Journal
ENERGY
Volume 272, Issue -, Pages -Publisher
PERGAMON-ELSEVIER SCIENCE LTD
DOI: 10.1016/j.energy.2023.127103
Keywords
Organic rankine cycle; Vapor compression refrigeration; Multi -layer performance optimization; Parametric analysis; Multi -objective optimization; Working fluids selection
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In this study, a multi-layer performance optimization method is used to optimize the ORC-VCR system. Firstly, parametric analysis and multi-objective optimization are conducted in operation parameter layer optimization, considering thermodynamic, economic and environmental performance. Then, working fluid selection under different heat source temperature is performed in working fluid layer optimization based on the results of multi-objective optimization. Finally, the optimal heat source temperature for all working fluids is determined in heat source layer optimization. The results show that the increase of heat source temperature leads to an increase in the generation temperature and condensation temperature of the optimal solution, while the evaporation temperature remains concentrated on the lower limit. The COP nearly remains the same, while NPV and AER continuously increase. Among the candidate working fluids, HCs have the best comprehensive performance and R602 is almost the optimal working fluid under all heat resource temperature. The optimal heat source temperature for all working fluids is concentrated on high-temperature region. The multi-layer performance optimization method provides a novel idea for improving comprehensive system performance.
As an effective energy utilization technology, the ORC-VCR system has great development potential. Multi-layer performance optimization of operation parameter-working fluid-heat source for the ORC-VCR system is carried out. Firstly, parametric analysis and multi-objective optimization are conducted by simultaneously considering thermodynamic, economic and environmental performance in operation parameter layer optimization. Then, working fluid selection under different heat source temperature is performed based on the results of multi -objective optimization in working fluid layer optimization. Finally, the optimal heat source temperature for all working fluids is determined in heat source layer optimization. The results show that with the increase of heat source temperature, generation temperature and condensation temperature of the optimal solution increase and change from centralized to dispersed, while evaporation temperature is always concentrated on the lower limit. COP nearly remains the same. NPV and AER increase continuously. Among the candidate working fluids, HCs have the best comprehensive performance and R602 is almost the optimal working fluid under all heat resource temperature. The optimal heat source temperature for all working fluids is concentrated on high-temperature region. The multi-layer performance optimization method provides a novel idea for improving comprehensive system performance.
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