Optimizing model predictive control of an industrial distillation column

The main scope of this work is the implementation of an MPC that integrates the control and the economic optimization of the system. The two problems are solved simultaneously through the modification of the control cost function that includes an additional term related to the economic objective. The optimizing MPC is based on a quadratic program (QP) as the conventional MPC and can be solved with the available QP solvers. The method was implemented in an industrial distillation system, and the results show that the approach is efficient and can be used, in several practical cases. (C) 2011 Elsevier Ltd. All rights reserved.

A strategy to extend reactive distillation column performance under catalyst deactivation

This work addresses the effects of catalyst deactivation and investigates methods to reduce their impact on the reactive distillation columns performance. The use of variable feed quality and reboil ratio are investigated using a rigorous dynamic model developed in gPROMS and applied to an illustrative example, i.e., the olefin metathesis system, wherein 2-pentene reacts to form 2-butene and 3-hexene. Three designs and different strategies on column energy supply to tackle catalyst deactivation are investigated and the results compared.

Optimization studies through simulation of a methanol/water/glycerol distillation column

This paper presents an optimization study of a distillation column for methanol and aqueous glycerol separation in a biodiesel production plant. Considering the available physical data of the column configuration, a steady state model was built for the column using Aspen-HYSYS as process simulator. Several sensitivity analysis were performed in order to better understand the relation between the variables of the distillation process. With the information obtained by the simulator, it is possible to define the best range for some operational variables that maintain composition of the desired product under specifications and choose operational conditions to minimize energy consumptions.

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Thermal design of a tray-type distillation column of an ammonia/water absorption refrigeration cycle

The goal of this paper is to present an analysis of a segmented weir sieve-tray distillation column for a 17.58 kW (5 TR) ammonia/water absorption refrigeration cycle. Balances of mass and energy were performed based on the method of Ponchon-Savarit, from which it was possible to determine the ideal number of trays. The analysis showed that four ideal trays were adequate for that small absorption refrigeration system having the feeding system to the column right above the second tray. It was carried out a sensitivity analysis of the main parameters. Vapor and liquid pressure drop constraint along with ammonia and water mass flow ratios defined the internal geometrical sizes of the column, such as the column diameter and height, as well as other designing parameters. Due to the lack of specific correlations, the present work was based on practical correlations used in the petrochemical and beverage production industries. The analysis also permitted to obtain the recommended values of tray spacing in order to have a compact column. The geometry of the tray turns out to be sensitive to the charge of vapor and, to a lesser extent, to the load of the liquid, being insensible to the diameter of tray holes. It was found a column efficiency of 50%. Finally, the paper presents some recommendations in order to have an optimal geometry for a compact size distillation column. (c) 2011 Elsevier Ltd. All rights reserved.

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Application of multivariable control using artificial neural networks in a debutanizer distillation column

LOPES, Jose Soares Batista et al. Application of multivariable control using artificial neural networks in a debutanizer distillation column.In: INTERNATIONAL CONGRESS OF MECHANICAL ENGINEERING - COBEM, 19, 5-9 nov. 2007, Brasilia. Anais... Brasilia, 2007

Design and manufacture of a microdistillation column

Aim of this thesis was to design and manufacture a microdistillation column. The literature review part of this thesis covers stainless steels, material processing and basics about engineering design and distillation. The main focus, however, is on the experimental part. Experimental part is divided into five distinct sections: First part is where the device is introduced and separated into three parts. Secondly the device is designed part by part. It consists mostly of detail problem solving, since the first drawings had already been drawn and the critical dimensions decided. Third part is the manufacture, which was not fully completed since the final assembly was left out of this thesis. Fourth part is the test welding for the device, and its analysis. Finally some ideas for further studies are presented. The main goal of this thesis was accomplished. The device only lacks some final assembly but otherwise it is complete. One thing that became clear during the process was how difficult it is to produce small and precise steel parts with conventional manufacturing methods. Internal stresses within steel plates and thermal distortions can easily ruin small steel structures. Designing appropriate welding jigs is an important task for even simple devices. Laser material processing is a promising tool for this kind of steel processing because of the flexibility, good cutting quality and also precise and low heat input when welding. Next step in this project is the final assembly and the actual distillation tests. The tests will be carried out at Helsinki University of Technology.

Logic hybrid simulation-optimization algorithm for distillation design

In this paper, we propose a novel algorithm for the rigorous design of distillation columns that integrates a process simulator in a generalized disjunctive programming formulation. The optimal distillation column, or column sequence, is obtained by selecting, for each column section, among a set of column sections with different number of theoretical trays. The selection of thermodynamic models, properties estimation etc., are all in the simulation environment. All the numerical issues related to the convergence of distillation columns (or column sections) are also maintained in the simulation environment. The model is formulated as a Generalized Disjunctive Programming (GDP) problem and solved using the logic based outer approximation algorithm without MINLP reformulation. Some examples involving from a single column to thermally coupled sequence or extractive distillation shows the performance of the new algorithm.

