Extractive Dividing Wall Column: Design and Optimization

Bravo-Bravo, Cristofer; Segovia‐Hernández, Juan Gabriel; Gutiérrez‐Antonio, Claudia; Durán, Ana Luisa; Bonilla-Petriciolet, Adrián; Briones-Ramírez, Abel

doi:10.1021/ie9006936

Cited by 147 publications

(104 citation statements)

References 37 publications

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“…Remarkably, DWC is the only known large scale process intensification example where both capital and operating costs can be vastly reduced, with the additional benefit of reducing the required installation space by up to 40% [8,3]. Moreover, DWC is not limited to ternary separations only but it can be used also in extractive distillation [6], azeotropic separations [32], and reactive distillation [36,17,26,33]. DWC is considered a major breakthrough in distillation, as it brings significant reduction in CapEx and OpEx -up to 30-40% [19,8].…”

Section: Introductionmentioning

confidence: 99%

Reactive DWC leading the way to FAME and fortune

Kiss

Segovia‐Hernández

Bîldea

et al. 2012

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a b s t r a c tReactive separation processes were recently proposed for the synthesis of fatty acid methyl esters (FAMEs), most of them making use of solid catalysts thus eliminating all conventional catalyst-related operations, improving process efficiency and reducing energy requirements. Such integrated systems require a stoichiometric reactants ratio in order to achieve complete conversion and high purity products. However, maintaining this ratio can be very difficult in practice, especially when the fatty acids feed composition is not constant in time.This study proposes a novel biodiesel process based on a reactive dividing-wall column (R-DWC) that allows the use of only $15% excess of methanol to completely convert the fatty acids feedstock. FAME are produced as pure bottom product, water as side stream, while the methanol excess is recovered as top distillate and recycled. The design is a challenging global optimization problem with discrete and continuous decision variables. The optimal setup was established by using simulated annealing as optimization method implemented in Matlab, and coupled with rigorous simulations carried out in Aspen Plus. Along with the FAME production, the novel design alternatives allow a fortune to be saved by reducing the energy requirements with over 25% and by using less equipment units than conventional processes.

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Section: Introductionmentioning

confidence: 99%

Reactive DWC leading the way to FAME and fortune

Kiss

Segovia‐Hernández

Bîldea

et al. 2012

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106

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“…DWC has been also applied to complex distillation systems. Wang extended DWC to azeotropic distillation [12], while other references deal with extractive and reactive DWC [13,14].…”

Section: Control Strategies For Divided-wall Columnsmentioning

confidence: 99%

Control of integrated unit operations

Chinea-Herranz¹,

Rodríguez²

2012

Computer Aided Chemical Engineering

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As a thermal separation method, distillation is one of the most important technologies in the chemical industry. Given its importance, it is no surprise that increasing efforts have been made in reducing its energy inefficiencies. A great deal of research is focused in the design and optimization of the Divided-Wall Column. Its applications are still reduced due to distrust of its controllability. Previous references studied the decentralized control of DWC but still few papers deal about Model Predictive Control. In this work we present a decentralized control of both a DWC column along with its equivalent MPC schema.Keywords: Process Control, Thermally coupled distillation, Model Predictive Control. Main TextBasically, in every production process some of the chemicals go through at least one distillation column on their way from raw species to final product. Distillation is and will remain the main separation method in the chemical industry (there are more than 50,000 columns in operation around the world). Despite its flexibility and widespread use, distillation is very energy demanding. It can generate more than 50% of plant operating costs and it is the responsible of 3% of the energy usage in the U.S. (notice that the thermodynamic efficiency of a distillation column is between 5-20%). In order to reduce this drawback new approaches and configurations have appeared. The divided-wall column (DWC, the name is given because the middle part of the column is split into two sections by a wall) is an important example of process intensification and integration. DWC is very appealing to the chemical industry, with Montz and BASF as the leading companies. Kenig et al. state that there are more than 125 industrial applications nowadays and if the exponential trend continues there will be more than 350 by 2015 [1]. DWC can separate three or more components in one vessel using a single condenser and reboiler, hence reducing capital and operating costs compared to conventional twocolumn sequences. In fact, DWC can save up to 30% in the capital invested and up to 40% in the energy costs, particularly for close boiling species. DWC is considered to be on the path for energy conservation and green house gases emissions decrease. DWC is not widespread due to distrust of its controllability. Its control is more difficult than the control of a conventional schema with two columns for the separation of ternary mixtures because there is more interaction among control loops. Besides, the absence of controllability could mean the absence of the energy savings if the optimal operation is not accomplished. The remaining of the paper is organized as follows. Section two discusses thermally coupled distillation columns, making emphasis in DWC columns. Section three presents the control strategies used in the paper. Section four applies decentralized (PID controllers) control and MPC to a ternary system separation. Finally, section five draws conclusions and introduces further work.

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“…The same combination of process simulator and metaheuristic algorithm is adopted by Vazquez-Castillo et al (2009) to address the optimization of five distillation sequences. Subsequent works used a multiobjective GA ) for the optimization of thermally coupled distillation systems (Bravo-Bravo et al, 2010;Cortez-Gonzalez et al, 2012;Gutérrez-Antonio et al, 2011), and for the retrofit of a subcritical pulverized coal power plant with an MEA-based carbon capture and CO2 compression system (Eslick & Miller, 2011). Finally, Odjo et al (2011) also presented a general M a n u s c r i p t 5 framework for the synthesis of chemical processes using a hybrid approach with Hysys and genetic algorithms.…”

Section: Introductionmentioning

confidence: 99%

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

Navarro-Amorós

Ruiz‐Femenia

2014

Computers & Chemical Engineering

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HighlightsA new modeling framework that exploits the synergistic combination of commercial process simulators and GDP models Our methodology allows to include easily logical relationships among alternativesThe proposed tool uses a logic based Outer Approximation algorithmThe methodology is applied to the synthesis of a methanol plant where different alternatives AbstractThe optimization of chemical processes where the flowsheet topology is not kept fixed is a challenging discrete-continuous optimization problem. Usually, this task has been performed through equation based models. This approach presents several problems, as tedious and complicated component properties estimation or the handling of huge problems (with thousands of equations and variables). We propose a GDP approach as an alternative to the MINLP models coupled with a flowsheet program. The novelty of this approach relies on using a commercial modular process simulator where the superstructure is drawn directly on the graphical use interface of the simulator. This methodology takes advantage of modular process simulators (specially tailored numerical methods, reliability, and robustness) and the flexibility of the GDP formulation for the modeling and solution. The optimization tool proposed is successfully applied

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Extractive Dividing Wall Column: Design and Optimization

Cited by 147 publications

References 37 publications

Reactive DWC leading the way to FAME and fortune

Reactive DWC leading the way to FAME and fortune

Control of integrated unit operations

Integration of modular process simulators under the Generalized Disjunctive Programming framework for the structural flowsheet optimization

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