Multicriteria optimization of a distributed energy supply system for an industrial area

In the paper a multi-objective optimization model for distributed energy supply systems optimization is presented. The superstructure of the system comprehends a district heating network that connects the users to each other, small-scale CHP systems, large centralized solar plant and a thermal storage. The optimization has to determine the optimal structure of the system, the size of each component inside the optimal solution and the optimal operation strategy. The multi-objective optimization is based on a MILP (Mixed Integer Linear Programming) model and takes into account as objective function a linear combination of the annual cost for owning, maintaining and operating the whole system and the CO2 emissions associated to the system operation. The model allows to obtain different optimal solutions by varying the relative weight of the economic and the environmental objectives. In this way the Pareto Front is identified and the possible improvements in both economic and environmental terms can be highlighted. The model has been applied to a specific case study and it has been optimized for different superstructure configurations and for two different values of the electricity carbon intensity. The obtained results show that the solar plant, coupled with the optimal thermal storage, allows reaching both environmental and economic goals.