Multi-objective optimization of district energy systems with demand response

In district energy applications, implementation of management strategies is crucial to achieve reductions in primary energy consumption and carbon dioxide emissions. The development of optimization tools to upgrade the operation of smart energy systems should take into account all the relevant elements of these complex infrastructures. In this paper, a global optimization approach, applied to district heating, cooling and electricity networks interconnected to each other, is proposed. The suggested approach combines the optimization of the production side, useful to understand how it is convenient to produce heat, cold and electricity, with demand-side management for district heating customers. This is reached by using a bi-level optimization structure, exploiting the genetic algorithm and linear programming. A physical model of the district heating network is included in the procedure to accurately reproduce the effects of demand-side management. The tool can be applied to different objective functions. In this paper, a multi-objective optimization is carried out with two different objective functions: the operation cost and the carbon dioxide emissions. Results show that, by choosing an intermediate trade-off among the two goals, it would be possible to have a 12% reduction in the emissions at the expense of a 25% increase in the operating cost.