Heat Integrated Distillation Sequences Research Articles

Synthesis of Heat-Integrated Distillation Sequences with Nonsharp Splits Using a Sequential Metaheuristic Method

Synthesis of Heat-Integrated Distillation Sequences with Nonsharp Splits Using a Sequential Metaheuristic Method

Synthesis of heat-integrated distillation sequences with mechanical vapor recompression by stochastic optimization

A method of synthesis of heat-integrated distillation sequences with mechanical vapor recompression (MVR-HIDSs) is proposed based on stochastic optimization in this study. The purpose is to introduce heat pump operation, which can be driven by green electricity, to distillation sequencing as a way of altering stream temperatures to increase the chance of heat integrations. Two types of MVR-HIDSs, namely the vapor recompression heat-integrated distillation sequences (VR-HIDSs) and bottom flashing heat-integrated distillation sequences (BF-HIDSs), are considered for the synthesis separately. To illustrate the proposed method, a case for separating five-component alcohol mixture is solved by the proposed method. The results show that the incorporation of the MVR can provide effectively higher economic efficiency compared with the traditional optimal heat-integrated and thermal coupled distillation sequences. The proposed method makes it possible to synthesize distillation sequences that use green electricity to partially replace the fossil fuel based thermal energy to reduce CO2 emission.

Simultaneous optimization of nonsharp distillation sequences and heat integration networks by simulated annealing algorithm

Based on stochastic optimization, a new method is proposed to synthesize heat integrated distillation sequences (HIDiSs), which are basic configurations and allow nonsharp splits with at most two middle components. Distillation sequences and heat integration networks are simultaneously optimized to minimize the total annual cost (TAC) of HIDiSs. First, the synthesis problem is formulated as an implicit mixed-integer nonlinear programming problem. Discrete variables are distillation sequences. Continuous variables include operating pressures, key component recoveries and ratios of the actual reflux ratios to the minimum reflux ratios in columns. Next, solution strategies are presented, including representing distillation sequences through a novel encoding method, randomly generating neighboring distillation sequences, automatically determining heat integration networks by the pinch method, and calculating the TAC based on shortcut design of columns. Then, the optimization problem is solved by an improved simulated annealing algorithm. Finally, correctness verification for the method is made in two case studies. The optimization algorithm is proved to be computationally efficient and capable to obtain high-quality optimal solution. The results demonstrate that heat integration between columns significantly reduces the energy consumption compared to the non-integrated distillation sequences. Moreover, nonsharp HIDiSs can further reduce the TAC compared to those with only sharp splits.

The Use of Factorial Design to Improve a Harmony Search Algorithm to Synthesize Heat-Integrated Distillation Sequences

Optimization problems often involve a large number of design variables, and the exact influence of each of these variables upon the objective function can become rather complex; there may exist local optima for the objective function, but for the typical heat-integrated distillation sequence, the matter of interest is solely the global optimum. Therefore, it is necessary to create a stochastic algorithm method which can synthesize distillation systems with multiple components. The encoding process employs and integer number series which allows the system flow sheet structure to be portrayed and then managed. Within this portrayal, the broad synthesis problem takes the form of an implicit MILP (mixed-integer linear programming) problem. This study considers the attributes of six well-known optimization algorithms: Harmony Search algorithm (HS), Artificial Bee Colony (ABC), Bat Algorithm (BA), Crow Search Optimization (CSO), Grew Wolf Optimization (GWO) and Monarch Butterfly Optimization (MBO). The optimal variables which influence the harmony search algorithm can be determined through full factorial design analysis. These variables can then be employed in the search to discover the optimal heat-integrated distillation sequence. The study investigates the attributes of the optimal configuration solution, in terms of harmony size (HS), required number of iterations, harmony memory considering the rate (HMCR), and pitch adjustment rate (PAR). The study then adopts the HS algorithm which is duly improved in order to address the problem. In comparison with alternative techniques, HS is more effective and more robust than other approaches.

