With the development of Smart Grids and advanced communication technologies, resiliency and service restoration has become an essential part of the operation and planning of electrical distribution systems (EDSs). In the presence of a permanent fault, an optimized service restoration (a.k.a. a self-heling scheme) minimizes the unsupplied demand while maintaining the faulted section of the network isolated for the maintenance crews to fix the failure. The decision variables of the optimization process are the status of the remote-controlled switches (either open or closed), the status of the load zones (either energized or de-energized) and the load shedding at each controllable load. The service restoration problem is a combinatorial optimization process whose computational complexity grows exponentially with the number of binary decision variables. To overcome this issue, a distributed optimal service restoration strategy will be developed using an adapted version of the alternating direction method of multipliers (ADMM) algorithm. Through ADMM, the optimization process is distributed among the zones of the EDS, without requiring a central controller. ADMM enhances the computational efficiency of the optimization process while converging to a high-quality solution. Operational constraints, such as current and voltage magnitude limits, distributed generation (DG) capacities, and radial topology must be guaranteed by the proposed method. Moreover, results must provide feasible and optimized solutions without the need of a central controller.
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