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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
Reforming technologies to syngas (CO + H2)
Upgrading - CH4 compression - CH4 liquefaction
Combustion ICE (heat & power)
Surplus energy exploitation
Sabatier reaction
Liquid fuel production
Gasoline, diesel, methanol
Hydrogen production
Fuel cells (heat & power)
Biogas
Biogas exploitation roadmap – focus on reforming
Liquid fuel production
Hydrogen production
Biogas
Reforming technologies to syngas (CO + H2)
Main target : Find the “best way” to reformate Biogas into Syngas
Reforming technologies
Technology Feed
Biogas dry-oxidative reforming (BG DOR) CH4, CO2, O2
Biogas dry-oxidative reforming (autothermal) (BG DOR (ATR)) CH4, CO2, O2
Biogas steam reforming (BG SR) CH4, CO2, H2O
Biogas steam reforming (autothermal) (BG SR(ATR)) CH4, CO2, H2O, O2
Biogas tri-reforming (BG TRI-R) CH4, CO2, H2O, O2
Biogas tri-reforming (autothermal) (BG TRI-R(ATR)) CH4, CO2, H2O, O2
Biogas as a feedstock
• 8 reforming technologies; • 32 reforming processes (feed sensitivity); • Fixed CH4/CO2=1.5 (60% CH4, 40% CO2).
Reforming technologies under exam
refe
ren
ce
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.
Computer-aided simulations
Technology CH4/CO2/H2O/O2 Technology (ctd) CH4/CO2/H2O/O2 (ctd)
BG DOR 1/0.67/0/0.1 1/0.67/2/0.25
1/0.67/0/0.25 1/0.67/2/0.5
1/0.67/0/0.5 1/0.67/2/0.75
1/0.67/0/0.75 1/0.67/3/0.1
BG DOR(ATR) 1/0.67/0/0.0015-0.8933 1/0.67/3/0.25
BG SR 1/0.67/1/0 1/0.67/3/0.5
1/0.67/2/0 1/0.67/3/0.75
1/0.67/3/0 BG TRI-R(ATR) 1/0.67/1/0-0.6839
BG SR(ATR) 1/0.67/1/0-1.0725 1/0.67/2/0-0.7144
1/0.67/2/0-1.1755 1/0.67/3/0-0.7471
1/0.67/3/0-1.2815 METHANE SR 1/0/1/0
BG TRI-R 1/0.67/1/0.1 1/0/2/0
1/0.67/1/0.25 1/0/3/0
1/0.67/1/0.5 METHANE SR(ATR) 1/0/1/0-0.6191
1/0.67/1/0.75 1/0/2/0-0.6524
1/0.67/2/0.1 1/0/3/0-0.6874
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)
Ein Eout
Methane Steam Reforming
- 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.
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
200 300 400 500 600 700 800 900 1000 1100 1200
Mo
lar
frac
tio
n a
t th
e o
utl
et
(y)
T (˚C)
Methane Steam Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0/1/0
yCH4
yCO2
yH2O
yCO
yH2
yCOKE
Step 1 - ASPEN Plus thermodynamic simulations
-150
-100
-50
0
50
100
150
200
250
300
0
10
20
30
40
50
60
70
80
90
100
200 300 400 500 600 700 800 900 1000 1100 1200
He
at (
KW
)
%
T (˚C)
Methane Steam Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0/1/0
xCH4
xCO2
η (%)
Heat (KW)
Step 1 - ASPEN Plus thermodynamic simulations
(30 x 8) matrix
1 mol/s Biogas (60% CH4, 40% CO2), P=1 bar, T=200-1200˚C, ΔT≈35˚C (30 alternatives)
0
0.1
0.2
0.3
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0.7
0.8
200 400 600 800 1000 1200
Mo
lar
frac
tio
n a
t th
e o
utl
et
(y)
T (˚C)
yCH4
yCO2
yH2O
yCO
yH2
yCOKE
Step 1 - ASPEN Plus thermodynamic simulations
(30 x 8) matrix
Target: Find a trade-off between cost (T, yCH4, yCO2, yCOKE, Heat) and benefit (yCO, yH2, η) criteria:
Multi Criteria Decision Making (MCDM) techniques
Step 1 - ASPEN Plus thermodynamic simulations
• 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)
Step 2 – MCDM techniques: TOPSIS method
Criterion 1 (increasing preference)
Cri
teri
on
2 (
incr
easi
ng
pre
fere
nce
)
PIS
NIS
Alternative 1
0
0.1
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0.9
1
200 400 600 800 1000 1200
Clo
sen
ess
to
th
e id
eal
so
luti
on
(C
*)
T (˚C)
98% Tolerance on C*
max
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
yCOKE yCH4 yCO2 yCO Heat(KW)
η (%) yH2 T (˚C)
We
igh
t
How do we choose weights?
