Reforming of Biogas: optimal conditions through
thermodynamics and MCDM analysis
Fabio De Rosa
School of Chemistry and Chemical Engineering, CenTACat, Queen’s
University Belfast
Supervisors : Professor David Rooney, Dr Beatrice Smyth, Dr Geoffrey
McCullough, Dr Alex Goguet
Biogas exploitation roadmap
Biogas
Combustion
ICE (heat & power)
Upgrading
- CH4 compression
- CH4 liquefaction
Surplus
energy
exploitation
Sabatier reaction
Liquid fuel
production
Gasoline, diesel, methanol
Hydrogen
production
Fuel cells (heat & power)
Reforming technologies to syngas (CO + H2)
Biogas exploitation roadmap – focus on reforming
Main target :
Find the “best way” to
reformate Biogas into Syngas
Biogas
Liquid fuel
production
Hydrogen
production
Reforming technologies to syngas (CO + H2)
Reforming technologies
Biogas as a feedstock
Technology
Biogas dry-oxidative reforming (BG DOR)
Biogas dry-oxidative reforming (autothermal) (BG DOR (ATR))
Biogas steam reforming (BG SR)
Biogas steam reforming (autothermal) (BG SR(ATR))
Biogas tri-reforming (BG TRI-R)
Biogas tri-reforming (autothermal) (BG TRI-R(ATR))
Feed
CH4, CO2, O2
CH4, CO2, O2
CH4, CO2, H2O
CH4, CO2, H2O, O2
CH4, CO2, H2O, O2
CH4, CO2, H2O, O2
Technology
BG DOR
BG DOR(ATR)
BG S R
BG S R(ATR)
BG TRI-R
•
•
•
CH4/CO 2/H2O/O 2
1/0.67/0/0.1
1/0.67/0/0.25
1/0.67/0/0.5
1/0.67/0/0.75
1/0.67/0/0.0015-0.8933
1/0.67/1/0
1/0.67/2/0
1/0.67/3/0
1/0.67/1/0-1.0725
1/0.67/2/0-1.1755
1/0.67/3/0-1.2815
1/0.67/1/0.1
1/0.67/1/0.25
1/0.67/1/0.5
1/0.67/1/0.75
1/0.67/2/0.1
8 reforming technologies;
32 reforming processes (feed sensitivity);
Fixed CH4/CO2=1.5 (60% CH4, 40% CO2).
Computer-aided
simulations
Technology (ctd)
BG TRI-R(ATR)
METHANE S R
METHANE S R(ATR)
CH4/CO 2/H2O/O 2 (ctd)
1/0.67/2/0.25
1/0.67/2/0.5
1/0.67/2/0.75
1/0.67/3/0.1
1/0.67/3/0.25
1/0.67/3/0.5
1/0.67/3/0.75
1/0.67/1/0-0.6839
1/0.67/2/0-0.7144
1/0.67/3/0-0.7471
1/0/1/0
1/0/2/0
1/0/3/0
1/0/1/0-0.6191
1/0/2/0-0.6524
1/0/3/0-0.6874
reference
Reforming technologies under exam
Relevant criteria for each process:
- T (˚C) = operative temperature of the reactor;
- yCH4 = molar fraction of CH4 unconverted;
- yCO2 = molar fraction of CO2 unconverted;
- yCO = molar fraction of CO produced;
- yH2 = molar fraction of H2 produced;
- yCOKE = molar fraction of C formed;
- η (%) = LHV-based thermal efficiency;
- Heat (KW) = thermal energy to supply to the system.
Step 1 - ASPEN Plus thermodynamic simulations
Ein
-
Eout
Advanced System for Process Engineering (ASPEN);
Ideal separation units (S);
Heat exchangers and mixers (H, M);
RGibbs reactor (R) (Gibbs free energy minimization);
Peng-Robinson EoS.
