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Large-scale power outages caused by accidents or natural disasters can be mitigated by coordinating hydrogen-powered generators, mobile emergency units, and energy storage systems to rapidly restore critical loads. This paper proposed a multi-source coordinated load restoration optimization strategy that dynamically adjusted load node weights based on time-varying characteristics of different load types. The strategy aimed to maximize post-fault load recovery while considering constraints such as finite energy availability, operational boundaries, and topological limitations. Leveraging the operational flexibility and dispatch potential of diverse flexible resources, it achieved synergistic coordination to enhance distribution network resilience. A Particle Swarm Optimization (PSO) algorithm was implemented on the IEEE 33-node distribution system testbed to determine optimal emergency power supply locations. The simulation resulted validate the strategy’s efficacy, demonstrating its ability to identify optimal access points and improve recovery efficiency. This approach provided an innovative solution for resilient distribution network restoration under high renewable penetration scenarios, offering practical insights for smart grid development and extreme disaster response.

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Research on Optimized Recovery Strategy of Emergency Power Supply with Multi-source Collaboration

  • 会议论文

  • 发表日期：

    2026年

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  • Meizhi Lei,
  • Tianyou Li,
  • Jun Su

摘要

Large-scale power outages caused by accidents or natural disasters can be mitigated by coordinating hydrogen-powered generators, mobile emergency units, and energy storage systems to rapidly restore critical loads. This paper proposed a multi-source coordinated load restoration optimization strategy that dynamically adjusted load node weights based on time-varying characteristics of different load types. The strategy aimed to maximize post-fault load recovery while considering constraints such as finite energy availability, operational boundaries, and topological limitations. Leveraging the operational flexibility and dispatch potential of diverse flexible resources, it achieved synergistic coordination to enhance distribution network resilience. A Particle Swarm Optimization (PSO) algorithm was implemented on the IEEE 33-node distribution system testbed to determine optimal emergency power supply locations. The simulation resulted validate the strategy’s efficacy, demonstrating its ability to identify optimal access points and improve recovery efficiency. This approach provided an innovative solution for resilient distribution network restoration under high renewable penetration scenarios, offering practical insights for smart grid development and extreme disaster response.