Decision Support for CO2 Capture Process Options under Uncertain Market Conditions using Multi-objective Optimisation

Jiří Jaromír Klemeš, Petar Sabev Varbanov and Peng Yen Liew (Editors) Proceedings of the 24th European Symposium on Computer Aided Process Engineering – ESCAPE 24 June 15-18, 2014, Budapest, Hungary. Copyright © 2014 Elsevier B.V. All rights reserved.

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Select which opmal process configuraon under which condions?

Physical model fuel

Pareto froner

offgas

Obj1

Economic parameters

Impact on Pareto Distribuon soluons funcons

Ranking # of mes in top 5

CO2 capture

Decision criteria

1 2

Obj1

Soluons ranking based on probability → Decision-making support

Mulobjecve opmisaon min fobj(x,z) h(x,z)=0 g(x,z)≤0

CO2

air

Energy integraon model (MILP resoluon)

Economic model & LCA model

3

Obj1

fobj(x,z)

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1210

COE with CO2 tax [$/GJe]

80

upper boundary

70 60

base

50 40 Pre-comb BM Selexol

30 20

Post-comb MEA

lower

10 boundary 0 25

30

35

40

45

50

Pre-comb ATR Selexol

55

60

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1211

100

CO2 capture [%]

80 Postijcomb MEA

60 40 Preijcomb BM Selexol

Preijcomb ATR Selexol

20 0 25

30

35

40

45

50

Energy efficiency [%]

55

60

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CO2 capture [%]

Relative competitiveness

1

100 Post−comb. MEA

90

0.8

80 Pre−comb. ATR Selexol

70

0.6

60 50 40

0.4

30 0.2 0 20

20

Pre−comb. BM Selexol

30

40

50

10 60

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