A predictive optimal control system for micro-cogeneration in domestic applications has been developed. This system aims at integrating stochastic inhabitant behavior and meteorological conditions as well as modeling imprecisions, while deﬁning operation strategies that maximize the effciency of the system taking into account the performances, the storage capacities and the electricity market opportunities. Numerical data of an average single family house has been taken as case study. The predictive optimal controller uses mixed integer and linear programming where energy conversion and energy services models are deﬁned as a set of linear constraints. Integer variables model start-up and shut down operations as well as the load dependent efﬁciency of the cogeneration unit. This control system has been validated using more complex building and technology models to asses model inaccuracies and typical demand proﬁles for stochastic factors. The system is evaluated in the perspective of its usage in Virtual Power Plants applications.