Methane Steam Reforming
1 mol/s Biogas (60% CH4, 40% CO2), P=1 bar, T=200-1200˚C, ΔT≈35˚C (30 alternatives)
Step 1 - ASPEN Plus thermodynamic simulations
Methane Steam Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0/1/0
0.8
0.7
Molar fraction at the outlet (y)
0.6
0.5
yCH4
yCO2
0.4
yH2O
yCO
0.3
yH2
yCOKE
0.2
0.1
0
200
300
400
500
600
700
T (˚C)
800
900
1000
1100
1200
Step 1 - ASPEN Plus thermodynamic simulations
Methane Steam Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0/1/0
100
300
90
250
80
200
70
150
%
100
50
50
40
0
30
-50
20
-100
10
0
200
300
400
500
600
700
T (˚C)
800
900
1000
1100
-150
1200
Heat (KW)
60
xCH4
xCO2
η (%)
Heat (KW)
Step 1 - ASPEN Plus thermodynamic simulations
1 mol/s Biogas (60% CH4, 40% CO2), P=1 bar, T=200-1200˚C, ΔT≈35˚C (30 alternatives)
Molar fraction at the outlet (y)
0.8
0.7
0.6
yCH4
0.5
yCO2
0.4
yH2O
0.3
yCO
0.2
yH2
0.1
yCOKE
0
200
400
600
800
1000
1200
T (˚C)
(30 x 8) matrix
Step 1 - ASPEN Plus thermodynamic simulations
Target:
Find a trade-off between cost (T, yCH4, yCO2, yCOKE, Heat)
and benefit (yCO, yH2, η) criteria:
Multi Criteria Decision Making
(MCDM) techniques
(30 x 8) matrix
Step 2 – MCDM techniques: TOPSIS method
Technique for Order Preference by Similarity to the Ideal Solution (goal-based decision-making technique);
It individuates the closest alternatives to the positive-ideal solution (PIS) and the negative-ideal solution (NIS);
PIS = maximizes all the benefit criteria (yH2, yCO, η), minimizing the cost ones (T, yCH4, yCO2, yCOKE, Heat);
Alternatives are ranked according to the Closeness to the PIS, C*(C*(PIS)=1, C*(NIS)=0);
It is rationable and understandable;
The method needs information about the relative importance of the criteria under exam (weights)
Example: Biogas Steam Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0/1/0
0.3
0.25
0.2
How do we
choose weights?
0.15
0.1
0.05
0
yCOKE yCH4 yCO2
Criterion 2 (increasing preference)
0.35
yCO
Heat
(KW)
NIS
η (%)
Closeness to the ideal solution (C*)
1
Weight
•
•
•
•
•
•
PIS
0.9
0.8
0.7
0.6
98%
Tolerance
on C*max
0.5
0.4Alternative 1
0.3
0.2
0.1
0
yH2
T (˚C)
200
400
600
800
T (˚C)
Criterion 1 (increasing preference)
1000
1200
Step 2 – MCDM techniques: entropy method
•
•
•
Used to determine the objective weights of the indexes for MCDM problems ;
It measures the quantity of useful information provided by data itself ;
If the data distribution is narrow the entropy is small, the considered criterion provides more useful information and
the corresponding weight should be set high, compared to another criterion with a broader distribution.
Example: Biogas Dry-Oxidative Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0.67/0/x
0.8
0.14
0.7
0.12
0.6
0.1
0.08
Weight
0.5
O2/CH4=0.1
0.06
0.4
O2/CH4=0.25
0.04
0.3
O2/CH4=0.5
0.02
O2/CH4=0.75
0.2
O2/CH4=0.1
O2/CH4=0.25
O2/CH4=0.5
O2/CH4=0.75
0
200
700
1200
0.1
0
T (°C)
yCH4
yCO2
yCO
yH2
yCOKE
η (%)
Heat
(KW)
• yCOKE decreasing
• WeightyCOKE increasing
Step 3 – Proposed method
Thermodynamic
…
Process 32
ASPEN Plus
Process 1
32 matrixes
(30 x 8)
Raw Data Matrix (960 x 8)
(T, yCH4, yCO2 etc.)
