Parametric study and performance-based multi-criteria optimization of the indirect-expansion solar-assisted heat pump through the integration of Analytic Network process (ANP) decision-making with MOPSO algorithm

Abstract

The current research intends to design and develop the simulation-based multi-criteria optimization (MCO) of the indirect-expansion solar-assisted heat pump (IX-SAHP) used to supply sustainable warm water for buildings. The developed IX-SAHP is verified and its performance is studied in the temperate climate of Iran every month of the year. The parametric analysis (PA) is performed using one-variable-at-a-time (OVAT) approach to analyze the impacts of input variables of the IX-SAHP on the system performance. Furthermore, the single and multi-objective particle swarm optimizations (MOPSO) are integrated with the designed IX-SAHP to maximize the coefficient of performance (COP) and the solar collector efficiency (SCE), independently and concurrently to study the trade-off in the COP and SCE of the system, to achieve the optimal non-dominated solutions in the form of Prato front, and to define the optimal configuration and operating parameters of the system. Eventually, the final optimum configuration is chosen through the Analytic Network Process (ANP) multiple-criteria decision-making (MCDM) method integrated with the MOPSO algorithm using MatLab coupling functions. The comparison of achieved optimum solutions indicates that the MCO scheme provides better comprehensive performance, more appropriate and reliable solutions in comparison with the single-criterion optimization (SCO) schemes. The results of the MCO process indicate that whereas the SCE relatively lessens from 52% to 47%, the COP enhances considerably from 3 to 7 in comparison with the baseline design so that the total operating hour of the optimized IX-SAHP lessens close to 282 h throughout the year that leads to considerable lessening of the total power consumption of the system. This study demonstrates the importance of MCO, OVAT, and MCDMs in the design stages of energy systems to maximize the performance and minimize power consumption of the system.