| Popis: |
Selecting high-efficient and environmentally friendly working fluids has always been the research focus of Organic Rankine cycle (ORC). Thus, in this work, based on the group contribution method (GCM) and cubic equation of state (CEOS), relationships between molecular structures and cycle performances are established to design working fluids for subcritical and transcritical cycles. In order to determine the calculation deviation, Peng-Robinson (PR) and volume translated Peng-Robinson (VTPR) models are firstly employed to predict the entropy, enthalpy and density. Meanwhile, the two equations are combined with GCMs to estimate these properties. Thereafter, cycle performances are predicted for four different ORCs, namely subcritical basic/regenerative cycles, transcritical basic/regenerative cycles. The obtained results show that PR and VTPR have satisfied and equivalent accuracy for the calculation of thermodynamic properties and cycle performances. Meanwhile, although the calculation deviations of GCM-CEOS are higher than those of CEOS, the deviations caused by GCM-CEOS are still within acceptable limits. For the subcritical cycle, average absolute relative deviations (AARDs) of net work and cycle efficiency are respectively less than 2.251% and 2.528%. As for the transcritical cycle, the corresponding AARDs are smaller than 9.168% and 8.364%. Based on the GCM-CEOS, working fluid can be designed for the four ORCs. Thus, a design case of working fluid is provided under a given heat source and PR is employed for simplicity. In the design process, when a working fluid is generated by combining groups, the corresponding cycle parameters are optimized with the target of maximizing output work. Thereafter, environmental and safety properties are furtherly considered to determine the optimum fluid. It is discovered that the optimum fluid for subcritical basic and regenerative cycles is R245cb, while R272fa and 1,1,2-trifluoropropane are respectively selected for transcritical basic and regenerative cycles. |