MCDM
Entropy
Method
Weights
TOPSIS
Method
C* ranking
(98% tolerance on C*max)
Weight
Step 3 – Proposed method: results
0.45
0.4
0.35
0.3
0.25
0.2
0.15
0.1
0.05
0
yCOKE yCH4 yCO
98% tolerance on C*max
0.97
Closeness to the ideal solution (C*)
yH2 Heat η (%) yCO2 T (˚C)
(KW)
0.96
0.95
0.94
0.93
BG DOR 1/0.67/0/0.25
0.92
BG SR 1/0.67/1/0
0.91
BG TRI-R 1/0.67/1/0.1
METHANE SR 1/0/1/0
0.9
600
700
800
900
T (˚C)
1000
1100
1200
Step 3 – Proposed method: results
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
BG SR CH4/CO2/H2O/O2=1/0.67/1/0
yCH4
yCO2
yCO
yHYD
yCOKE
200
700
1200
Molar fraction at the outlet (y)
Molar fraction at the outlet (y)
BG DOR CH4/CO2/H2O/O2=1/0.67/0/0.25
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
yCH4
yCO2
yCO
yHYD
yCOKE
200
T (˚C)
METHANE SR CH4/CO2/H2O/O2=1/0/1/0
yCH4
yCO2
yCO
yHYD
yCOKE
T (˚C)
1200
Molar fraction at the outlet (y)
Molar fraction at the outlet (y)
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
700
1200
T (˚C)
BG TRI-R CH4/CO2/H2O/O2=1/0.67/1/0.1
200
700
0.8
0.7
0.6
0.5
0.4
0.3
0.2
0.1
0
yCH4
yCO2
yCO
yHYD
yCOKE
200
700
T (˚C)
1200
Step 3 – Proposed method: results
700
%
xCH4
xCO2
η (%)
Heat (KW)
100
90
80
70
60
50
40
30
20
10
0
200
200
700
T (˚C)
xCO2
η (%)
Heat (KW)
METHANE SR CH4/CO2/H2O/O2=1/0.67/1/0
xCH4
xCO2
η (%)
Heat (KW)
%
Title
%
BG TRI-R CH4/CO2/H2O/O2=1/0.67/1/0.1
400
350
300
250
200
150
100
50
0
1200
xCH4
T (˚C)
T (˚C)
100
90
80
70
60
50
40
30
20
10
0
700
400
350
300
250
200
150
100
50
0
1200
100
90
80
70
60
50
40
30
20
10
0
200
700
T (˚C)
400
350
300
250
200
150
100
50
0
1200
Title
200
400
350
300
250
200
150
100
50
0
1200
Hat (KW)
%
100
90
80
70
60
50
40
30
20
10
0
Title
BG SR CH4/CO2/H2O/O2=1/0.67/1/0
BG DOR CH4/CO2/H2O/O2=1/0.67/0/0.25
xCH4
xCO2
η (%)
Heat (KW)
Conclusions and future work
Conclusions:
Future
work:
The more
proposed
is rational analysis
and straightforward;
•• Add
casesmethod
to the sensitivity
on the feeds;
Multiple
be taken
into(e.g.
consideration
in the assessment of
•• Add
morecriteria
criteriacan
to the
method
economical);
the effectiveness
of therig
process,
rather than
η alone;
• Set-up
an experimental
for simulated
biogas
tri-reforming (on going);
Biogas can
be employedthe
as adata
methane/natural
gas substitute
for reforming
processes
•• Validate
experimentally
from thermodynamic
simulations
plus MCDM
analysis;
over an
operating
conditions.
Interestingly
biogas
results inroadmap
slightly
• Apply
theeffective
methodrange
to theofother
processes
reported
in the biogas
exploitation
thanassessment.
methane.
inhigher
orderoverall-performances
to have a comprehensive
Thanks for listening
This project has received funding from the
European Union’s Seventh Framework Programme
for research, technological development and
demonstration under grant agreement n. 316838
Project coordinated by the QUESTOR Centre
at Queen’s University Belfast
www.qub.ac.uk/questor