Multi-objective optimization of a polygeneration grid including thermal energy storage system

The aim of this work is the optimization of a polygeneration grid including renewable sources and fossil-fuel based prime movers. The system produces both electrical and thermal power and is equipped with a thermal energy storage device in the form of a hot water tank. The grid layout has been chosen to consider the energy needs of the University campus in Savona with a configuration to improve the flexibility for a possible extensive optimization. Starting from the energy demands of different typical days, a multi-objective approach has been used to minimize both generation costs and CO2 emissions. The activity has been carried out comparing the use of different technologies (e.g., boiler against heat pump) in order to assess performance in different cases. Special attention has been devoted to an innovative approach for thermal energy storage optimization. Since the sizing of energy storage devices remains an open aspect due to balancing of energy security constraints and cost/emission association to the stored energy, the innovative method proposed here can generate solutions with important benefits on the grid performance and optimization. Moreover, due to possible contrasts of minimization objectives, this work shows the benefits related to a multi-objective approach applied to a real smart grid. An important innovation is the application of a heat pump in grid optimization analyses. In details, the algorithm can demonstrate the improvements in terms of emissions and cost savings considering the innovative integration of existing technologies with the heat pump (− 13.2 % cost decrease for the cost minimization target, − 16.6 % CO2 emission decrease for the CO2 minimization objective, and, finally, − 35.2 % for the cost*CO2 innovative objective proposed here).