4.7 Article

Design and comprehensive analysis of a novel pressure-swing batch distillation process for the separation of a binary azeotrope with various boiling behaviors

Journal

SEPARATION AND PURIFICATION TECHNOLOGY
Volume 251, Issue -, Pages -

Publisher

ELSEVIER
DOI: 10.1016/j.seppur.2020.117329

Keywords

Pressure-swing batch distillation; Multi-objective optimization; Exergy analysis; Heat integration; Economic analysis

Funding

  1. National Natural Science Foundation of China [21776145, 21676152]
  2. Taishan Scholar Young Talent Program [tsqn201909114]

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Batch distillation is widely employed in the fine chemical industry because of its operational flexibility. The mixture of n-heptane and isobutanol exhibits a special azeotropic phenomenon by which it changes from a minimum-boiling azeotrope to a maximum-boiling one with increasing pressure. However, the traditional double column batch rectifier and double column batch stripper processes cannot separate the mixture efficiently. Therefore, the double-column batch stripper-rectifier (DCBS-R) process was designed to obtain high purity products, based on the azeotropic phenomenon. Further, control structures are explored to achieve stability, and the final purities of the separated products are over 99.9%. Each batch of raw materials is 100 kmol, and the expected annual production capacity is 800 batches. Additionally, a precooler of the low-pressure column (LPC) is introduced to reduce the exergy destruction by exergy analysis. The equipment cost and CO2 emissions are analyzed afterward to optimize the process, based on the multi-objective optimization method. Further, the number of stages and the pressure of the columns are optimized. The optimal obtained total annual cost (TAC) and CO2 emissions of the DCBS-R process are 2.26 x 10(5) $/y and 4.92 x 10(5) kg/y, respectively. The partial heat integration is studied to further improve the process performance, thus obtaining TAC and CO2 emissions of 2.22 x 10(5) $/y and 3.80 x 10(5) kg/y, which are 7.1% and 22.76% lower than the values obtained from the optimal process, respectively.

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