Search

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. [ABSTRACT FROM AUTHOR]

This study aims to make a comparative investigation on performance analysis of cascade refrigeration systems using R744/R717, R744/R134a, and R744/R1234yf refrigerant pairs. Artificial Cooperative Search methaheuristic algorithm is put into practice to obtain the optimal values of eight design parameters including Condenser and evaporator temperature, R744 condensing temperature, temperature difference in the cascade condenser, and amount of subcooling and superheating at the bottom and the top of the cascade cycle. Second law efficiency and total annual cost of the cascade refrigeration system are chosen as design objectives to be optimized individually and concurrently in order to obtain the optimal operating conditions of the system. Single optimization results show that R744/R1234yf system has the lowest operating cost while having the highest second law efficiency compared to other cycle configurations. A set of non-dominated solutions obtained through multi objective Artificial Cooperative Search algorithm is represented in the form of Pareto front and the best result is chosen from the well-reputed decision makers of TOPSIS and LINMAP for each cycle configuration. Multi objective optimization results reveal that design variables of the refrigeration system can create a trade off between problem objectives. A sensitivity analysis is performed to investigate the influences of varying values of design variables upon problem objectives while the system is operated under optimal conditions. [ABSTRACT FROM AUTHOR]

This study aims to comparatively investigate the performance of a cascaded vapor compression absorption refrigeration system (CVCARS) operated with different refrigerants such as R1234yf, R134a, R717 and R290 in vapor compression cycle. Two design objectives are considered for performance evaluations. Total annual cost is the first design objective which includes investment and operational cost along with the social cost associated with carbon emissions. Exergy efficiency is the second considered objective which is related to thermodynamic issues. These problem objectives are individually and concurrently optimized by means of Artifical Cooperative Search metaheuristic algorithm and best results are compared for each cycle configuration. Single objective optimization results reveal that CVCARS working with R717 in vapor compression cycle has the lowest total annual cost whereas the maximum second law efficiency is obtained by the refrigeration system operated with R290 in vapor compression cycle. Following that, multi objective optimization is applied to acquire the Pareto optimal solutions which are nondominated to each other and no solution between them prevails over the other. Reputed decision making method TOPSIS is applied to choose the final best answer among the Pareto curve. It is seen that solution found by TOPSIS is skewed towards the minimum total annual cost and second law efficiency for each cycle configuration. Sensitivity analysis is then put into practice to observe the influences of variations of decision variables on design objectives as well as performance coefficients of the different cycles in the refrigeration system. [ABSTRACT FROM AUTHOR]