Emergency Resource Dispatch Scheme for Ice Disasters Based on Pre-Disaster Prediction and Dynamic Scheduling
Source abstract
Abstract
To address the challenge of dispatching emergency resources for community residents under extreme ice disaster, this paper proposes an emergency resource dispatch strategy based on pre-disaster prediction and dynamic scheduling. First, the fast Newman algorithm is employed to cluster communities, optimizing the preprocessing of resource scheduling and reducing scheduling costs. Subsequently, mobile energy storage vehicles and mobile water storage vehicles are introduced based on the ice disaster trajectory prediction to enhance the efficiency and accuracy of post-disaster resource supply. A grouped scheduling strategy is adopted to reduce cross-regional resource flow, and the dispatch routes of mobile energy storage and water vehicles are dynamically adjusted based on real-time traffic network conditions. Simulations on the IEEE-33 node system validate the feasibility and advantages of the proposed strategies. The results demonstrate that the grouped dispatch and scheduling strategies increase user satisfaction by 24.73%, average state of charge (SOC) by 30.23%, and water storage by 31.88% compared to global scheduling. These improvements significantly reduce the cost of community energy self-sustainability, enhance the satisfaction of community residents, and ensure system stability across various disaster scenarios.
Source: crossref · Quality: baseline
Research context
OpenAlex topics: Infrastructure Resilience and Vulnerability Analysis · Evacuation and Crowd Dynamics · Mobile Ad Hoc Networks
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
School of Materials and Energy, Guangdong University of Technology, Guangzhou 510006, China
Guangdong Provincial Key Laboratory of Intelligent Systems and Optimization Integration, School of Automation, Guangdong University of Technology, Guangzhou 510006, China
Funding
Guangdong Basic and Applied Basic Research Foundation
References (33)
Show source-provided references
1. Urban impacts of ice storms: Toronto December 201310.1007/s11069-014-1211-7 ↗
2. Zhang, P.-F., Tan, Y.-X., Ai, J.-M., Chen, R., Gao, B., Zhang, H.-X., and Jia, C.-J. (2009, January 27–31). Lessons learned from the ice storm in 2008 in Jiangxi China. Proceedings of the 2009 Asia-Pacific Power and Energy Engineering Conference (APPEEC), Wuhan, China.10.1109/APPEEC.2009.4918461 ↗
3. Emergency systems and power outage restoration due to infrastructure damage from major floods and disasters10.1002/inst.12297 ↗
4. Melaku, N.D., Fares, A., and Awal, R. (2023). Exploring the impact of winter storm Uri on power outage, air quality, and water systems in Texas, USA. Sustainability, 15.10.3390/su15054173 ↗
5. Li, L., Tan, E., Gao, P., and Jin, Y. (2024). Enhancing concurrent emergency response: Joint scheduling of emergency vehicles on freeways with tailored heuristic. Appl. Sci., 14.10.3390/app14177433 ↗
6. A review of incident prediction, resource allocation, and dispatch models for emergency management10.1016/j.aap.2021.106501 ↗
7. Changes in ice storm impacts over time: 1886–200010.1175/2009WCAS1013.1 ↗
8. Multiple emergency resource allocation for concurrent incidents in natural disasters10.1016/j.ijdrr.2016.05.003 ↗
9. Rolling optimization of mobile energy storage fleets for resilient service restoration10.1109/TSG.2019.2930012 ↗
10. Transportable energy storage for more resilient distribution systems with multiple microgrids10.1109/TSG.2018.2824820 ↗
11. Lin, Y., He, C., Zheng, L., and Ning, Y. (2024, January 17–20). Data driven urban power grid disaster prediction under extreme weather conditions. Proceedings of the 2024 7th International Conference on Electronics Technology (ICET), Chengdu, China.10.1109/ICET61945.2024.10672886 ↗
12. Multiperiod distribution system restoration with routing repair crews, mobile electric vehicles, and soft-open-point networked microgrids10.1109/TSG.2020.3001952 ↗
13. Zhao, R., Lu, J., Chen, Y., Gao, Y., Li, M., Wei, C., and Li, J. (2025). Active support strategies for power supply in extreme scenarios with synergies between idle and emergency resources in the city. Energies, 18.10.3390/en18081940 ↗
14. Modeling multiple humanitarian objectives in emergency response to large-scale disasters10.1016/j.tre.2014.11.007 ↗
15. Models for relief routing: Equity, efficiency and efficacy10.1016/j.tre.2011.05.004 ↗
16. Resilient disaster recovery logistics of distribution systems: Co-optimize service restoration with repair crew and mobile power source dispatch10.1109/TSG.2019.2899353 ↗
17. Mobile energy storage scheduling and operation in active distribution systems10.1109/TIE.2017.2682779 ↗
18. Abdulrazzaq Oraibi, W., Mohammadi-Ivatloo, B., Hosseini, S.H., and Abapour, M. (2023). Multi-microgrid framework for resilience enhancement considering mobile energy storage systems and parking lots. Appl. Sci., 13.10.3390/app13031285 ↗
19. Chen, J., Chen, C., and Duan, S. (2019). Cooperative optimization of electric vehicles and renewable energy resources in a regional multi-microgrid system. Appl. Sci., 9.10.3390/app9112267 ↗
20. Fast algorithm for detecting community structure in networks10.1103/PhysRevE.69.066133 ↗
21. Self-sustaining of post-disaster pelagic island energy systems with mobile multi-energy storages10.1109/TSG.2022.3225557 ↗
22. Fault recovery of active distribution network considering translatable load and soft open point
23. The great 2008 Chinese ice storm: Its socioeconomic–ecological impact and sustainability lessons learned10.1175/2010BAMS2857.1 ↗
24. A simple model for freezing rain ice loads10.1016/S0169-8095(97)00053-7 ↗
25. Resilience assessment of electric-thermal energy networks considering cascading failure under ice disasters10.1016/j.apenergy.2024.123533 ↗
26. Finding and evaluating community structure in networks10.1103/PhysRevE.69.026113 ↗
27. Community structure in social and biological networks10.1073/pnas.122653799 ↗
28. Integrated network partitioning and DER allocation for planning of virtual microgrids10.1016/j.epsr.2022.109024 ↗
29. Borodinecs, A., Zajecs, D., Lebedeva, K., and Bogdanovics, R. (2022). Mobile off-grid energy generation unit for temporary energy supply. Appl. Sci., 12.10.3390/app12020673 ↗
30. Gurobi Optimization, LLC (2025, July 10). Gurobi Optimizer Reference Manual, Version 11.0. Available online: https://www.gurobi.com/documentation/.
31. Xie, S., Yang, Z., Wang, M., Xu, G., and Bai, S. (2025). Evaluating the resilience of mountainous sparse road networks in high-risk geological disaster areas: A case study in Tibet, China. Appl. Sci., 15.10.3390/app15052688 ↗
32. Routing and scheduling of mobile power sources for distribution system resilience enhancement10.1109/TSG.2018.2889347 ↗
33. Analysis of water supply and demand based on logistic model10.1088/1755-1315/300/2/022013 ↗