Investigation of cascade high temperature heat pump optimal design theory based on experiment supporting multi-objective optimization

Abstract

Cascade high temperature heat pump has been drawing wide attention due to its impressive application prospects to upgrade the low temperature heat. However, the relatively high initial cost has been hindering its application. Therefore, a refined design theory considering both thermodynamic performance and economic performance has been proposed. Herein, multi-objective optimization model with the improved non-dominated sorting genetic algorithm was adopted to determine the key design parameters: evaporation temperature and condensation temperature. The cost of per exergy output and initial cost of per heat capacity were cited as objective functions. Based on the Pareto fronts and the technique for order preference by similarity to an ideal solution method, the most favorable evaporation temperature and condensation temperature were determined. For the working condition of constant heat source temperature and different output water temperatures, the optimal evaporation and condensation temperatures were 15.27 °C and 101.93 °C, 13.06 °C and 111.77 °C, 11.44 °C and 121.58 °C, which denoted that the optimal condensation temperature increased along with the output water temperature but the differences between them were kept with a rather small range. For the working condition of constant output water temperature and different heat source temperatures, the optimal evaporation temperature and condensation temperature were 11.21 °C, 11.44 °C, 11.95 °C and 121.8 °C, 121.58 °C, 122.03 °C, respectively. Conclusion that optimal design evaporation temperature and condensation temperature were barely influenced by the heat source temperature could be drawn.