Superstructure-based Simultaneous Optimization of Heat and Water Integration

Linlin Yang Advisor: Ignacio E. Grossmann

Department of Chemical Engineering Carnegie Mellon University

Pittsburgh, PA 15213

March 6th , 2011

Motivation

Water and energy are important resources in the process industries

Water issues Energy issues

Rapidly growing demand for freshwater Steadily growing demand for energy

All regions of the United States are vulnerable to water shortages

All regions of the United States are vulnerable to energy shortages

Environmental regulations for water discharge may require more energy

Meeting power plant emission standards requires more water

Need to lower intensity of water use Need to lower intensity of energy use

NETL - Technology Roadmap & Program Plan (2009) 2

Goal

To determine the flowsheet configuration and operating conditions that achieves optimal water and energy use to minimize cost

Two essential steps: 1.  Determine the minimum freshwater flowrate (target) required for a

given set of water-using units   Challenges: 1.  Multi-contaminant water stream integration 2.  Realistic wastewater system

2.  Perform simultaneous optimization on heat and water integration of a process flowsheet

  Note: only process flowsheet and HENS optimization has been performed (Duran and Grossmann, 1986)

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Advantage

  Captures tradeoffs among raw material, investment cost and operating cost

Cost

Overall conversion

raw material cost

Energy &water cost (sequential)

Total cost (sequential)

Energy &water cost (simultaneous)

Why simultaneous optimization?

4

Total cost (simultaneous)

Targeting approach

Determine a performance index ahead of detailed design of system configuration

Examples:   Heat-exchanger network: heating and cooling utilities   Water network: freshwater flowrate   Distillation sequencing: recovery ratio

Advantages:   Avoiding combinatorial problems   Reduces problem dimensionality to a manageable size   Offers insights into the system performance and characteristics

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Levels of model complexity

Aggregated model (LP/NLP/MILP)  e.g. Utility level

  Transshipment model HENS/MENS (Papoulias, Grossmann, 1983; El-Halwagi, Maniousiouthakis, 1989)

  Distillation Sequences (Papalexandri, Pistikopoulos, 1996; Caballero, Grossmann, 1999)

  Reactor networks (Balakrishna, Biegler, 1992; Kravanja, Bedenik, Pahor, 2003)

Short-cut model (NLP/MINLP)  e.g. Cost optimization

  HENS: (Yee at al., 1990; Ciric and Floudas, 1991)   Distillation sequences: (Aggrawal, and Floudas, 1990;

Yeomans and Grossmann, 1998)   Process flowsheets: (Kocis and Grossmann, 1989; Türkay

and Grossmann, 1996; Lee et al, 2003)

Rigorous model (NLP/MINLP)  e.g. Unit performance

  Synthesis of distillation sequences Bauer, Stichlmair (1996,1998), Smith and Pantelides (1995), Yeomans, Grossmann (2000), Barttfeld, Aguirre, Grossmann (2004), Caballero, Milan-Yanez ,Grossmann (2005)

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Minimum utility requirement

Not all models require a great amount of details!

Tubular Reactor

N2 H2

NH3

Purge

Multibed Reactor

Flash

Absorber

Membrane

Flash Condensation

Distillation

NH3

Water

Water

Distillation

Simultaneous flowsheet, heat, and water integration

7 Aggregated (LP)

Shortcut (MINLP)

Rigorous (MINLP)

Flowsheet

HEN

Water network

Path 1: Optimal solution (simultaneous optimization; MINLP)

Path 2: Can we avoid solving that MINLP but still get to the same optimal solution?

Path 0: Unrealistic

HEAT TARGETING

Proposed strategy – simultaneous integration

PROCESS FLOWSHEET

WATER TARGETING

Cold streams

Hot streams

MUC*

*MUC – minimum utility consumption

Hot utility

Cold utility

MUC*

Water streams

Wastewater

Freshwater

Utility networks

PROCESS STRUCTURE

WN STRUCTURE HEN STRUCTURE

PROCESS FLOWSHEET WITH HEN AND WN 8

Heat Integration – Targeting strategy

9

H1‐C 1

H1‐C 2

H2‐C 1

H2‐C 2

H1‐C 1

H1‐C 2

H2‐C 1

H2‐C 2

S tage 1 S tage 2

Temperature location k=1

Temperature location k=2

Temperature location k=3

s1

s 2

W1

W2

C 1

C 2

H1

H2

tC 1,1 tC 1,2 tC 1,3

tC 2,1 tC 2,2 tC 2,3

tH1,1 tH1,2 tH1,3

tH2,1 tH2,2 tH2,3

C oolersHeaters

Pinch Superstructure

- Linear formulation - Determines the minimum heating and

cooling requirement (targets)

-  Difficult to solve (MINLP) -  Determines the network structure

Conventional Water Network

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Ahmetović and Grossmann(2009)

