Post on 17-Mar-2018
Modelling of Material and Energy Balance of Biogas Production Process
Mandy Gerber
2nd GERG Academic Network Event
Brussels, June 2010
2Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Basics
Biogas • Metabolic waste product
Production• Degradation of organic matter
(protein, carbohydrate, fats)in anaerobic environment
• Natural process identical toswamp / marsh, cattle rumen,sewage sludge, dumps, rice field
Input material• Manure, energy crops, organic waste
10.01 – 5N2
0.030.01 – 2O2
<10 – 1H2
0.7*0.01 – 2.5*NH3
500*10 – 30,000*H2S
ProcessRangeVol-%
AverageVol-%
CH4 45 – 70 60
CO2 25 – 55 35
H2Od(25°C, 1 atm)
0 – 10 3.1
* in mg/m³ DVGW, 2005
3Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Basics
IEKP of German government• Integrated energy and climate programme (measures to
increase energy efficiency and use of renewable energies)• Objective: replace 10% of gas supply by gas out of biomass
(60·109 kWh biogas per year until 2020, 100·109 kWh biogas per year until 2030)
Quality of biogas for feeding in gas distribution net• Raw biogas: HHV = 5.2 - 8.2 kWh/m³, WS = 18.0 - 33.1 MJ/m³
(average: HHV = 6.9 kWh/m³, WS = 26.1 MJ/m³)
• Upgraded biogas: HHV = 10.8 kWh/m³, WS = 51.3 MJ/m³• Depending on net and biogas quality as exchange gas or
additional gas(L-Gas: WS = 37.8 - 46.8 MJ/m³, H-Gas: WS = 46.1 - 56.5 MJ/m³,HHV = 8.4 - 13.1 kWh/m³)
4Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Basics
Status biogas plants in Germany• 30 of about 4500 biogas plants with feed in a gas distribution net
(about 2.6% of government goal)
• To reach the goal of government: Construction of 100 – 120 biogas plants per year until 2020 will be needed(700 Nm³/h, 8000 operating hours)
8501043
13601608 1760
2010
2690
3711
3280
4780
4000
1600
1400
1270
950
665
2471901601117849
0
1000
2000
3000
4000
5000
1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009*
num
ber o
f bio
gas
plan
ts
0
200
400
600
800
1000
1200
1400
1600
pow
er in
stal
led
in M
W
biogas plants
installed power
EEG1. modified
EEG2. modiefied
EEG
5Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Basics
Typical biogas plant• Two-stages• Feed: energy crops and manure
6Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Modelling
Aspen Custom Modeller• Modelling
of importantplantcomponents
7Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Material Balance Fermenter
Process parameter • Quality of input material
(organic components, inhibitors, trace elements)
• Quantity of inputmaterial (organic loading rate, dilution)
• pH value / alkalinity / phase equilibrium
• Temperature• Adaption of
microorganism
0.0
0.1
0.2
0.3
0.4
0 20 40 60 80 100 120
substrate concentration in mmol/L
spec
ific
grow
th ra
te in
d -1
pH 6.0 pH 6.5 pH 7.0
µmax = 0,4 d-1
KS = 0,033 mmol/LKI = 0,667 mmol/L
biodegradable organic
Hydrolysis(hydrolytic enzymes)
amino acids, mono saccharide fatty acids
Acidogenesis(acidogentic microorganisms)
acetate
CH4, CO2
Methanogenesis(methanogenic microorganisms)
Acetogenesis(acetogenic microorganisms)
21%
100%
proteinscarbo-hydrate fats
complex organic
21%40% 5%
46%
H2, CO2
propionate, butyrate, etc
20% 34%
35% 12% 23% 11% 8% 11%
70% 30%
biodegradable organic
Hydrolysis(hydrolytic enzymes)
amino acids, mono saccharide fatty acids
Acidogenesis(acidogentic microorganisms)
acetate
CH4, CO2
Methanogenesis(methanogenic microorganisms)
Acetogenesis(acetogenic microorganisms)
21%
100%
proteinscarbo-hydrate fats
complex organic
21%40% 5%
46%
H2, CO2
propionate, butyrate, etc
20% 34%
35% 12% 23% 11% 8% 11%
