Multi-objective optimization of the basic and single-stage Organic Rankine Cycles utilizing a low-grade heat source

This study deals with the multi-objective optimization of basic and single-stage Organic Rankine Cycles (ORC) utilizing a low-grade heat source. Twelve different isentropic and dry pure refrigerants are considered as the primary working fluid for two different ORC configurations. Specific Investment Cost (SIC) and second law efficiency of the thermodynamic cycle are considered for optimization objectives to be optimized seperately and concurrently. Sixteen and twenty two different decision variables are respectively taken into account for modeling of the basic and the single-stage ORC optimization problems. The optimization problem is solved by applying a swarm based metaheuristic optimizer called Artificial Cooperative Search (ACS) algorithm. A pareto curve comprised of non dominated optimal solutions is constructed for each refrigerant-cycle pair and the best answer among the set of non dominated solutions are chosen by means of TOPSIS decision making method. Thermodynamic performance of each refrigerant are evaluated with respect to numerical outcomes of the objective functions. Comparative analysis based on the efficiencies of problem objectives reveals that R236ea, R245fa and R600 are selected as the best performers of the basic ORC and R245ca, R245fa and R600 are selected as the best performers of the single-stage ORC. Finally, a sensitivity analysis is executed to observe the effect of the decision variables on the objectives. It is understood that the evaporator shell diameter, number of tube passes in the evaporator, evaporator pressure and mass flow rate of the refrigerant are the decision variables with the most influence on the design objectives.