Rigorous Design of Complex Distillation Columns Using Process Simulators and the Particle Swarm Optimization Algorithm

We present a derivative-free optimization algorithm coupled with a chemical process simulator for the optimal design of individual and complex distillation processes using a rigorous tray-by-tray model. The proposed approach serves as an alternative tool to the various models based on nonlinear programming (NLP) or mixed-integer nonlinear programming (MINLP) . This is accomplished by combining the advantages of using a commercial process simulator (Aspen Hysys), including especially suited numerical methods developed for the convergence of distillation columns, with the benefits of the particle swarm optimization (PSO) metaheuristic algorithm, which does not require gradient information and has the ability to escape from local optima. Our method inherits the superstructure developed in Yeomans, H.; Grossmann, I. E.Optimal design of complex distillation columns using rigorous tray-by-tray disjunctive programming models. Ind. Eng. Chem. Res.2000, 39 (11), 4326–4335, in which the nonexisting trays are considered as simple bypasses of liquid and vapor flows. The implemented tool provides the optimal configuration of distillation column systems, which includes continuous and discrete variables, through the minimization of the total annual cost (TAC). The robustness and flexibility of the method is proven through the successful design and synthesis of three distillation systems of increasing complexity.

Rigorous design of distillation columns using surrogate models based on Kriging interpolation

The economic design of a distillation column or distillation sequences is a challenging problem that has been addressed by superstructure approaches. However, these methods have not been widely used because they lead to mixed-integer nonlinear programs that are hard to solve, and require complex initialization procedures. In this article, we propose to address this challenging problem by substituting the distillation columns by Kriging-based surrogate models generated via state of the art distillation models. We study different columns with increasing difficulty, and show that it is possible to get accurate Kriging-based surrogate models. The optimization strategy ensures that convergence to a local optimum is guaranteed for numerical noise-free models. For distillation columns (slightly noisy systems), Karush–Kuhn–Tucker optimality conditions cannot be tested directly on the actual model, but still we can guarantee a local minimum in a trust region of the surrogate model that contains the actual local minimum.

Ethanol dehydration via azeotropic distillation with gasoline fractions as entrainers: A pilot-scale study of the manufacture of an ethanol–hydrocarbon fuel blend

We establish experimentally and through simulations the economic and technical viability of dehydrating ethanol by means of azeotropic distillation, using a hydrocarbon as entrainer. The purpose of this is to manufacture a ready-to-use ethanol–hydrocarbon fuel blend. In order to demonstrate the feasibility of this proposition, we have tested an azeotropic water–ethanol feed mixture, using a hydrocarbon as entrainer, in a semi pilot-plant scale distillation column. Four different hydrocarbons (hexane, cyclohexane, isooctane, and toluene) that are representative of the hydrocarbons present in ordinary gasoline have been tested. Each of these hydrocarbons was tested separately in experiments under conditions of constant feed rate and variable reboiler heat duty. The experimentally obtained results are compared with results calculated by a simulator. Finally, the proposed and traditional ethanol dehydration processes are compared to ascertain the advantages of the former over the latter.

Ethanol dehydration via azeotropic distillation with gasoline fraction mixtures as entrainers: A pilot-scale study with industrially produced bioethanol and naphta

Various hydrocarbons (n-hexane, cyclohexane, toluene, isooctane) and mixtures of them (binary, ternary or quaternary), as well as two different types of industrially produced naphtha (one obtained by direct distillation and the other from a catalytic cracking process), have been tested as candidate entrainers to dehydrate ethanol. The tests were carried out in an azeotropic distillation column on a semi pilot plant. The results show that it is possible to dehydrate bioethanol using naphtha as entrainer, obtaining as a result a fuel blend with negligible water content and ready for immediate use in motor vehicles.

Computer control of chemical process plants with special reference to distillation

A sieve plate distillation column has been constructed and interfaced to a minicomputer with the necessary instrumentation for dynamic, estimation and control studies with special bearing on low-cost and noise-free instrumentation. A dynamic simulation of the column with a binary liquid system has been compiled using deterministic models that include fluid dynamics via Brambilla's equation for tray liquid holdup calculations. The simulation predictions have been tested experimentally under steady-state and transient conditions. The simulator's predictions of the tray temperatures have shown reasonably close agreement with the measured values under steady-state conditions and in the face of a step change in the feed rate. A method of extending linear filtering theory to highly nonlinear systems with very nonlinear measurement functional relationships has been proposed and tested by simulation on binary distillation. The simulation results have proved that the proposed methodology can overcome the typical instability problems associated with the Kalman filters. Three extended Kalman filters have been formulated and tested by simulation. The filters have been used to refine a much simplified model sequentially and to estimate parameters such as the unmeasured feed composition using information from the column simulation. It is first assumed that corrupted tray composition measurements are made available to the filter and then corrupted tray temperature measurements are accessed instead. The simulation results have demonstrated the powerful capability of the Kalman filters to overcome the typical hardware problems associated with the operation of on-line analyzers in relation to distillation dynamics and control by, in effect, replacirig them. A method of implementing estimator-aided feedforward (EAFF) control schemes has been proposed and tested by simulation on binary distillation. The results have shown that the EAFF scheme provides much better control and energy conservation than the conventional feedback temperature control in the face of a sustained step change in the feed rate or multiple changes in the feed rate, composition and temperature. Further extensions of this work are recommended as regards simulation, estimation and EAFF control.