70% 30%
8Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Material Balance Fermenter
Static models • Baserga
based on gas production → except KTBL and batch testof organic components mostly used for facility design
• Keymer & Schilcherbased on Baserga incl. → derived from evaluating animal feeddegradation coefficients
• Boylebased on elementary → maximum of gas production as referencecomposition state ⋅⎛ ⎞+ − − + +⎜ ⎟
⎝ ⎠⋅⎛ ⎞→ + − − −⎜ ⎟
⎝ ⎠⋅⎛ ⎞+ − + + + + +⎜ ⎟
⎝ ⎠
2
4
2 3 2
34 2 4 2
32 8 4 8 4
32 8 4 8 4
a b c d eb c d eC H O N S a H O
a b c d e CH
a b c d e CO d NH e H S
= ⋅ ⋅∑KoS i i ii
q x VQ q
= ⋅ + ⋅ + ⋅KoS CH CH Lip Lip Prot Protq x q x q x q
9Mandy Gerber | 2nd GERG Academic Network Event | June 2010
0
20
40
60
80
100
0 10 20 30 40 50 60test duration in d
stan
dard
ised
gas
pro
duct
ion
in %
CCM 2
CCM 3
Material Balance Fermenter
Comparison to literature and laboratory
literaturelabliteraturelabliteraturelabliteraturelab
-1.4-1.4
-186.7
-3.1-43.7-75.4
Corn silage
12.6-21.8-48.7
-33.7-56.4-80.5
CCM
---
10.1-45.0-73.1
GPSCattle manure
Boyle -122.7 -82.1Baserga 21.2 -52.5K&S 21.2 5.4
Deviation in % [100 · (lN,exp/lit – lN,calc) / lN,exp/lit] of specific gas production (lN/kgOM):
inhibition
10Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Material Balance Fermenter
Comparison to a largescale biogas plant
-2.2-2.51.349.450.550.648.7Vol.-%CH4
2.32.64.147.346.246.145.3Vol.-%CO2
---44.20.1--0.1Vol.-%H2S------2.5Vol.-%NH3
Gas productionK&SBasergaBoylePraxisK&SBasergaBoyle
3.3
154965
3.3
123771
3.3
89554
3.3
88548
0.0
-76.0-76.0
0.0
-40.7-40.7in lN/kgOM -1.1
in lN/kgOM -1.1
H2O Vol.-% 0.0
11Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Material Balance Fermenter
Henry coefficient, acidcoefficient, vapour pressure
growth rate, vapourpressure
vapour pressureTemperature
CH4, CO2, H2CO2, NH3CO2Gas solubilityVOA, CO2, H2O, NH3CO2, acetic acid, H2OCO2, acetic acid, H2OIonic equilibrium
CH, XP, XL, MS, AA, AC, PR, BU, VA, LCFA, H2, CH4, 7 MO, Comp, IN, IC , PI, SI
organic matter, acetic acid
acetic acidInput material
CH4, CO2, H2, H2OCH4, CO2, NH3, H2OCH4, CO2, H2OGas
highmediumlowComplexitymany input parameters, many dependencies
less input, many outputparameters
process stability, lessinput parameters
Adapted to
1921Degradation stepsADM1Hill & BarthAndrews & Graef
substrate Substrate substrate, NH3, H2, pHInhibition
CH: carbohydrate, XP: protein, XL: lipid, MS: monosaccharide, AA: Amino Acid, LCFA: Long Chain Fatty Acid, VA: Valeric Acid, BU: Butyric Acid, PR: Propionic Acid, AC: Acetic Acid, MO: Microorganism, Comp: Composites, PI: Particulate Inert, SI: Soluble Inert, IN: Inorganic Nitrogen, IC: Inorganic Carbon, A-: Anions, C+: Cations
Dynamic models
12Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Material Balance Fermenter
Model of Andrews & Graef
Gas phase
biogas = +4 2BG CH COV V V
CO2 production = − ⋅ ⋅2CO m L GV v V T
CH4 production μ= ⋅ ⋅ ⋅ ⋅4 4 / 1CH m L CH XV v V Y X
CO2 partial pressure = − ⋅ ⋅ ⋅ − ⋅2 2CO COLT m G BG
G G
dp pVp v T Vdt V V
Liquid phase
CO2 balance ( )= ⋅ − + + +, 2 ,1 0, 2 ,0 , 2 ,1
D
D D
m COm CO m CO G B C
L
dc V c c T R Rdt V
netto cation balance ( )= ⋅ −, ,1 0, ,0 , ,1
m Zm Z m Z
L
dc V c cdt V
chemical production rate ( )= ⋅ − + −, ,1 , ,10, 3,0 , 3,1
m AC m ZC m HCO m HCO
L
dc dcVR c cV dt dt
gas transfer rate ( )= ⋅ −, 2 , 2 , 2 ,1S DG LA CO m CO m COT K c c
dissolved CO2, saturated
= ⋅, 2 , 2 2Sm CO H CO COc K p
carbonate −= −, 3,1 , ,1 , ,1m HCO m Z m ACc c c
unionised acetic acid + −⋅
= , ,1 , ,1, ,1
m H m ACm HAC