Controllability analysis of heat integrated distillation systems for a multicomponent stream

Understanding the dynamic behavior of distillation columns has received considerable attention due to the fact that distillation is one of the most widely used unit operations in chemical process industries. Heat integrated distillation sequences can provide significant energy savings; however, they exhibit a complex structure which appears to affect their controllability properties. One potential solution to this problem has been suggested through the operation of heat integrated sequences under the conditions that do not provide minimum energy requirements. But, this work proved that the process under the conditions of minimum energy requirements can operate with the best controllability properties. In this work, the controllability properties were analyzed with the application of the Morari resiliency index, condition number and relative gain array, which were frequency-dependent indices. The results showed that the controllability of the best heat integrated distillation column with the minimum total annual cost was better than other sequences.

A simulated annealing-based approach to the optimal synthesis of heat-integrated distillation sequences

A simulated annealing-based approach to synthesis of multi-component distillation systems is developed. An encoding procedure that makes use of an integer number series is developed to represent and manipulate the flow sheet structure of the system. With the representation procedure, the overall synthesis problem is formulated as an implicit mixed-integer nonlinear programming (MINLP) problem. A simulated annealing approach suitable for MINLP optimization is adopted and improved to solve the problem. Four example problems, including large-scale ones are solved to illustrate the approach.

Structural Considerations and Modeling in the Synthesis of Heat-Integrated−Thermally Coupled Distillation Sequences

This paper examines the design of mixed thermally coupled−heat-integrated distillation sequences. The approach considers a variety of methodologies, from conventional columns (each distillation column with a condenser and a reboiler) to fully thermally coupled systems (only one reboiler and one condenser in the entire system). A discussion about superstructure generation and the convenience of using a representation based on separation tasks instead of equipment is presented, as well as a set of logical rules in terms of boolean variables that allow all of the feasible structures to be generated systematically. Based on the logical rules, an algorithm is developed for generating valid sequences (even by hand) without explicitly solving the logical equations. All the specific aspects were related to intercolumn heat integration when partially thermally coupled systems are considered. A disjunctive programming formulation for extracting the optimal solution is presented. The model is based on the Fenske−Und...

Evaluation of hybrid optimization methods for the optimal design of heat integrated distillation sequences

Optimal process design often requires the solution of mixed integer non-linear programming problems. Optimization procedures must be robust and efficient if they are to be incorporated in automated design systems. For heat integrated separation process design, a natural hybrid evolutionary/local search method with these properties is possible. The method is based on the use of local search methods for the continuous design parameters for the units in the process and the use of an evolutionary optimization procedure for the design of the heat exchanger network. The use of a stochastic method for the heat exchanger network aspect introduces noise in the evaluation of the objective function used by the local search methods. A smoothing procedure has been designed and implemented to improve the efficacy of the hybrid approach. This paper presents the evaluation of a variety of local search methods. It is shown that the Hooke and Jeeves algorithm, combined with a simple genetic algorithm, provides a robust, efficient and effective solution procedure for optimizing heat integrated distillation sequences.

Nonlinear disjunctive programming models for the synthesis of heat integrated distillation sequences

In this paper we present nonlinear optimization models for the optimal synthesis of heat integrated distillation sequences. These nonlinear optimization models can overcome problems with singularities that are encountered in the mixed integer nonlinear programming (MINLP) superstructure optimization of distillation columns with nonlinear short-cut models. The proposed optimization models are obtained from a systematic modeling procedure where generalized disjunctive programming models are derived using the state task network (STN) or state equipment network (SEN) superstructure representations. These models are solved with a modified logic-based outer approximation (OA) algorithm, in which the key item is an effective scheme for initialization for setting up the master problem. For heat integration, a disjunctive mixed integer linear programming (MILP) model based on pinch candidate selection is used that can be readily incorporated into the synthesis models. Numerical results are presented for both the state task network and the state equipment network representations, and for the case of no heat integration and with heat integration. As will be shown, robustness and efficiency of the structural optimization is greatly enhanced.

98/00819 Heuristic approach for the synthesis of heat-integrated distillation sequences

98/00819 Heuristic approach for the synthesis of heat-integrated distillation sequences

Heuristic approach for the synthesis of heat-integrated distillation sequences

A simple heuristic approach is developed for the synthesis of thermally coupled distillation trains. The proposed algorithm consists of seven sequential steps. The heat integration matrix for the synthesis problem is generated with the aid of three heuristic rules for identifying the feasible matches between the condenser and reboiler. The impact of both utility and capital costs on heat integration is considered in the analysis. The effectiveness of the proposed method is demonstrated by two examples. The first example is a synthesis problem concerning a five-component mixture for a sharp separation process, and the second concerns a four-component mixture for a non-sharp separation process. The proposed method yields a high reduction in cost compared with other methods reported in the literature. The method is straightforward to apply by hand and it does not require any mathematical background on computational skills of the user. © 1997 by John Wiley & Sons, Ltd.

