Reforming of Biogas: optimal conditions through ...478837,en.pdf · Reforming of Biogas: optimal conditions through thermodynamics and MCDM analysis Fabio De Rosa School of Chemistry

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


-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)


(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

0.4

0.5

0.6

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


(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


• 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

0.2

0.3

0.4

0.5

0.6

0.7

0.8

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

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 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


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)


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

Documents

Reforming of Biogas: optimal conditions through ...478837,en.pdf · Reforming of Biogas: optimal conditions through thermodynamics and MCDM analysis Fabio De Rosa School of Chemistry