AC
c cc
K
hydrogen +
⋅= , 2 ,1
, ,1, 3,1
DC m COm H
m HCO
K cc
c
pH value ( )+= − , ,1log m HpH c
Biological phase
organism balance ( ) μ= ⋅ − + ⋅010 1 1
L
VdX X X Xdt V
acetic acid balance ( ) μ= ⋅ − − ⋅, ,1 0
, ,0 , ,1 1/
m ACm AC m AC
L X S
dc V c c Xdt V Y
growth rate μμ =
+ +
max
, ,1
, ,1
1 m HAcS
m HAc I
cKc K
biological production rate CO2
μ= ⋅ ⋅2 / 1B CO XR Y X
Coefficients
,a ACK 10-4,5 ionisation constant acetic acid at 38°C
,a CK 10-6 ionisation constant CO2 at 38°C
, 2H COK 0,024272 kmol/bar·m³ Henry’s law constant CO2 at 38°C
, 2LA COK 100 d-1 gas transfer rate
IK 0,667 mol/m³ inhibition constant
SK 0,0333 mol/m³ saturation constant
μmax 0,04 d-1 maximum growth rate
2 /CO XY 47 kmolCO2/kmolX Yield coefficient biomass to CO2
4 /CH XY 47 kmolCH4/kmolX Yield coefficient biomass to CH4
/X ACY 0,02 kmolX/kmolAC Yield coefficient acetic acid to biomass
13Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Material Balance Fermenter
Spontanously triplication of feeding
02468
1012141618
0 5 10 15 20test duration in d
gas
prod
uctio
n in
l/da
y
1 to 3 l/day
1 to 2 l/day
0
10
20
30
40
50
60
0 5 10 15 20
test duration in d
met
hane
in v
ol.-%
1 to 3 l/day
1 to 2 l/day
0.000.020.040.060.080.100.120.140.160.18
0 5 10 15 20test duration in d
subs
trate
con
cent
ratio
n in
km
ol/m
³
1 to 3 l/day
1 to 2 l/day
0.00
0.05
0.10
0.15
0.20
0.25
0.30
0 5 10 15 20test duration in d
grow
th ra
te in
1/d
ay
1 to 3 l/day
1 to 2 l/day
0.00000.00050.00100.00150.00200.00250.00300.00350.00400.0045
0 5 10 15 20
test duration in d
mic
roor
gani
sm c
once
ntra
tion
in k
mol
/m³
1 to 3 l/day
1 to 2 l/day
0.01.02.03.04.05.06.07.08.09.0
0 5 10 15 20test duration in d
pH
0.000
0.002
0.004
0.006
0.008
0.010
0.012
0.014
conc
entra
tion
HC
O3
in k
mol
/m³
1 to 3
1 to 2
14Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Summary
Conclusion• Tool to design and optimise biogas plants• Investigation of process failures and reaction rates possible
Outlook• More data needed for validation, especially for dynamic models• expand simulation for modeling of gas treatment
15Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Thank you for your attention!
16Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Energy Balance Fermenter
Power demand mixer • Danish fermenter: one central, slow ongoing agitator• Agricultural fermenter: one or more submersible, fast ongoing
motor-driven agitators• Calculation by Newton-Number (geometry, agitator speed, flow,
density / viscosity - composition)
Danishfermenter
Agriculturalfermenter
Number of mixer 1 3Power 18.9 kW 38.3 kW
Energy Demand454 kWh/d
(24 h/d)77 kWh/d
(2 h/d)Feed: manure and corn silage (1:1), 3.65 kgOM/(m³d), volume 3000 m³, retention time 74d, temperature 38°C
ρ= ⋅ ⋅ ⋅3 5Mix RP Ne n d
Danish Fermenter
Agricultural Fermenter
17Mandy Gerber | 2nd GERG Academic Network Event | June 2010
Energy Balance Fermenter
Heat demand • Heat loss via roof, wall and ground (heat transfer coefficient of
every layer depending on temperature, wind speed, geometry, fluid properties)
• Dissipation Mixer• Enthalpy balance für heat of reaction and temperature difference
substrate / biogas (heating value, evaporation, heat capacity)
Danishfermenter
Agriculturalfermenter
Heat Demand 90.3 kW 38.3 kW2167 kWh/d 2936 kWh/d
Feed: manure and corn silage (1:1), 3.65 kgOM/(m³d), volume 3.000 m³, retention time 74d, temperaturefermenter 38°C, input material 20°C, ambient 15°C, wind speed 5 m/s
SUB SUBH ,t
BG BGH ,t
DIG DIGH ,t
Reft
Reft
ReftReaktion
SUBH
BGH
DIGH
HeizQ LossQ DissP