In this paper, by combining a stochastic optimization method with a refrigeration shaft work targeting method,an approach for the synthesis of a heat integrated complex distillation system in a low-temperature process is presented. The synthesis problem is formulated as a mixed-integer nonlinear programming(MINLP) problem,which is solved by simulated annealing algorithm under a random procedure to explore the optimal operating parameters and the distillation sequence structure. The shaft work targeting method is used to evaluate the minimum energy cost of the corresponding separation system during the optimization without any need for a detailed design for the heat exchanger network(HEN) and the refrigeration system(RS). The method presented in the paper can dramatically reduce the scale and complexity of the problem. A case study of ethylene cold-end separation is used to illustrate the application of the approach. Compared with the original industrial scheme, the result is encouraging.
In low-temperature processes, there are interactions between heat exchanger network(HEN) and refrigeration system. The modification on HEN of the chilling train for increasing energy recovery does not always coordinate with the minimum shaft work consumption of the corresponding refrigeration system. In this paper, a systematic approach for optimizing low-temperature system is presented through mathematical method and exergy analysis. The possibility of "pockets", which appears as right nose section in the grand composite curve(EGCC) of the process, is first optimized. The EGCC with the pockets cutting down is designed as a separate part. A case study is used to illustrate the application of the approach for a HEN of a chilling train with propylene and ethylene refrigerant system in an ethylene production process.
