Optimization and control of extractive distillation for formic acid-water separation with maximum-boiling azeotrope. (January 2023)

• Record Type: Journal Article
• Authors: Ge, Xiaolong; Zhang, Ran; Liu, Pengfei; Liu, Botan; Liu, Botong
• Is Part Of: Computers & chemical engineering. Volume 169(2023)
• Publication Date: 2023-01
• Subjects: Process intensification -- Sustainability -- Extractive distillation -- Process optimization -- Linear model predictive control; Chemical engineering -- Data processing -- Periodicals; 660.0285
• DOI: 10.1016/j.compchemeng.2022.108075
• Languages: English
• ISSNs: 0098-1354

Abstract

Highlights: Energy-efficient extractive distillation process for formic acid-water separation developed. Optimization for series separation processes conducted with genetic algorithm. Operational issues with respect to intensified process investigated by advanced control scheme. Model-based control scheme shows its superiority for efficient extractive distillation process. Abstract: It is urgent to develop sustainable chemical process through process intensification, especially for the energy-intensive distillation process. Formic acid-water forms maximum azeotrope which is purified by pressure-swing distillation in Kemira–Leonard (K-L) process and extraction plus distillation in BASF route. However, either process for this maximum azeotrope separation is energy-intensive. In the present work, by selecting the effective heavy entrainer, extractive distillation and extractive dividing wall column was firstly synthesized and optimized with genetic algorithm for formic acid-water separation. Based on optimal design, the energy consumption and CO2 emission among these proposed and existent processes were compared, and extractive distillation shows its strength for achieving high efficiency and sustainability. Then multi-loop PI control scheme and linear model predictive control based on temperature and temperature difference were developed, respectively. Dynamic response validates the control performance superiority of advanced controllers, especially for controlled variables with large overshoot, oscillations and settling time.