design and synthesis of complex column networks …

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Feasible Case MinBPD = 0

DESIGN AND SYNTHESIS OF COMPLEX COLUMN NETWORKS WITH GLOBAL FEASIBILITY TESTGerardo J. Ruiz, Seon B. Kim, and Andreas A. Linninger

Laboratory for Product and Process Design, Departments of Chemical and Bio-Engineering, University of Illinois at Chicago, Chicago, IL 60607, USA

General on Separations (02H00), AIChE Annual Meeting, Nashville, TN, Nov 9, 2009Poster No. 335o

Case Study 2 - Initialization of Complex Distillation Networks with AspenPlus Simulator

Motivation and Objectives

Rigorous Feasibility Test Reduced Search Space

Methodology - Complex Column Network Synthesis

Conclusions

ReferencesAgrawal, R. (2003). "Synthesis of multicomponent distillation column configurations." AIChE J 49(2): 379-401.Tapp, M., S.T. Holland, D. Hildebrandt, and D. Glasser, Column Profile Maps. 1. Derivation and

Interpretation. I&EC Research, 2004. 43(2): p. 364-374. Zhang, L. and A. A. Linninger (2004). "Temperature collocation algorithm for fast and robust distillation design." I&EC

Research 43(12): 3163-3182.Zhang, L. and A. A. Linninger (2006). "Towards computer-aided separation synthesis." AIChE J 52(4): 1392-1409.

Acknowledgements•DOE Grant: DE-FG36-06GO16104•Dr. Rakesh Agrawal (Purdue University)•Dr. Chau-Chyun Chen (Aspen Tech.)

MotivationDistillation occupies in chemical process:

�40-70% of capital and operating costs�60% of the total process energy�4% of total energy consumption in United States�Atmospheric carbon emissions

There is a need for a redefinition of the design objectives for industrial separations with a new focus on energy conservation and the emission reduction using complex column configurations have the potential of achieving up to 70% energy savings over simple column networks

• Temperature collocation and minimum bubble point distance algorithm were effective to find a feasible separation by intercepting profiles.

• The first case study demonstrates the potential to save 72% in energy using a complex column network compared to the simple column network.

• The second case study demonstrates the current state of the art of separation synthesis in conjunction with computer simulations to fully integrate complex separation networks.

• The seamless integration of rigorous flowsheet simulators to validate the predictive results of our scientific method was demonstrated.

A quaternary mixture of pentane, hexane, heptane, and octane was studied. In the complex network, it uses two simple columns for pre-fraction to complex column. As a result, the best energy efficient complex column network saves up to 72% of the operating cost in terms of vapor flowrate.

Bubble Point Temperature Distance map shows the minimum composition distance between two adjacent sections. The minimum bubble point distance (BPD) of 10-8 is localized at r= 2.35, xD3=0.0081 and BPT= 72.6 �C.

Basic complex column configurations

Generic Structure SynthesisNetwork Task Optimization

Using Difference Point Equations

Find Feasibility of Two Column Sections

Considering Operating and Capital Cost

Obtain Optimal Design

Level I: Find all possible basics configurations

Mixed IntegerLinear Program

Basic Config.

Level II: Identify the feasible complex column

Pinch Point

Feasible

Supply

Design Specification

Temperature

BPD

Level III : Obtain optimal designs

Input Specification

OutputComp. profile

OutputFlow ratetray#

According to the general definition of the minimum bubble point distance approach, a complex column k is feasible if and only if the sum of all minimum profile distances of any pair of equivalent rectifying, r, and stripping, s, column sections is within a small tolerance of zero (�) as in expression

AspenPlus Simulation of Composition and Temperature Profiles

Temperature Collocation Composition Profiles

Global Design Procedure

Basic Complex Configuration: Quaternary System

Temperature Collocation of a General Column Section

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Implicit Differentiation

Case Study 1 – Complex Column Network for Quaternary Mixtures Separation

Basic Structure

Each random initial guess for integer variables, x, will generate one possible structure

Feasibility test

High performance Inverse problem

2min ix

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K individuals

Population

MASTER

•Dr. Angelo Lucia (University of Rhode Island)•Dr. Diane Hildebrandt (University of the Witwatersrand)

40 60 80 100 1200

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Optimal operating conditions for 9 selected Networks

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Inverse Design of Distillation Column

Column I Column II Column III

Unit (kmol/h) Net. 1 Net. 2 Net. 3 Net. 4 Net. 5 Net. 6 Net. 7 Net. 8 Net. 9

Column I 74.99 79.99 186.87 114.81 186.87 156.56 156.56 478.08 186.87

Column II 78.07 57.36 46.73 63.34 60.60 66.44 281.14 63.70 472.62

Column III 70.34 64.66 48.99 86.30 62.68 76.09 62.681 72.50 63.27

Total 223.41 202.02 282.59 264.45 310.15 299.09 500.38 614.28 722.76

Complex Network

Simple Network

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• Starting with the desired design specification of product purity requires that each column of the network is feasible

• Feasible design – Intersection of profiles of both adjacent sections

• Profile Intersection Index - bubble point distance (BPD)

Objectives�Develop computer-aided systematic design procedures to prevent numerical failuresassociated with the extraordinary sensitivity of column profile calculations�Massive size reductions enabled by a new column profile computation algorithm called Temperature Collocation�Synthesize separation networks with realistic column profiles�Realizable column profiles validated with industrially accepted simulation software such as AspenPlus

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