A Coordinated Restoration Scheduling Strategy for Distribution Network Sources Under Typhoon Weather Considering Correlation Effects
To mitigate large-scale blackout risks in urban distribution systems under typhoon-induced extreme weather and to reduce post-disaster restoration costs, this study proposes a resilience-oriented spatiotemporal co-optimization framework integrating transportation networks, power grids, and distributed energy resources. First, a city-scale typhoon spatiotemporal model is established, integrating static wind field, dynamic evolution, and trajectory-based mobility with urban-geometry-driven wind speed correction to characterize the spatiotemporal progression of extreme wind hazards. Second, the time-varying failure rates of distribution network components are quantified by explicitly accounting for network topology correlations, while the spatiotemporal dispatchability and output characteristics of distributed resources under disaster conditions are systematically modeled. Third, a pre-disaster proactive deployment model is formulated to minimize load curtailment costs and resource allocation expenditures. The model integrates active network reconfiguration with coordinated placement of distributed generation (DG) and mobile energy storage systems (MESSs), enabling resilience-enhancing pre-positioning strategies. Subsequently, a post-disaster restoration scheduling model is developed with the objective of minimizing unserved load. By embedding traffic flow constraints and optimal path computation under disrupted transportation conditions, the proposed framework realizes spatiotemporal coordination among MESSs, DG, and electric vehicles (EVs), thereby accelerating system-level recovery. Finally, the effectiveness of the proposed strategy is validated on a 51-node urban distribution system located in eastern coastal China, demonstrating significant improvements in restoration performance and resilience enhancement.
Institutions
- State Grid Corporation of China (China) (CN)
- Fujian Electric Power Survey & Design Institute (CN)
- Economic Research Institute (BG)
- Zhejiang University (CN)
Publication Details
- Journal
- Applied Sciences
- Published
- 2026-05-19
- DOI
- https://doi.org/10.3390/app16105054
- Primary Topic
- Optimal Power Flow Distribution
- Type
- article
- Field-Weighted Citation Impact
- 0.00
Funders
- State Grid Fujian Electric Power Company