Thermal-Economic Optimization and Working Fluid Selection of Subcritical Organic Rankine System for Low-Temperature Waste Heat Recovery

In the present study, multi-objective optimization is conducted to search for the best operating condition for a subcritical organic Rankine system with the trade-off between system exergy efficiency and dynamic payback period (PBP). A 150°C wastewater heat source is employed as a typical low-temperature heat source. Five decision variables are considered: turbine inlet temperature and pressure, pinch point temperature differences in evaporator and condenser, and condensing temperature. The multi-objective genetic algorithm combined with the backpropagation neural network method is employed as the optimization approach. In addition, the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) is developed to gain the optimal Pareto front solution for either working fluid and find the optimal working fluid among the candidates investigated. The results show that working fluid R236fa is the optimal solution, despite the minimum PBP for working fluid R123 and the maximum system exergy efficiency for working fluid R1234ze. Under the optimal working condition for working fluid R236fa, the system exergy efficiency and the PBP are 0.465 and 7.377 years, respectively