Service Restoration Strategy for Distribution Networks Considering Multi-Source Collaboration and Incomplete Fault Information

To address the severe damage and outage risks to distribution networks caused by extreme weather, this paper proposes a coordinated optimization strategy for distribution network repair sequencing and rapid restoration, which considers multi-source collaboration and incomplete fault information. In response to the challenge of incomplete fault information after a disaster, a two-layer robust optimization model is constructed. The upper-layer model aims to minimize the completion time of repairs for all faults under the most unfavorable fault scenario to obtain a robust repair time for potential faulty lines, providing a reliable basis for the restoration decisions of the lower-layer model. The lower-layer model’s objective is to maximize the weighted restored load quantity by comprehensively coordinating mobile diesel generators (MDGs), distributed generators (DGs), photovoltaics (PVs), wind turbines (WTs), and energy storage systems (ESSs) to achieve the optimal restoration strategy. The proposed service restoration strategy is validated through simulation on a modified IEEE 33-bus power system, and the results demonstrate that the strategy can efficiently and comprehensively utilize multi-source collaborative resources and improve the resilience of the distribution network.