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This paper proposes a new methodology for distribution network reconfiguration (DNR), in a Smart Grid (SG) scenario, regarding power losses, grid reliability and the utilization factor of substations; as well as an approach to model the effects of electric vehicle charging stations, distributed energy generators and energy storage systems in the electric grid. The proposed methodology first deals with the problem setting, that is, it determines the state of the grid (in terms of electrical parameters and variables, power loss, reliability indicators and utilization factor for each substation) and its topology. Then, it's defined the universe of possible solutions, to which is applied a simple formulation of Genetic Algorithm (GA) that solves the optimization problem. To demonstrate the applicability of this methodology in a real network, the methodology was implemented in the specialized commercial power system simulator SINAP Grid and applied in a case study. Its results showed that it is possible to accommodate so many objectives in one solution, however, the state of the grid and its initial topology influence greatly in the outcome of the solution.