This work proposes a simultaneous approach for the synthesis and design optimization of industrial refrigeration cycles integrated with heat exchanger networks. Given the process hot and cold streams, the methodology determines the economically optimal refrigeration cycle configuration (number of evaporation/condensation levels, compressor intercooling, multiple throttling, etc.),cycle variables and heat exchanger network. The methodology includes a novel refrigeration cycle superstructure capable of reproducing a wide range of cycle architectures and an effective solution algorithm (based on the decomposition of the problem on two levels) to tackle the challenging Mixed Integer Non-Linear Program. The application to four literature case studies indicates that the proposed approach returns solutions which are considerably better both in terms of efficiency and economics than those published in literature. The application to four literature case studies indicate that the required computation time is tractable even for problems with thousands of variables and constraints (up to 87,000 real variables, 29,000 binary variables and 129,000 equations). Moreover, compared to previous literature studies, the optimized solutions feature a total annual cost reduction up to 40% and a decrease in compression power consumption up to 52%.

Simultaneous synthesis and optimization of refrigeration cycles and heat exchangers networks

Martinelli M.;Elsido C.;Martelli E.
2022

Abstract

This work proposes a simultaneous approach for the synthesis and design optimization of industrial refrigeration cycles integrated with heat exchanger networks. Given the process hot and cold streams, the methodology determines the economically optimal refrigeration cycle configuration (number of evaporation/condensation levels, compressor intercooling, multiple throttling, etc.),cycle variables and heat exchanger network. The methodology includes a novel refrigeration cycle superstructure capable of reproducing a wide range of cycle architectures and an effective solution algorithm (based on the decomposition of the problem on two levels) to tackle the challenging Mixed Integer Non-Linear Program. The application to four literature case studies indicates that the proposed approach returns solutions which are considerably better both in terms of efficiency and economics than those published in literature. The application to four literature case studies indicate that the required computation time is tractable even for problems with thousands of variables and constraints (up to 87,000 real variables, 29,000 binary variables and 129,000 equations). Moreover, compared to previous literature studies, the optimized solutions feature a total annual cost reduction up to 40% and a decrease in compression power consumption up to 52%.
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Utilizza questo identificativo per citare o creare un link a questo documento: http://hdl.handle.net/11311/1206677
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