Process engineering method for
systematically comparing
CO
2
capture options
Presented at
ESCAPE 23
Lappeenranta, Finland
9-12 June 2013
Dr. Laurence TOCK
a,
Prof. François Maréchal
aa
Industrial Process and Energy Systems Engineering
Dual global challenge
Greenhouse gas emissions ↘
Sustainable energy supply
Context
Power Plants CO2 emissions Fossil fuel depletion Alternatives ? Conversion Efficiency ↗ Less C intensive Renewable resourcesWorld CO2 emissions from fuel combustion by sector in 2010 (IEA 2011)
Bridging to the future ?
Carbon capture and storage
CO
2
emissions ↘ & energy supply
Carbon capture and storage (CCS)
1
1.
Capture
CO
2removal from flue gas by
gas separation technologies
2.
Transport
CO
2compression to 110bar
Transport by ship or pipeline
3.
Storage
Geological formations
Ocean
Mineral carbonation
Context
1. CO2 capture 2. Transport 3. Storage Ocean Saline aquifers Geological formations Coal beds EOR Mineral carbonation
CO
2
capture concepts
Context
•
Post-combustion
End of pipe CO
2removal
•
Oxy-fuel combustion
Pure O
2combustion
•
Pre-combustion
Syngas intermediate, H
2route
Coal Gas Biomass Power & Heat Air Exhaust gas CO2 separation N2 O2 H2O CO2 storage CO 2 Coal Gas Biomass Power & Heat CO2 separation H2O CO2 H2O CO2 storage CO 2 O 2 Air separation N 2 Air Power & Heat Air N2, O2, H2O H2rich fuel CO2 storage CO 2 CO2 separation Syngas H 2 +CO Gas Reforming WGS Coal Biomass Gasification Air/O2 Steam
CO
2
separation technologies
Chemical absorption
Physical absorption
Physical adsorption
Membrane processes
Context
Q+
Drawbacks of CO
2
capture & compression
Large energy requirement:
Up to
10%-pts efficiency penalty
(~2%-pts from CO
2compression)
Additional investment:
20-30%
production cost increase
Challenge:
Competitive power plants with CCS
Context
Energy
Systems
CO
2↘
Costs ↘
Efficiency ↗
Operation ?
Systematic optimisation of CO
2
capture processes
Thermo
-environomic optimisation methodology
2
Thermodynamic
,
economic
& environmental
aspects
Trade-off between
efficiency
,
costs
and
CO
2capture rate
!
Assessment of fuel decarbonisation competitiveness
Process
Resources
Technologies
Products
Services
Process configuration & integration Energy efficiency Costs Environmental impactObjective
Thermo
-
environ
omic
optimisation methodology
Uniform and systematic platform
3
Methodology
3Tock et al. PSE 2012, Bolliger et al. 2009/2010, Gassner et al. 2009, Gerber et al. 2011
Global problem Multi-objective optimisation min fobj(x,z) h(x,z)=0 g(x,z)≤0 xiL≤x i ≤ xiU fobj(x,z) Pareto set Obj1 Obj2 Physical model
Energy integration model
(MILP resolution)
Economic model & LCA model
Model preprocessing
Model (external software) Model post-processing
Process models
Methodology
Global problem
Physical model
Model preprocessing
Model (external software)
Model post-processing
xi
Process units operation
Physical & chemical
transformations
Heat transfer
requirement
Coherent representation
of existing technology
•
Accurate and flexible
Superstructure of candidate technologies
Conceptual process design of fuel decarbonisation
Methodology
Post-combustion Pre-combustion CO2stored 110bar CO2stored 110barQ+ LP Q+reheat Q+ richheat Q -leanheat Q-ABS Q -HP NABS DABS Massf H2O Trichheat Spilt frac Treheat Pratio=HP/LP Rich_load NHP DHP NLP DLP LP Lean_load solvent MEA %
Process models
Process simulation:
Connection between different flowsheeting software !
