HAN Zhonghe, MEI Zhongkai, LI Peng. Working fluid selection and multi-objective optimization of organic Rankine cycle with variable turbine efficiency[J]. CIESC Journal, 2018, (6): 2603-2611.
DOI:
HAN Zhonghe, MEI Zhongkai, LI Peng. Working fluid selection and multi-objective optimization of organic Rankine cycle with variable turbine efficiency[J]. CIESC Journal, 2018, (6): 2603-2611.DOI: 10.11949/j.issn.0438-1157.20171349.
Working fluid selection and multi-objective optimization of organic Rankine cycle with variable turbine efficiency
To harness heat of 523.15 K high temperature flue gas
pentane
hexane
heptane
cyclohexane
MM (hexamethyldisiloxane)
benzene and toluene were selected as working fluid candidates. With selection of one-dimensional radial-inflow turbine efficiency prediction model to replace constant turbine efficiency model
and net power output and exergy efficiency as target functions
organic Rankine cycle (ORC) system was simulated for multiple output variables by using non-dominated sorting genetic algorithm (NSGA-Ⅱ). Optimal solution of each working fluid was determined from Pareto frontiers by ideal point estimation. The results show a strong correlation between turbine efficiency and volumetric flow ratio (VFR) of working fluids in a way that turbine efficiency curve trends oppositely to VFR curve. At fixed heat source conditions
benzene is the optimal working fluid whereas toluene and cyclohexane are sub-optimal. Exergy efficiency accelerates in a downward trend at evaporation temperature above 400 K
but net power output slows down in a rise trend at evaporation temperature above 410 K. Optimization with constant turbine efficiency model somewhat affects screening results of optimal parameters and best working fluid
which are deviated from actual outcomes. However
optimization with variable turbine efficiency model can reduce such error and results are much closer to engineering practice.