Coordinated Repair and Restoration of a Multienergy Distribution System Under Diverse Uncertainties via Joint Network Reconfiguration

This article proposes a new resilient service restoration approach for a multienergy distribution system (MDS) following unexpected large contingencies. The repair scheduling and MDS restoration are optimally coordinated through a two-stage coordinated framework. To fully exploit the network flexibility during the recovery process, a joint network reconfiguration model is proposed to regulate the switching operations between the power distribution network and the district heating network (DHN). To effectively model the reconfigurable property, the DHN is formulated as a quasi-linear energy flow model for mathematical tractability. Besides, diverse uncertainties from the power, heat, and traffic networks are handled via a two-stage stochastic program. The proposed model is linearized and formulated as a mixed-integer linear programming (MILP) problem considering detailed network operational and temporal-spatial constraints. Furthermore, to accelerate the solution process, a penalty-based Gauss–Seidel decomposition algorithm is developed to decompose and solve the proposed MILP problem efficiently. Finally, comprehensive case studies are done to validate the effectiveness and efficiency of the proposed model and solution method.