equipment and System, Tianjin University, Tianjin 300072, China)

  • Delong Zhang

    (Tianjin Key Laboratory of New Energy Power Conversion, Transmission and Intelligent Control, Tianjin University of Technology, Tianjin 300384, China)

  • Xuesong Zhou

    (Tianjin Key Laboratory of New Energy Power Conversion, Transmission and Intelligent Control, Tianjin University of Technology, Tianjin 300384, China)

Abstract

The resilience and sustainable development of modern power distribution systems faces escalating challenges due to increasing renewable integration and extreme events. Traditional single-system approaches often overlook the spatiotemporal coordination of cross-domain restoration resources. In this paper, we propose a multi-stage resilience enhancement method that employs transportation and hydrogen energy systems. This approach coordinates the pre-event preventive allocation and multi-stage collaborative scheduling of diverse restoration resources, including remote-controlled switches (RCSs), mobile hydrogen emergency resources (MHERs), and hydrogen production and refueling stations (HPRSs). The proposed framework supports cross-stage dynamic optimization scheduling, enabling the development of adaptive resource dispatch strategies tailored to the characteristics of different stages, including prevention, fault isolation, and service restoration. The model is applicable to complex scenarios involving dynamically changing network topologies and is formulated as a mixed-integer linear programming (MILP) problem. Case studies based on the IEEE 33-bus system show that the proposed method can restore a distribution system’s resilience to approximately 87% of its normal level following extreme events.

Suggested Citation

  • Xi Chen & Jiancun Liu & Pengfei Li & Junzhi Ren & Delong Zhang & Xuesong Zhou, 2025. "A Multi-Stage Resilience Enhancement Method for Distribution Networks Employing Transportation and Hydrogen Energy Systems," Sustainability, MDPI, vol. 17(19), pages 1-19, September.
  • Handle: RePEc:gam:jsusta:v:17:y:2025:i:19:p:8691-:d:1759348
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