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In this study, optimization of a solar cooling system assisted ground source Heat Pump system (GSHP) is performed. The optimization process was carried out using a multi-objective evolutionary algorithm. Three optimization scenarios, including thermodynamic single objective, thermoeconomic single objective, and multi-objective optimizations, are performed. In the case of multi-objective optimization, an example of a decision-making process for selection of the final solution from the Pareto optimal frontier is presented. It was concluded that the multi-objective optimization considers two objectives of thermodynamic and economic, simultaneously. The results obtained using the various optimization approaches are compared and discussed. It is shown that the thermodynamic optimization is focused on provision for the limited source of energy, whereas the thermoeconomic optimization only focuses on monetary resources. In contrast, the multi-objective optimization considers both energy and monetary. The results showd that percentages of deviation from ideal values of thermodynamic and economic criteria for the thermodynamic optimized system were 0% and 905% respectively. These percentages for the economic optimized system were 104% and 0%, respectively. Deviation values from minimum ideal point for the multi-objective optimized design were obtained 10% and 88% for thermodynamic and economic criteria, respectively. It was concluded that the multi-objective design satisfies the thermodynamic and economic criteria better than two single-objective thermodynamic and economic optimized designs.

Keywords: Multi-Criteria Optimization, Hybrid Ground Source Heat Pump, Solar Cooling, genetic algorithm

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