cold-climate, vapor injected, two-stage, genetic algorithm, exergo-economic optimization
The rise of energy consumption and environmental concerns necessitate research efforts on optimizing HVAC systems. Air source heat pump systems are widely used as space conditioning systems because of their low cost of installation and the possibility of achieving both heating and cooling from the same device. However, under extreme conditions especially in heating mode, conventional heat pumping systems face challenges when operating in cold climate at ambient temperatures that fall below 0°C (32°F). In this paper, a two-stage vapor injection heat pump system with R-32, R-290 and R-410A as the working fluids, was investigated by considering both single objective (heating COP and unit cost of heating (UCH), as the thermodynamic and thermo-economic criteria, respectively) and multi-objective (maximum heating COP and minimum UCH) optimizations at low ambient conditions. The system model was developed by using Engineering Equation Solver (EES) and the optimizations have been carried out with the available genetic algorithm (GA) method. From a multi-objective standpoint, the Pareto frontier decision-making process was used for the selection of final solution. The results revealed that R-32 and R-290 were the best selections for the investigated system based on exergo-economic and thermodynamic criteria, respectively. The system with R-32 and R-290 had a minimum UCH of 265 $/kWh and a maximum heating COP of and 3.94. Whereas, for the baseline system with R-410A, the heating COP, exergy efficiency and the UCH were estimated to be 3.75, 30.31% and 384.2 $/kWh, respectively.