Saeid Hosseini - University of Tehran, Faculty of Managemen, Department of MBA, Tehran, Iran,
Navid Delgarm - University of Tehran, College of Engineering, Department of Mechanical Engineering, Tehran, Iran

This paper aims to develop a thermodynamic model and a multi-objective optimization for the thermal performance of a direct-expansion solar-assisted heat pump water heater (DX-SAHPWH). In the current investigation, the heat pump design parameters such as the solar collector area, compressor speed, collector tilt angle, length and outside diameter of coil in the condenser are chosen as decision variables. A parametric study is conducted to identify how various input factors may affect the DX-SAHPWH system. A multi-objective non-dominated sorting genetic algorithm (NSGA–II) is employed to obtain the optimal solutions of design parameters, where the coefficient of performance (COP) and the solar collector efficiency (SCE) are taken as two fitness functions. The achieved optimum solutions from the bi–criteria optimization process is given as Pareto frontier. The ultimate optimal solution from available solutions on the Pareto optimal curve is selected using TOPSIS decision-making method. In addition, single-objective optimization is performed for each objective function in order to compare the results with the optimum solutions achieved by the bi-objective optimization as well as the performance measures of the base-case system to identify the behaviour of the objective functions. The comparisons of single and bi-objective optimization results illustrate that bi-objective optimization method yields the more adequate results, mainly because of the lower deviation index from the ideal solution. The results of bi-objective optimization show ۸.۷۶% diminution in the SCE in comparison with the initial test case, while the COP increases close to ۹۱.۵۳% that makes the optimal solution more desirable respect to the single ones

Direct-expansion solar-assisted heat pump, Solar collector efficiency, Coefficient of performance, Building energy efficiency, Multi-objective optimization