Example: Biogas Steam Reforming, P=1 bar, CH4/CO2/H2O/O2=1/0/1/0
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
• yCOKE decreasing • WeightyCOKE increasing
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
T (°C) yCH4 yCO2 yCO yH2 yCOKE η (%) Heat(KW)
We
igh
t O2/CH4=0.1
O2/CH4=0.25
O2/CH4=0.5
O2/CH4=0.75 0
0.02
0.04
0.06
0.08
0.1
0.12
0.14
200 700 1200
O2/CH4=0.1
O2/CH4=0.25
O2/CH4=0.5
O2/CH4=0.75
Raw
Dat
a M
atri
x (9
60
x 8
) (T
, yC
H4
, yC
O2
etc
.)
Entropy Method
TOPSIS Method
Weights
C* ranking (98% tolerance on C*max)
Process 1
ASP
EN P
lus
Process 32
… 32 matrixes (30 x 8)
Step 3 – Proposed method
Thermodynamic MCDM
0
0.05
0.1
0.15
0.2
0.25
0.3
0.35
0.4
0.45
yCOKE yCH4 yCO yH2 Heat(KW)
η (%) yCO2 T (˚C)
We
igh
t
0.9
0.91
0.92
0.93
0.94
0.95
0.96
0.97
600 700 800 900 1000 1100 1200
Clo
sen
ess
to
th
e id
eal
so
luti
on
(C
*)
T (˚C)
BG DOR 1/0.67/0/0.25
BG SR 1/0.67/1/0
BG TRI-R 1/0.67/1/0.1
METHANE SR 1/0/1/0
98% tolerance on C*max
Step 3 – Proposed method: results
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200 700 1200Mo
lar
frac
tio
n a
t th
e o
utl
et
(y)
T (˚C)
BG DOR CH4/CO2/H2O/O2=1/0.67/0/0.25
yCH4
yCO2
yCO
yHYD
yCOKE 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
200 700 1200Mo
lar
frac
tio
n a
t th
e o
utl
et
(y)
T (˚C)
BG SR CH4/CO2/H2O/O2=1/0.67/1/0
yCH4
yCO2
yCO
yHYD
yCOKE
0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
200 700 1200Mo
lar
frac
tio
n a
t th
e o
utl
et
(y)
T (˚C)
BG TRI-R CH4/CO2/H2O/O2=1/0.67/1/0.1
yCH4
yCO2
yCO
yHYD
yCOKE 0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
200 700 1200Mo
lar
frac
tio
n a
t th
e o
utl
et
(y)
T (˚C)
METHANE SR CH4/CO2/H2O/O2=1/0/1/0
yCH4
yCO2
yCO
yHYD
yCOKE
Step 3 – Proposed method: results
0
50
100
150
200
250
300
350
400
0102030405060708090
100
200 700 1200
Hat
(K
W)
%
T (˚C)
BG DOR CH4/CO2/H2O/O2=1/0.67/0/0.25
xCH4
xCO2
η (%)
Heat (KW)
0
50
100
150
200
250
300
350
400
0102030405060708090
100
200 700 1200
Titl
e
%
T (˚C)
BG TRI-R CH4/CO2/H2O/O2=1/0.67/1/0.1
xCH4
xCO2
η (%)
Heat (KW)
0
50
100
150
200
250
300
350
400
0102030405060708090
100
200 700 1200
Titl
e
%
T (˚C)
BG SR CH4/CO2/H2O/O2=1/0.67/1/0
xCH4
xCO2
η (%)
Heat (KW)
0
50
100
150
200
250
300
350
400
0102030405060708090
100
200 700 1200
Titl
e
%
T (˚C)
METHANE SR CH4/CO2/H2O/O2=1/0.67/1/0
xCH4
xCO2
η (%)
Heat (KW)
Step 3 – Proposed method: results
Conclusions and future work
Conclusions:
• The proposed method is rational and straightforward;
• Multiple criteria can be taken into consideration in the assessment of
the effectiveness of the process, rather than η alone;
• Biogas can be employed as a methane/natural gas substitute for reforming processes
over an effective range of operating conditions. Interestingly biogas results in slightly
higher overall-performances than methane.
Future work:
• Add more cases to the sensitivity analysis on the feeds;
• Add more criteria to the method (e.g. economical);
• Set-up an experimental rig for simulated biogas tri-reforming (on going);
• Validate experimentally the data from thermodynamic simulations plus MCDM analysis;
• Apply the method to the other processes reported in the biogas exploitation roadmap
in order to have a comprehensive assessment.
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