This paper describes a two-layer control and coordination framework for distributed energy resources. The lower layer is a real-time model predictive control (MPC) executed at 10 s resolution to achieve fine tuning of a given energy setpoint. The upper layer is a slower MPC coordination mechanism based on distributed optimization, and solved with the alternating direction method of multipliers (ADMM) at 5 minutes resolution. It is needed to coordinate the power flow among the controllable resources such that enough power is available in real-time to achieve a pre-established energy trajectory in the long term. Although the formulation is generic, it is developed for the case of a battery system and a curtailable PV facility to dispatch stochastic prosumption according to a trajectory at 5 minutes resolution established the day before the operation. The proposed method is experimentally validated in a real-life setup to dispatch the operation of a building with rooftop PV generation (i.e., 101 kW average load, 350 kW peak demand, 82 kW peak PV generation) by controlling a 560 kWh/720 kVA battery and a 13 k W peak curtailable PV facility.