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HERO ID
6213195
Reference Type
Journal Article
Title
Process optimization and plant-wide control for producing 1,3-dioxolane from aqueous formaldehyde solution and ethylene glycol
Author(s)
Gao, L; Li, J; Liu, J; Pan, Q; Sun, L; Sun, M; Yan, J; Zhang, L
Year
2019
Is Peer Reviewed?
1
Journal
Separation and Purification Technology
ISSN:
1383-5866
Volume
236
Page Numbers
116235
DOI
10.1016/j.seppur.2019.116235
Web of Science Id
WOS:000509819400013
URL
http://www.sciencedirect.com/science/article/pii/S1383586619331120
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Abstract
1,3-Dioxolane (DOL) is an important chemical raw material with wide application, but the traditional production process of DOL has many problems that affect operational efficiency and quality, such as low conversion rate, high separation energy consumption, and complicated production process. Recently, a new process, which adopts reactive distillation and pressure swing distillation techniques, has been proposed for producing 1,3-dioxolane from aqueous formaldehyde solution and ethylene glycol. However, the researches on the process optimization and plant-wide control strategy for this new flowsheet are still in the original state. In this paper, multi-objective genetic algorithm (MOGA) is adopted to obtain the optimal process design parameters, and the economic implications, controllability, and ecological benefits of the process are selected as objective functions. Then, complex network topologies are established on the dynamic simulation data, and the key controlled variable is found by calculating central characteristics. Based on the principles of plant-wide control strategy and the complex network analysis results, three control schemes are developed in the dynamic simulation program, which can help to examine the robust stability and controllability of the system under different feed disturbances. The dynamic responses indicate that the CS3 scheme has better anti-interference ability, and the proposed analysis method can assist the development of the control system.
Keywords
1,3-dioxolane; Process optimization; Plant-wide control; Dynamic simulation
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