Optimal Plug-in Electric Vehicles Management by Aggregators

The energy consumption and supply requirements of a large number of plug-in electric vehicles (PEV) should be optimally attended in an economical and controlled form. In this manner, adequate economic remunerations to PEV owners that participate in energy selling/purchase transactions and normal operative conditions in a smart distribution grid (SDG) can be provided. The concept of "aggregators" represents an alternative to manage the new active role that the PEV will perform in the SDG. In this sense, this paper proposes a methodology to dispatch the PEV requirements in an optimal and economical manner. Aggregators located in a SDG are used to optimize the quantities of energy that each PEV can consume and supply. Mean-Variance Mapping Optimization (MVMO) metaheuristic algorithm is used in the optimization process and compared with an exhaustive analysis of the problem. The results show the robustness and the quickness of MVMO to solve this dispatch.