Research on Mobile Energy Storage Configuration and Path Planning Strategy Under Dual Source-Load Uncertainty in Typhoon Disasters

Bingchao Zhang, Chunyang Gong (), Songli Fan, Jian Wang, Tianyuan Yu and Zhixin Wang ()
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Bingchao Zhang: College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Chunyang Gong: College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Songli Fan: School of Electronic and Information Engineering, Suzhou University of Science and Technology, Suzhou 215009, China
Jian Wang: College of Smart Energy, Shanghai Jiao Tong University, Shanghai 200240, China
Tianyuan Yu: College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China
Zhixin Wang: College of Automation Engineering, Shanghai University of Electric Power, Shanghai 200090, China

Energies, 2025, vol. 18, issue 19, 1-21

Abstract: In recent years, frequent typhoon-induced disasters have significantly increased the risk of power grid outages, posing severe challenges to the secure and stable operation of distribution grids with high penetration of distributed photovoltaic (PV) systems. Furthermore, during post-disaster recovery, the dual uncertainties of distributed PV output and the charging/discharging behavior of flexible resources such as electric vehicles (EVs) complicate the configuration and scheduling of mobile energy storage systems (MESS). To address these challenges, this paper proposes a two-stage robust optimization framework for dynamic recovery of distribution grids: Firstly, a multi-stage decision framework is developed, incorporating MESS site selection, network reconfiguration, and resource scheduling. Secondly, a spatiotemporal coupling model is designed to integrate the dynamic dispatch behavior of MESS with the temporal and spatial evolution of disaster scenarios, enabling dynamic path planning. Finally, a nested column-and-constraint generation (NC&CG) algorithm is employed to address the uncertainties in PV output intervals and EV demand fluctuations. Simulations on the IEEE 33-node system demonstrate that the proposed method improves grid resilience and economic efficiency while reducing operational risks.

Keywords: mobile energy storage system; dual uncertainty; grid resilience; two-stage robust optimization; path planning (search for similar items in EconPapers)
JEL-codes: Q Q0 Q4 Q40 Q41 Q42 Q43 Q47 Q48 Q49 (search for similar items in EconPapers)
Date: 2025
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