A Two-step Optimization Algorithm Assisted by Pseudo-Transient Continuation Models for Single-Column Extractive Distillation Process

计算机科学 萃取蒸馏 数学优化 共沸物 工艺工程 过程(计算) 能源消耗 最优化问题 继续 模块化设计 蒸馏 工艺优化 能量(信号处理) 算法 流量(数学) 分馏塔 功能(生物学) 体积流量 二次无约束二元优化 优化算法 二进制数 迭代法 全局优化 在制品
作者
Xingchen Song,Fucheng Xu,Weiyang Wang,Lianghua Xu,Yiqing Luo
出处
期刊:Industrial & Engineering Chemistry Research [American Chemical Society]
卷期号:64 (41): 19900-19907
标识
DOI:10.1021/acs.iecr.5c01948
摘要

Single-column extractive distillation with an internally circulated intermediate boiling entrainer process (IC-SCED) realizes the separation of some binary azeotropic mixtures with low energy consumption and equipment cost. However, the simulation and optimization of this process are significantly difficult, as the flow rate of the IC entrainer cannot be specified directly in the sequential modular (SM) environment. In our previous work, a two-column model and its corresponding sequential iterative optimization procedure are proposed, while this optimization procedure is highly time-consuming, and the global optimum is difficult to achieve. In this work, we propose a new simulation and optimization strategy for the IC-SCED process. The IC-SCED process is simulated by pseudotransient continuation (PTC) models in an equation-oriented (EO) environment. Then, a two-step steady-state optimization algorithm is used to optimize the models. In the first optimization step, the total energy consumption per product unit is chosen as the objective function to ensure a sufficient amount of entrainer flow rate for breaking the azeotrope in the column. In the second optimization step, the total annual cost (TAC) is chosen as the objective function to optimize all decision variables. Two optimization cases are studied to evaluate the performance of the proposed algorithm. The computational results demonstrate that the proposed algorithm converges successfully and rapidly. The obtained optimal IC-SCED processes have a lower energy consumption and total annual cost than the processes achieved in our previous work.
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