Multicriteria synthesis of trigeneration systems considering economic and environmental aspects

The necessity of considering the environment as an additional design factor arises due to increasing environmental conscience worldwide and stricter requirements to reduce the environmental impact of energy systems. Designing such systems very often involves conflicting objectives as eco-friendly technologies are usually more expensive. This paper considers simultaneously economic and environmental criteria in the synthesis of a trigeneration system to be installed in a hospital. Synthesis includes optimal configuration (commercially available equipment) and optimal operation throughout the year. The multiobjective optimization accounts for minimization of total annual cost and CO2 emissions released in the atmosphere, as well as the Eco-indicator 99 (EI-99) in order to broaden environmental considerations in the impact assessment. A Pareto frontier, set of solutions representing optimal trade-offs between the economic and environmental objectives, is obtained from the solution of a Mixed Integer Linear Programming (MILP) model. Two bicriteria problems were solved using the MILP model: (1) annual cost (€/yr) versus CO2 emissions (kg CO2/yr) and (2) annual cost (€/yr) versus EI-99 Single Score (points/yr). The Pareto solutions consist of optimal configurations that adapt their operational strategy during a specific range in the Pareto frontier. Solutions are compared and it is observed that some configurations are more stable along the Pareto frontier, and that significant reductions in economic cost can be attained if the environmental impact is partially compromised. After the judgment of the solutions obtained and the trade-offs involved, one ultimate configuration is selected, which presents a flexible range of adaptability in the economic/CO2 and economic/EI-99 optimizations.

► Multiobjective optimization applied to synthesis problem in a trigeneration system.
► Optimization considered economic and environmental criteria.
► Pareto optimal design alternatives were analyzed and evaluated.
► Reductions in economic cost were attained if environmental impact was compromised.
► A specific configuration was more flexible to changes in external conditions.