Stochastic programming in process synthesis: A two-stage model with MINLP recourse for multiperiod heat-integrated distillation sequences

This paper presents a two-stage stochastic programming approach with MINLP recourse for the synthesis problem of heat integrated distillation sequences that can handle prespecified changes in the composition and/or flowrate of the multicomponent feed to the separation system for a finite number of periods of operation. A new synthesis strategy is proposed that combines the aspects of a superstructure approach with a partitioning of the design variables into two classes: structural and periodic. Structural design variables comprise the fixed elements of a design that are common to all operating conditions, while the periodic design variables are adjustable quantities that can be changed for optimal operation in each period. The synthesis strategy identifies the optimal separation sequence and selection of heat exchanger units that can accommodate the different periods of operation. In addition, for each selected unit, the approach provides simultaneous optimization of the column press ure, reflux ratio, number of trays, diameter and heat integration/exchange matches. The column pressure, reflux, number of trays and diameter are treated explicitly as continuous variables in the model. The mathematical formulation that results is a large-scale mixed-integer nonlinear programming (MINLP) problem. The structure of the problem can be exploited by viewing the multiperiod design problem as a two-stage stochastic programming problem with the feed composition and flowrate as the uncertain parameters. The different periods of operation provide the discretization of the uncertainty and the multiple scenarios of operation have (MINLP) recourse. A nested solution procedure is detailed that combines the Generalized Benders Decomposition and the Outer Approximation/Equality Relaxation algorithms. Emphasis is given to the application of this type of approach to the general synthesis problem and its potential for extension to design problems under uncertainty and/or flexibility requirements. Application of the approach is illustrated through an example problem.

A mixed-integer nonlinear programming formulation for the synthesis of heat-integrated distillation sequences

Sequences of distillation columns are widely employed in chemical plants as the main system for the separation of various multicomponent mixtures into their components. Considerable savings in plant operating costs can often be obtained by adjusting the operating pressures of the columns in a separation sequence so as to allow for heat transfer between the condenser of one column and the reboiler of another. Because of the importance of distillation sequences in the operation of the entire chemical process and the large investment and operating costs represented by them, the synthesis of optimal heat-integrated distillation sequences becomes an important synthesis problem. In this paper, a systematic framework is presented for the synthesis problem of heat-integrated distillation sequences with the column pressures treated as continuous variables for a single multi-component feed of fixed composition. This framework consists of the mathematical formulation of the distillation sequence superstructure as a mixed-integer nonlinear programming MINLP problem. The mathematical formulation features as an objective function, the minimum total annual cost comprised of investment costs for the distillation columns and heat exchangers plus the operating costs based on utility consumption. The heat integration options are incorporated in the proposed formulation through the assignment of integer variables representing the potential condenser-reboiler matches. Solution of this mathematical formulation, which can be obtained automatically using the computer programming procedure APROS provides the optimal distillation sequence and heat integration matches as well as the operating pressures required for each column. The effectiveness of this systematic framework is illustrated with three example problems.

Shortcut evaluation of ΔT and QΔT for the synthesis of heat integrated distillation sequences

AIChE JournalVolume 31, Issue 6 p. 1039-1040 R & D Note Shortcut evaluation of ΔT and QΔT for the synthesis of heat integrated distillation sequences K. Glinos, K. Glinos Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003Search for more papers by this authorM. F. Malone, M. F. Malone Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003Search for more papers by this authorJ. M. Douglas, J. M. Douglas Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003Search for more papers by this author K. Glinos, K. Glinos Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003Search for more papers by this authorM. F. Malone, M. F. Malone Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003Search for more papers by this authorJ. M. Douglas, J. M. Douglas Department of Chemical Engineering, University of Massachusetts, Amherst, MA 01003Search for more papers by this author First published: June 1985 https://doi.org/10.1002/aic.690310622Citations: 6AboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL No abstract is available for this article.Citing Literature Volume31, Issue6June 1985Pages 1039-1040 RelatedInformation