This paper presents a time-dependent thermo-economic hierarchical approach to the investigation of smart poly-generation grids determining the optimal size of different prime movers in order to meet the energy (electrical, thermal, cooling) demands of a generic user. A specific case study was developed around the smart poly-generation grid at the University of Genoa, Savona Campus (Italy), operational since 2013. In an initial configuration, the grid included different co-generative prime movers, renewable generators and a thermal storage system to manage the thermal load demand over the year. A second layout used a tri-generative plant including an absorption chiller to also meet campus cooling demand.The simulation method considered the time-dependent energy load demands as problem constraints. This approach enabled both the optimal size and management for each component of the poly-generation grid to be determined for the entire year by giving due consideration to both energy and economic features.The results enabled the identification of the best configuration from the thermo-economic standpoint for the considered scenario. The proposed method is easily replicated for different applications and configurations of smart poly-generation grids.
