The inherent storage of plug-in electric vehicles is likely to foster the integration of intermittent generation from renewable energy sources into existing power systems. In the present paper, we propose a three-stage scheme to the end of achieving dispatchability of a system composed of plug-in electric vehicles and intermittent generation. The main difficulties in dispatching such a system are the uncertainties inherent to intermittent generation and the time-varying aggregation of vehicles. We propose to address the former by means of probabilistic forecasts and we approach the latter with separate stagespecific models. Specifically, we first compute a dispatch schedule, using probabilistic forecasts together with an aggregated dynamic model of the system. The power output of the single devices are set subsequently, using deterministic forecasts and device-specific models. We draw upon a simulation study based on real data of generation and vehicle traffic to validate our findings.Index Terms-dispatch schedule, plug-in electric vehicle, probabilistic forecasting, renewable energy, stochastic programming, dynamic aggregation of energy storage All authors are with the