化工学报2018，Vol.69Issue(6)：2603-2611,9.DOI:10.11949/j.issn.0438-1157.20171349
变透平效率有机朗肯循环工质筛选及多目标优化
Working fluid selection and multi-objective optimization of organic Rankine cycle with variable turbine efficiency
摘要
Abstract
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.关键词
有机朗肯循环/多目标优化/一维向心透平效率预测模型/热力学/经济/透平等熵膨胀比Key words
organic Rankine cycle/multi-objective optimization/one-dimensional radial-inflow turbine efficiency prediction model/thermodynamic/economic/volumetric flow ratio分类
能源科技引用本文复制引用
韩中合,梅中恺,李鹏..变透平效率有机朗肯循环工质筛选及多目标优化[J].化工学报,2018,69(6):2603-2611,9.基金项目
国家自然科学基金项目(51306059) （51306059）
中央高校基本科研业务费专项资金项目(2017XS120).supported by the National Natural Science Foundation of China (51306059) and the Fundamental Research Funds for the Central Universities(2017XS120). （2017XS120）
