A multi-objective methodology for locating, sizing and operation of energy storage devices in distribution systems considering a typical load curve on a horizon of 24 hours is presented. The objective functions of the problem are minimization of power losses and the installation cost of the energy storage devices. The proposed methodology considers two optimization stages through a master-slave optimization algorithm. In master stage, the planning and sizing of the battery banks is done by using a multi-objective optimization algorithm called non dominated sorting genetic algorithm II, which defines the nodes where there will be batteries and their storage capacity. In slave stage, a tabu search optimization algorithm is used, which defines what is the best operation scheme for each battery configuration generated in the previous stage. The IEEE 33-nodes test feeder is used to validate the proposed methodology. The results show the robustness and efficiency of the approach proposed in this paper.