Methodology
Global problem Physical model Wtot fAir fNG fsyngas fexhaust fH2O q1 q2 q3 Physical modelAspen Plus: CO2 capture model
Belsim Vali:
Generic reheat GT model
Belsim Vali: CO2 compression model
W1 W2 q1 q2 q3 q4 fCO2 fH2O fin T, P, Xi, MFG T, P, Xi, MOG Model preprocessing
Model (external software)
Model post-processing
Energy integration: Pinch analysis
Methodology
Global problem
Physical model
Model preprocessing
Model (external software)
Model post-processing
xi
Optimal integration of
process units
Maximal heat recovery
4
Optimal combined heat &
power production
Waste heat valorisation
Resolution
Linear programming
minimising operating cost
Energy integration model
(MILP resolution)
Performance evaluation
Methodology
Global problem
Physical model
Model preprocessing
Model (external software)
Model post-processing xi
Economic performance
5 Equipment sizing
Capital investment
estimation
Production costs
Energy integration model
(MILP resolution)
5Turton 2009, Ulrich 2003
Economic model & LCA model
( , , , ,...) size f T P m V ( , , , ,...) GR C f T P material size , P I d M OL UT RM C C C C C C
Performance evaluation
Methodology
Global problem
Physical model
Model preprocessing
Model (external software)
Model post-processing
xi
Economic performance
5
Uniform approach
Uniform assumptions
Energy integration model
(MILP resolution)
Economic model & LCA model
Performance evaluation
Methodology
Global problem
Physical model
Model preprocessing
Model (external software)
Model post-processing
xi
Environmental impacts
6
Life cycle assessment (LCA)
Life cycle inventory considering
specific operating conditions
Energy integration model
(MILP resolution)
6Gerber et al. 2011
Economic model & LCA model
Waste Emissions Byproducts
Energy Materials Infrastructure
Feedstock production Feedstock transport Conversion H2 prod. CO2 storage H2 rich fuel product Heat & power conversion Upgrading Capture CO2RM CO2Pr CO2Emit CO2Seq.
Performance evaluation
Methodology
Global problem
Physical model
Model preprocessing
Model (external software)
Model post-processing
xi
Performance indicators
identify optimal process design
Energy efficiency
CO
2capture rate
CO
2avoidance costs
Competing indicators
Trade-offs assessment !
Energy integration model
(MILP resolution)
Economic model & LCA model
E
m
Δh
E
m
Δh
ε
feed 0 feed fuel 0 out fuel, tot
captured in C 2 C n CO capture [%] 100 n 2 emit,ref 2 emit,CC Pcc Pref CO2,avoided CO COC
-C
$/t
=
m
-m
Multi-objective optimisation
Methodology
Global problem Multi-objective optimisation min fobj(x,z) h(x,z)=0 g(x,z)≤0 xiL≤x i ≤ xiU fobj(x,z) Pareto set Obj1 Obj2 Physical modelEnergy integration model
(MILP resolution)
Economic model & LCA model
Model preprocessing
Model (external software) Model post-processing
MINL problem
7
Evolutionary algorithm
Optimal values of
decision variables
Pareto optimal frontier
Detailed modelling
Chemical absorption
Physical absorption
Decision variables
Operating conditions
(T, P, S/C,…)
, cogeneration system
CO
2
capture optimisation
Post-combustion Pre-combustion CO2stored 110bar CO2stored 110bar
Multi-criteria comparison
Thermo-dynamic
Environmental
Economic
Sensitivity to resource price, carbon tax, etc.
CO
2
capture optimisation
Post-combustion Pre-combustion CO2stored 110bar CO2stored 110bar
Multi-objective optimisation
Maximisation of
energy efficiency
Maximisation of CO
2
capture rate
CO
2
capture optimisation
E
m
Δh
E
m
Δh
ε
feed 0 feed fuel 0 out fuel, tot
captured in C 2 C n CO capture [%] 100 n Post-combustion Pre-combustion CO2stored 110bar CO2stored 110bar
Pareto-optimal frontiers
CO
2
capture optimisation
Natural gas
Biomass Biomass
Natural gas
CO
2capture ↗
→
ε
tot↘
&
COE ↗
Energy & cost penalty of CO
2capture and compression
Economic scenario base: 9.7$/GJres, 7500h/y, 25y, 6%ir
CO
2
capture energy and cost penalty
Different process configurations
Natural gas fed processes 90% CO
2capture, biomass 60% capture
Competition between post- and pre-combustion
CO
2
capture options comparison
CO
2
capture energy and cost penalty
Economic competitiveness highly influenced by
Resource price & carbon tax
CO
2
capture options comparison
Economic conditions sensitivity analyses
CO
2
capture options comparison
62$/tCO2
50$/tCO2
Natural gas price influence
Carbon tax 35$/tCO2
Carbon tax influence
Resource price 9.7$/GJNG, 5$/GJBM
COE strongly dependent
on resource price!