No reuse

Freshwater 

Boiler Feedwater treatment

Steam System

Wastewater Boiler Blowdown 

Steam Condensate  Losses 

Boiler 

Water-using unit 1

Water-using unit 2

Water-using unit 3

Raw Water  Raw Water Treatment

Wastewater 

U"lity uses 

Cooling  Tower 

Cooling Tower Blowdown 

Water Loss by Evapora2on 

Discharge 

Wastewater Treatment

Storm Water 

Process uses 

Other Uses (Housekeeping)

Wastewater 

No regeneration

reuse

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Pinch

Process

Process

Treatment

Treatment

Freshwater

Discharge

Pinch Superstructure

-  Linear formulation -  Valid only for single-contaminant system

-  Nonlinear network formulation -  Valid for multiple contaminants

Water Integration – Targeting strategy

Proposed work - freshwater targeting

Relax nonlinear WN formulation into linear formulation   Necessary condition of optimality (Savelski and Bagajewicz,2003)

“If a system is optimum, freshwater user processes have at least one component reaching its maximum concentration.”

  The proposed LP model predicts the EXACT target for minimum freshwater consumption of a set of water-using processes   Does not provide the network structure   Accounts for process units that have water loss / gain   No treatment unit included

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Process unit 1

Process unit 2

Process unit 3

Freshwater Wastewater

Simultaneous optimization - example

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+ cooling system + steam system Freshwater requirement

Heating requirement

Cooling requirement

methanol synthesis from syngas

Duran & Grossmann (1986); Turkay & Grossmann (1998)

Preliminary results – sequential vs. simultaneous comparison

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SEQUENTIAL  SIMULTANEOUS Profit                      (1000 $/yr)  62,695  73,416 Investment cost   (1000 $)  1,891  1,174 Opera"ng costs and parameters    

electricity (KW)  6.59  1.84 freshwater (kmol/s)  202.4  162.5 

heaKng uKlity (10^9 KJ/yr)  0.29  0 cooling uKlity (10^9 KJ/yr)  67.3  72.7 

Steam generated (10^9 kJ/yr)  2448  1965 overall conversion  0.23  0.29 

Material flowrate (10^6 kmol/yr)    feedstock  48.04  37.13 product   10.89  10.89 

byproduct  9.95  4.41 

17% improvement Solved with BARON

Conclusion and future work

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Conclusions:   Developed water targeting formulation for water using units excluding

treatment units   Developed targeting strategy for solving simultaneous flowsheet, heat and

water integration   Captures tradeoffs between capital and operating costs

Future work:   Water network

  Non-isothermal water network   Include wastewater treatment units

Thank you!

Heat Integration for PC Power Plant with CO2 Capture

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Question: how to integrate the system to minimize power loss due to CO2 capture?

Steam cycle

Sorbent cycle

CO2 compression

NETL CCSI project

Heat Integration for PC Power Plant with CO2 Capture

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Steam cycle

Sorbent cycle

CO2 compression

0

100

200

300

400

500

600

700

800

900

1000

0 200 400 600 800 1000 1200 1400

Temperature(°F)

Heat(MMBtu/hr)

hotcurvecoldcurve

condensedsteam

steamextraction

CO2compression

stripperreboiler

condensedsteam

HRAT=18°F

T-Q Curve (original design)

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T-Q Curve (optimized design)

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0

100

200

300

400

500

600

700

800

900

1000

0 200 400 600 800 1000 1200

Temperature(°F)

Heat(MMBtu/hr)

hotcurve

coldcurve

condensedsteam

steamextraction

CO2compression

stripperreboiler

condensedsteam

HRAT=18°F

H1

H2

H3

H4

H5

C1

C2

C3

262.2 92.7

218

723.5

124.6

724.5

148.7

488.4

123.6

723.5

180

488.4

219

128.4

94.4

218

179.4

471.4 144.6

163 146.7

184.1

109.7

165.7

H1 - CO2 compression streams H2 - stripper to absorber H3 – condensed steam extract IP-02 H4 - stripper condenser H5 – condensing steam extract IP-02

C1 - absorber to stripper C2 – boiler feed water C3 - stripper reboiler

Heat Exchange Network

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Reference

Heat integration: Duran, M. A.; Grossmann, I. E. Simultaneous Optimization and Heat Integration of Chemical Processes. AIChE J. 1986, 32 (1), 123-138. Floudas, C.A. Nonlinear and Mixed-Integer Optimization: Fundamentals and Applications. Oxford University Press, 1995. Furman, K.C.; Sahinidis, N. A Critical Review and Annotated Bibliography for Heat Exchanger Network Synthesis in the 20th Century. Ind. Eng. Chem.

