摘要
The organic Rankine cycle(ORC) has attracted attention for waste heat recovery and renewable energy systems.An accurate prediction for thermodynamic properties of working fluids is of great importance for cycle performance evaluations and system design. Particularly, hydrocarbons are promising for their good performance and low global warming potentials. Moreover, the thermal efficiency of the ORC is higher when the evaporation temperature is closer to the critical temperature, which makes the properties in the critical region rather important. Recent research has shown that using mixture as working fluid can achieve better temperature matches. Therefore, an equation of state(Eo S) that can be extended to mixture calculations is more attractive. Specific Eo S for selected hydrocarbons is precise, but very complex. Cubic Eo Ss, such as widely used Peng–Robinson Eo S and Soave–Redlich–Kwong(SRK) Eo S, fail to accurately predict liquid densities over wide pressure ranges or pressure–density–temperature(pρT) properties in the near-critical region. This work combines the volume translation approach and the crossover method to provide better prediction for thermodynamic properties in the critical region and in regions far from the critical point. A crossover volume translation SRK Eo S is developed and used for n-butane, i-butane, n-pentane, i-pentane, n-hexane, i-hexane and n-heptane. The volume translation term is set as a constant to ensure the accuracy of the saturated liquid density at low reduced temperatures. Then, the crossover method is introduced into the volume translation Eo S to improve the predictions of thermodynamic properties in the critical region. Six crossover parameters are used, which are constants or functions of acentric factor and critical parameters. Therefore, none of the parameters in the crossover volume translation SRK Eo S is adjustable, which makes the crossover Eo S totally predictive and easily extend to mixtures. Comparisons show that the crossover Eo S is in much better agreement with experimental data than the original SRK Eo S.
The organic Rankine cycle(ORC) has attracted attention for waste heat recovery and renewable energy systems.An accurate prediction for thermodynamic properties of working fluids is of great importance for cycle performance evaluations and system design. Particularly, hydrocarbons are promising for their good performance and low global warming potentials. Moreover, the thermal efficiency of the ORC is higher when the evaporation temperature is closer to the critical temperature, which makes the properties in the critical region rather important. Recent research has shown that using mixture as working fluid can achieve better temperature matches. Therefore, an equation of state(Eo S) that can be extended to mixture calculations is more attractive. Specific Eo S for selected hydrocarbons is precise, but very complex. Cubic Eo Ss, such as widely used Peng–Robinson Eo S and Soave–Redlich–Kwong(SRK) Eo S, fail to accurately predict liquid densities over wide pressure ranges or pressure–density–temperature(pρT) properties in the near-critical region. This work combines the volume translation approach and the crossover method to provide better prediction for thermodynamic properties in the critical region and in regions far from the critical point. A crossover volume translation SRK Eo S is developed and used for n-butane, i-butane, n-pentane, i-pentane, n-hexane, i-hexane and n-heptane. The volume translation term is set as a constant to ensure the accuracy of the saturated liquid density at low reduced temperatures. Then, the crossover method is introduced into the volume translation Eo S to improve the predictions of thermodynamic properties in the critical region. Six crossover parameters are used, which are constants or functions of acentric factor and critical parameters. Therefore, none of the parameters in the crossover volume translation SRK Eo S is adjustable, which makes the crossover Eo S totally predictive and easily extend to mixtures. Comparisons show that the crossover Eo S is in much better agreement with experimental data than the original SRK Eo S.
基金
Supported by the National Natural Science Foundation of China(51076074,51236004,51321002)
