Exergetic-Economic analysis and optimization of solar assisted heat pump using Multi-objective Genetic Algorithm

This study proposes the use of two-stage heat pump systems (SAHPs) for high temperature applications, 105°C. This system integrates solar thermal collectors and heat pumps into a hybrid system to meet the 400 kW heating load. The aim of this research is providing a method to deliver heat with sustainable energy resource, than to improve the performance of the system which is indicated by low exergy destruction. The model creation, performance evaluation and the optimization of solar assisted heat pump system are discussed in this paper. This system used R1234ze (E) as working fluid. A genetic algorithm is employed to optimize operation condition of the system. To ensure that the optimal solution obtained from the proposed method is an optimum condition, three constraints are selected, including evaporation temperatures, condensing temperatures and compressor temperatures while exergy destruction and total cost as the objective functions. The result showed that the system has an optimum condition at evaporating temperature of 317 K, Flash Tank temperature of 353.6 K and condensing temperature of 380.4 K with exergy destruction of 70.21 kW and total cost of 63,441 US$.