화학공학소재연구정보센터
Energy Conversion and Management, Vol.136, 11-26, 2017
Thermo-economic analysis of zeotropic mixtures based on siloxanes for engine waste heat recovery using a dual-loop organic Rankine cycle (DORC)
Siloxanes are usually used in the high temperature organic Rankine cycle (ORC) for engine waste heat recovery, but their flammability limits the practical application. Besides, blending siloxanes with retardants often brings a great temperature glide, causing the large condensation heat and the reduction in net output power. In view of this, the zeotropic mixtures based on siloxanes used in a dual-loop organic Rankine cycle (DORC) system are proposed in this paper. Three kinds of binary zeotropic mixtures consisting of R123 and various siloxanes (octamethylcyclotetrasiloxane 'D4', octamethyltrisiloxane 'MDM', decamethyltetrasiloxane 'MD2M'), represented by D4/R123, MDM/R123 and MD2M/R123, are selected as the working fluid of the high temperature (HT) cycle. Meanwhile, R123 is always used in the low temperature (LT) cycle. The net output power and utilization of heat source are considered as the evaluation indexes to select the optimal mixture ratios for further analysis. Based on the thermodynamic and economic model, net output power, thermal efficiency, exergy efficiency, exergy destruction and electricity production cost (EPC) of the DORC system using the selected mixtures have been investigated under different operating parameters. According to the results, the DORC based on D4/12123 (0.3/0.7) shows the best thermodynamic performance with the largest net power of 21.66 kW and the highest thermal efficiency of 22.84%. It also has the largest exergy efficiency of 48.6% and the smallest total exergy destruction of 19.64 kW. The DORC using MD2M/R123 (0.35/0.65) represents the most economic system with the smallest EPC of 0.603 $/kW h. Besides, the irreversibility in the internal heat exchanger, turbine and evaporator of HT cycle contributes most to the total exergy destruction which can serve as the parameter to be optimized in the further study. (C) 2016 Elsevier Ltd. All rights reserved.