The aim of this paper is to propose a control approach for the management of a production–consumption energy system based on model predictive control (MPC). The solar absorption cooling system is seen as part of this production–consumption energy system where the solar hot water storage (SHWS) system is the producer subsystem and the chiller-building system is one of the consumer subsystems. In order to provide modularity to the control structure, the coordination between the subsystems is achieved by designing interactive local predictive controllers. The consumer controllers compute a set of energy demand profiles sent to the producer controller which selects the profile that better minimizes the global optimization cost function. In a first part, the proposed control approach is tested on a simplified linear model composed of one producer and several consumers. In a second part, a more complex case is studied. A simplified model of an absorption cooling system is evaluated using the simulation tool TRNSYS. The producer model is no longer linear, instead it is described by a nonlinear hybrid model which increases the complexity of the optimization problem. The simulations results show that the performance of the controller fulfills the control objectives.