Multicriteria Optimization of a Distrubuted Energy Supply System for a 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 distri1ct heating network that connects the users to each other, small scale CHP systems (e.g. micro gas turbines or internal combustion engine), conventional integration boilers, large centralized solar plant and a seasonal thermal storage. The optimization has to determine the optimal structure of the system, the size and the load of each component inside the optimal solution, as well as the optimal operation strategy. The multi-objective optimization is based on a Mixed Integer Linear Programming model (MILP) and it takes into account as objective function a linear combination of the total annual cost (for owning, maintaining and operating the whole system) and the CO2 emissions amount, 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 as an example to a specific case study made of nine industrial facilities and it has been optimized for different superstructure configurations and for two different values of the electricity greenhouse emissions factor. The obtained results shows that the solar plant, coupled with the seasonal thermal storage, allows reaching both environmental and economic goals. If the centralized solar plant is not considered in the superstructure, CO2 emissions related to electricity affect the optimal structure of the energy supply system