关键词: 修复路径规划, 拓扑重构, 配电网弹性, 新能源, 分布鲁棒优化

Abstract:

Extreme disaster events frequently lead to distribution network faults，compromising power supply reliability. To enhance distribution network resilience，a post-disaster restoration model coordinating repair crew routing and network reconfiguration was established. To formulate an orderly fault repair plan，spatial and temporal constraints for repair crew routing were established，together with fault status constraints coupled with network reconfiguration. System load shedding was minimized through the coordinated optimization of repair paths and network reconfiguration. By leveraging probability density-based fuzzy sets to characterize the distribution uncertainty of renewable energy，distributionally robust optimization was employed to balance the robustness and economy of dispatch decisions. To efficiently solve the proposed model，probability density uncertainty was addressed based on duality theory，and the min operator within constraints was removed，whereby the two-stage post-disaster restoration model was converted into a non-iterative single-stage problem. Case studies demonstrated that the proposed coordinated model effectively reduced load losses. Furthermore，the proposed distributionally robust optimization method ensured the robustness of dispatch decisions and significantly enhanced computational efficiency while strictly maintaining optimization quality.

Key words: repair crew routing, network reconfiguration, distribution network resilience, renewable energy, distributionally robust optimization