Res. 2002, 41, 2335-2370. Gundersen, T.; Naess, L. The Synthesis of Cost Optimal Heat Exchanger Networks. Comput. Chem. Eng. 1988, 12 (6), 503-530. Ježowski, J. Heat Exchanger Network Grassroot and Retrofit Design. The Review of the State-of-the-Art: Part I. Heat Exchanger Network Targeting

and Insight Based Methods of Synthesis. Hung. J. Ind. Chem. 1994, 22, 279-294. Papoulias, S. A.; Grossmann, I. E. A Structural Optimization Approach in Process SynthesissII. Heat Recovery Networks. Comput. Chem. Eng. 1983, 7

(6), 707-721.

Water integration: Ahmetović, E.; Grossmann, I. E. Global superstructure optimization for the design of integrated process water networks. AIChE Journal. 2010 Ahmetović, E.; Martín, M.; Grossmann, I.E. Optimization of Energy and Water Consumption in Corn-Based Ethanol Plants. Ind. Eng. Chem. Res. 2010. Bagajewicz, M.J. A review of recent design procedures for water networks in refineries and process plants.Comput.Chem. Eng.2000,24,2093-2113. Foo, D.C.Y. State-of-the-art review of pinch analysis techniques for water network synthesis. Ind. Eng. Chem. Res. 2009, 48, 5125-5159. Ježowski , J. Review of Water Network Design Methods with Literature Annotations. Ind. Eng. Chem. Res. 2010, 49, 4475–4516. Karuppiah, R.; Grossmann, I. E. Global optimization for the synthesis of integrated water systems in chemical processes. Comput. Chem. Eng. 2006,

30, 650-673. Mann JG, Liu YA. Industrial Water Reuse and Wastewater Minimization. New York: McGraw-Hill, 1999. Savelski, M. J.; Bagajewicz, M. J. On the necessary conditions of optimality of water utilization systems in process plants with multiple contaminants.

Chem. Eng. Sci. 2003, 58 (23-24), 5349-5362. Wang, Y.-P.; Smith, R. Wastewater minimization. Chem. Eng. Sci. 1994, 49 (7), 981-1006.

Others: NETL. EXISTING PLANTS PROGRAM: ENERGY – WATER R&D Technology Roadmap & Program Plan. 2009. Turkay, M.; Grossmann, I.E. Structural flowsheet optimization with complex investment cost functions. Comput. Chem. Eng. 1998, 22, 673-686.

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NETL – “Water Requirements for Existing and Emerging Thermoelectric Plant Technologies “

Water Usage in PC Power Plant

Water consumption

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Water network – problem statement

Given   A set of freshwater sources with/without contaminants   A set of water-using operations units and their inlet/outlet maximum

concentration level for contaminants   A set of wastewater treatment units   Maximum discharge contaminant concentrations

Determine   Optimal water network

Minimize   Freshwater consumption   Annual cost of water network

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Water targeting – pinch method for single contaminant system

Past works   El-Halwagi and Manousiouthakis (1989)   Wang and Smith (1994)

Comparison with heat pinch analysis Similarities:   Heat pinch: heat load

Water pinch: mass load   Heat pinch: Heating/cooling utilities

Water pinch: freshwater/wastewater flowrates Differences:   Heat pinch: transfers heat only   Water pinch: transfers MULTIPLE contaminants

  Solution not rigorous

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Need to find other method for freshwater targeting

Pinch

WN – superstructure-based method

Karuppiah and G. (2006); Ahmetović and G. (2009)   Integrated water network with reuse, recycle, and regeneration schemes   Constraints and objective functions are nonconvex   Can determine global optimal solution with branch and bound algorithm

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Process Unit

Process Unit

Treatment Unit

Treatment Unit

Freshwater

Discharge

Contaminants

Contaminants

Splitter

Mixer

Contaminants

Contaminants

HEN – problem statement

Given   A set of hot process streams to be cooled   A set of cold process streams to be heated   Available utilities and their costs   Heat recovery approach temperature (HRAT)

Determine   Network configuration

Minimize   Heating utility required   Cooling utility required   Investment cost of heat exchanger units

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HEN – stage-wise superstructure

H1‐C 1

H1‐C 2

H2‐C 1

H2‐C 2

H1‐C 1

H1‐C 2

H2‐C 1

H2‐C 2

S tage 1 S tage 2

Temperature location k=1

Temperature location k=2

Temperature location k=3

s1

s 2

W1

W2

C 1

C 2

H1

H2

tC 1,1 tC 1,2 tC 1,3

tC 2,1 tC 2,2 tC 2,3

tH1,1 tH1,2 tH1,3

tH2,1 tH2,2 tH2,3

C oolersHeatersYee and Grossmann(1990)

Objective Function   Min capital and utility costs

Constraints   Overall energy balance for

each stream   Energy balance for each stage   Heating and cooling duties   Logical constraints   Temperatures differences

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T-Q curve: Hohmann (1971); Linnhoff and Flower (1978)

Heating and cooling target – pinch analysis

Floudas (1995)

LP transshipment: Fixed F, T Papoulias and Grossmann (1983)

Pinch location method: Variable F, T Duran & Grossmann (1986)

900 kW

750 kW

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Pinch

0),,( ≤CHHEN QQug