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author:

Yingsheng, Yang (Yingsheng, Yang.) [1] | Zheng, Wendi (Zheng, Wendi.) [2] | Lai, Zhenhua (Lai, Zhenhua.) [3] | Zhao, Yuhang (Zhao, Yuhang.) [4] | Wang, Jiangteng (Wang, Jiangteng.) [5]

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EI Scopus

Abstract:

In response to the urgent need for improving distribution network resilience under frequent extreme natural disasters, a dynamic collaborative recovery strategy incorporating mobile fuel cell vehicles (MFCV) is proposed. First, an emergency response collaborative optimization model is constructed. At the topology reconstruction level, network dynamic partitioning is achieved through remote control switches (RCS), coordinating the spatiotemporal coupling characteristics of preset energy storage systems and MFCV. At the resource scheduling level, an MFCV dynamic scheduling model considering traffic network constraints is established, introducing hydrogen replenishment to characterize MFCV's endurance characteristics. Second, for the bilinear non-convex problem, the original problem is transformed into mixed-integer linear programming (MILP) through linearization methods, while introducing virtual power flow constraints to ensure network radial structure. Finally, comparative experiments based on the improved IEEE 33-node distribution system and coupled traffic network demonstrate that, compared to traditional post-disaster MFCV scheduling schemes, the proposed method can significantly reduce load loss and improve distribution network resilience and economics. © 2025 IEEE.

Keyword:

Computer system recovery Data storage equipment Distributed computer systems Electric power distribution Embedded systems Emergency services Fuel cells Fuel cell vehicles Integer programming Mixed-integer linear programming Remote control Vehicles

Community:

  • [ 1 ] [Yingsheng, Yang]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 2 ] [Zheng, Wendi]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 3 ] [Lai, Zhenhua]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 4 ] [Zhao, Yuhang]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China
  • [ 5 ] [Wang, Jiangteng]College of Electrical Engineering and Automation, Fuzhou University, Fuzhou, China

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Year: 2025

Page: 2118-2123

Language: English

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ESI Highly Cited Papers on the List: 0 Unfold All

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30 Days PV: 0

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