TY - JOUR
T1 - Thermoeconomic analysis and multi-objective optimization of a novel hybrid absorption/recompression refrigeration system
AU - Razmi, Amir Reza
AU - Arabkoohsar, Ahmad
AU - Nami, Hossein
PY - 2020/11
Y1 - 2020/11
N2 - In the present article, thermodynamic, exergoeconomic, economic, and sustainability investigations of a recently developed environmentally friendly hybrid absorption/recompression refrigeration cycle is proposed to evaluate its feasibility for decision making and marketing. The proposed system is a novel hybridization of the conventional vapor compression and absorption cycles, wherein a booster compressor has been used between the generator and condenser of the single-effect absorption cycle to improve its performance. Also, two separate multi-objective optimization models are developed using a combination of the nondominated-storing-genetic algorithm (NSGA-II) and artificial neural network (ANN) to address the optimum performance values concerning the objective functions. The obtained results approve that the proposed cycle is a promising concept from both thermodynamic and economic viewpoints. The results indicate that the system presents a coefficient of performance and exergy efficiency of 4.88 and 37.43% under the optimum working conditions. The overall rate of exergy destruction of the system is 20.23 kW, and a sustainability index of around 1.53 can be achieved at a cooling capacity of 150 kW. The economic results indicate that the reference system has a payback period of 4.17 years, which is reduced to less than 4 years after doing the optimizations.
AB - In the present article, thermodynamic, exergoeconomic, economic, and sustainability investigations of a recently developed environmentally friendly hybrid absorption/recompression refrigeration cycle is proposed to evaluate its feasibility for decision making and marketing. The proposed system is a novel hybridization of the conventional vapor compression and absorption cycles, wherein a booster compressor has been used between the generator and condenser of the single-effect absorption cycle to improve its performance. Also, two separate multi-objective optimization models are developed using a combination of the nondominated-storing-genetic algorithm (NSGA-II) and artificial neural network (ANN) to address the optimum performance values concerning the objective functions. The obtained results approve that the proposed cycle is a promising concept from both thermodynamic and economic viewpoints. The results indicate that the system presents a coefficient of performance and exergy efficiency of 4.88 and 37.43% under the optimum working conditions. The overall rate of exergy destruction of the system is 20.23 kW, and a sustainability index of around 1.53 can be achieved at a cooling capacity of 150 kW. The economic results indicate that the reference system has a payback period of 4.17 years, which is reduced to less than 4 years after doing the optimizations.
U2 - 10.1016/j.energy.2020.118559
DO - 10.1016/j.energy.2020.118559
M3 - Journal article
SN - 0360-5442
VL - 210
JO - Energy
JF - Energy
M1 - 118559
ER -