A predictive control strategy for energy management in buildings with radiant floors and thermal storage

Due to the growing energy demand in residential building, the need to reduce carbon footprint, and the smart grid paradigm, thermal energy control and overall power consumption reduction have become a hot research topic. The development of an energy management system able to modify consumer's energy consumption patterns while preserving comfort is a substantial solution. Hence, for load shaping in demand side management, particularly useful is the usage of a thermal energy storage (TES). It gives the possibility to shape the demand profile in an economic way based on dynamic electricity tariffs, by storing energy in thermal terms during off-peak hours. This paper focuses on the development of a novel control model for the integration of TES, HVAC system, building and local renewable energy sources to be used with optimization techniques. The presented control framework is based on Model Predictive Control (MPC) to better anticipate the effects of disturbances (e.g. weather conditions and user requirements on the load side, electricity price, etc.). A distributed structure has also been considered, to follow the modular structure of the system under control with the aim of optimizing the energy consumption costs and improving the indoor comfort level. Furthermore, the novel configuration of TES coupled with a heat pump and a radiant floor building giving rise to a more complex model with respect to the literature ones.