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Emergency scheduling of virtual energy storage based on continuous-time model for resilience enhancement under extreme events

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  • Chen, Jiajia
  • Liu, Fengwei
  • Wang, Yanxin
  • Li, Yuanzheng

Abstract

Resilience against extreme events is an essential feature of the smart distribution system. Virtual energy storage (VES), aggregating mobile energy storage and demand response, has the potential to contribute to proving such resilience. Yet, there is still a lack of effective methods to exploit the available power from VES that can be optimally dispatched in continuous-time to restore critical loads after blackouts. We here propose a continuous-time-based emergency scheduling for VES to enhance the resilience of the distribution network. The path-planning method with the shortest driving time which relates to both transportation network and electricity network is presented to simulate the path selection of mobile energy storage. Then, an interval normalizing-based Bernstein polynomial is derived to capture the continuous-time operating process of VES, such as the real-time state of energy and the charging/discharging power. This extends the application of the Bernstein polynomial in the emergency scheduling of power systems with arbitrary closed intervals. Simulation results conducted on different test systems verify the effectiveness of the proposed resilience enhancement framework in reducing load loss and operation cost against extreme events. Specifically, our approach achieves average cost savings of 1.27% and 3.04% compared to the DT method in emergency scenarios 1 and 2 for the IEEE-15 system, while also significantly reducing resilience-related load loss costs by 2.12% and 5.93%, respectively.

Suggested Citation

  • Chen, Jiajia & Liu, Fengwei & Wang, Yanxin & Li, Yuanzheng, 2026. "Emergency scheduling of virtual energy storage based on continuous-time model for resilience enhancement under extreme events," Energy, Elsevier, vol. 342(C).
    • Handle: RePEc:eee:energy:v:342:y:2026:i:c:s0360544225052764
    DOI: 10.1016/j.energy.2025.139634
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    References listed on IDEAS

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