The concept of Vehicle-to-Grid technology has turned the presence of plug-in electric vehicles (PEVs) into an opportunity for electricity grid. With a large-scale production of PEVs, the PEV fleet aggregator–as a new entity whose main objective in interaction with electricity markets is maximizing its profit–manages charging and discharging processes as well as offering and purchasing electricity for the vehicles. Thus, the performance of this aggregator, as a private entity, with the main objective of maximizing its profits in day-ahead and real-time electricity markets, considering (a) customers’ satisfaction constraints,(b) effects of driving patterns uncertainties, and (c) real-time energy market clearing prices uncertainties, is studied in this paper. To this end, the proposed model is formulated as a two-stage stochastic programming problem and implemented in GAMS software. The findings of the study reveal the effectiveness of the proposed algorithm on maximizing the aggregator’s profit-making as well as both customers’ and electricity distribution company’s financial satisfaction.