With increasing carbon tax
CO
2capture becomes
competitive!
Economic scenario base: 9.7$/GJres, 7500h/y, 25y, 6%ir
6$/GJNG
Economic competitiveness of process configurations
Influenced by economic conditions
CO
2
capture options comparison
low:14.2$/GJres, 20$/tCO2, 4500h/y, 15y, 4%ir base: 9.7$/GJres, 35$/tCO2, 7500h/y, 25y, 6%ir high: 5.5$/GJ , 55$/t , 8200h/y, 30y, 8%ir 5.5$/GJres 55$/tCO2
.
.
εtot 57.5% CO2 capt. 10% 14.2$/GJres 20$/tCO2.
εtot 51% CO2 capt. 85%
Optimal process
design ?
Most economically competitive process configurations
CO
2
capture options comparison
CO
2capture penalty
•
Efficiency ↘
: 6-10%-pts
(CO
2compression ~2%-pts)
•
COE ↗
: 20-25%
Best performing process
•
Efficiency
: Nat gas. pre-comb.
•
Economic
: Nat gas. post-comb.
•
Environmental
: Biomass pre-comb.
Competition between processes
and objectives!
System NGCC Post-comb ATR BM
Performance no CC MEA Selexol Selexol
Feed [MWth] 559 582 725 380
CO2 capture [%] 0 82.9 78.6 69.9
εtot [%] 58.75 50.6 53.5 35.4
Net electricity [MWe] 328 295 383 135
[kgCO2, local/GJe] 105 13.9 22.2 -198.1
COE incl. tax[$/GJe] 18.2-28.8 9-40 12.8-42 15-69
Avoid. Costs incl. tax
Most economically competitive process configurations
Choice of optimal process configuration is defined by
production scope and priorities given to the different
thermo-environomic criteria!
Decision-making
CO
2capture penalty
•
Efficiency ↘
: 6-10%-pts
(CO
2compression ~2%-pts)
•
COE ↗
: 20-25%
Best performing process
•
Efficiency
: Nat gas. pre-comb.
•
Economic
: Nat gas. post-comb.
•
Environmental
: Biomass pre-comb.
System NGCC Post-comb ATR BM
Performance no CC MEA Selexol Selexol
Feed [MWth] 559 582 725 380
CO2 capture [%] 0 82.9 78.6 69.9
εtot [%] 58.75 50.6 53.5 35.4
Net electricity [MWe] 328 295 383 135
[kgCO2, local/GJe] 105 13.9 22.2 -198.1
COE incl. tax[$/GJe] 18.2-28.8 9-40 12.8-42 15-69
Avoid. Costs incl. tax
Quantitative & consistent evaluation of CO
2
capture
Systematic methodology for the
thermo
-environomic
comparison and optimisation
Flowsheeting
Energy integration
Performance evaluation (
efficiency
,
cost
,
LCIA
)
Multi-objective optimisation
Powerful tool to assess process competitiveness
Conclusions
Energy & cost penalty of CO
2
capture
Efficiency ↘
: 6-10%-pts
COE ↗
: 20-25%
COE with carbon tax → competitive
Competition between the different processes!
Post-combustion CO
2capture in NGCC plants yields
best
economic performance
for 70-85% capture
Pre-combustion CO
2capture in natural gas fired
power plants highest
energy efficiency
CO
2capture in biomass based power plants lowest
environmental impacts
Conclusions
Competitiveness on energy market depends strongly on resource
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and power production, PhD Thesis N°5655, EPFL, Lausanne, 2013
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