With the rapid deployment of the advanced metering infrastructure (AMI) and distribution automation (DA), selfhealing has become a key factor to enhance the resilience of distribution networks. Following a permanent fault occurrence, the distribution network operator (DNO) implements the selfhealing scheme to locate and isolate the fault and to restore power supply to out-of-service portions. As an essential component of self-healing, service restoration has attracted considerable attention. This paper mainly reviews the service restoration approaches of distribution networks, which requires communication systems. The service restoration approaches can be classified as centralized, distributed, and hierarchical approaches according to the communication architecture. In these approaches, different techniques are used to obtain service restoration solutions, including heuristic rules, expert systems, metaheuristic algorithms, graph theory, mathematical programming, and multi-agent systems. Moreover, future research areas of service restoration for distribution networks are discussed.

With the advent of Smart Grids and advanced communication technologies, the self-healing scheme has become a desirable function of the operation and planning of electrical distribution systems (EDSs). In the presence of a permanent fault, an optimized self-healing scheme minimizes the unsupplied demand while maintaining the faulted section of the network isolated. The service restoration of the self-healing scheme is a combinatorial optimization problem whose computational complexity grows exponentially with the number of binary variables. To resolve this issue, a distributed optimal service restoration strategy is developed based on the alternating direction method of multipliers (ADMM). The service restoration problem is formulated as a mixed-integer second-order cone programming (MISOCP) problem. The decision variables of the problem are the status of the remote-controlled switches, load zones and load shedding at each controllable demand. Operational constraints, such as current and voltage magnitude constraints, distributed generation (DG) capacity constraints and radial topology constraints, are respected in the optimization problem. Through the ADMM, the optimization problem is distributed among the zones of the EDS, without requiring a central controller. Two test systems, an unbalanced 44-node system and the IEEE 123node system, were used to conduct case studies. Results show that the proposed method can provide optimal service restoration solutions in reasonable time without a central controller.Index Terms-Alternating direction method of multipliers, distributed self-healing scheme, electrical distribution systems, service restoration. NOMENCLATUREThe notation used throughout this paper is listed below. Sets and indices: Ω b Set of nodes Ω z , Ω * z Set of zones and set of zones without main sources Φ Set of phases a, b, c This work was supported in part by the DTU-NTU double PhD project of the Smart City joint program and in part the Brazilian institution FAPESP.

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