In this paper, a new model is developed to optimise the performance of a plug-in Electric Vehicle (EV) aggregator in electricity markets, considering both short- and long-term horizons. EV aggregator as a new player of the power market can aggregate the EVs and manage the charge/discharge of their batteries. The aggregator maximises the profit and optimises EV owners' revenue by applying changes in tariffs to compete with other market players for retaining current customers and acquiring new owners. On this basis, a new approach to calculate the satisfaction/motivation of EV owners and their market participation is proposed in this paper. Moreover, the behaviour of owners to select their supplying company is considered. The aggregator optimises the self-scheduling programme and submits the best bidding/offering strategies to the day-ahead and real-time markets. To achieve this purpose, the day-ahead and real-time energy and reserve markets are modelled as oligopoly markets, in contrast with previous works that utilised perfectly competitive ones. Furthermore, several uncertainties and constraints are taken into account using a two-stage stochastic programing approach, which have not been addressed in previous works. The numerical studies show the effectiveness of the proposed model. (C) 2015 Elsevier Ltd. All rights reserved.