energy balances of bio-energy systems; the relative

Copernicus InstituteSustainable Development and Innovation Management

Energy balances of bio-energysystems; the relative position of

biogas production.- Workshop: Energy Crops & Biogas, ’pathways tosuccess?, Organized by Cropgen & IEA task 37,Utrecht, the Netherlands, September 22, 2005’ -

Andre FaaijCopernicus Institute – Utrecht University


Issues

• Development of digestion so far.• Digestion as waste treatment option in

waste treatment infrastructure.• Some notions on energy crops.• Final remarks on energy crops &

digestion


State-of-the-art

Central digestor in Studsgard


Denmark…

Denemark issuccessful:

- 40 farm systems- 20 centralised

systems- High market

penetration

0

5

10

15

20

25

30

35

40

1974

1976

1978

1980

1982

1984

1986

1988

1990

1992

1994

1996

1998

2000

2002

Centralised plants Farmscale plants


Een leercurve voor de investeringskosten vanDeense biogas centrales

Cumulative digester capacity (m3/day)

50 100 200 400 600 8001000 2000 4000

Inve

stm

ent c

osts

/ da

ily d

iges

ter c

apac

ity

(103 E

uro(

2002

) / m

3 / da

y)

10

20

30

40

50

PR = 88% R2 = 0.69


Based on 20large scalegrootschaligebiogas plantsin Denmark1985-2001

Cumulative Danish biogas production (106 Nm3)

0.01 0.1 1 10 100 1000

Bio

gas

prod

uctio

n co

sts

(Eur

o(20

02)/N

m3 )

0.1

0.2

0.3

0.4

0.50.60.70.80.9

1

2

3

4

56789

10

Cumulative treated biomass use (103 m3)

0.1 1 10 100 1000 10000

Cos

t of t

reat

ed b

iom

ass

(Eur

o(20

02)/m

3 )

10

11

12

13

14

15

16

17

181920

Average biogas production costs 1984-1997 (Source: Mæng et al.)Weighed average biogas production costs 1984-1991Weighed average biogas production costs 1991-2001Marginal biogas production costs (1987-2001)Wheighed average treated biomass costs (1989-2001) (top / right axes)

1984

1988

1989

1990

1986

2001

1991

1985

PR = 85% R2 = 0.97

PR = 76% R2= 0.98

1996

19891990

2001

PR 100%

A learningcurve for

Danish biogasproduction

1985

1992

2001


Development of average biogas yield andincome of Danish manure digestors.

0

5

10

15

20

25

30

35

40

45

1988 1990 1992 1994 1996 1998 2000 2002Year

Ave

rage

bio

gas

yiel

d pe

r m3 b

iom

ass

treat

ed (m

3 )

0

1

2

3

4

5

6

Ave

rage

cur

rent

Inco

me

(106 E

uro

(200

2))

Gas yield

income


Some remarks:• Digestion has reached sound maturity

level (significant learning achieved overpast decades).

• Further cost reductions hampered byscarcity of co-digestate, stalling ofscale-up and market liberalisation.

• Continuity/stability of government policyvery important.


More information on digestion:

Learning in renewable energytechnology development

(Martin Junginger)

Strategic Niche Managementfor Biomass (Rob Raven)


National waste treatmentinfrastructure; optimalisation

• Optimalisation model; maximizing energy yield orminimizing costs.

• Performance of waste treatment and separationoptions in relation to scale (efficiencies, costs, heat(distribution), logistics).

• Waste supply and characteristics (moisture,contamination!).

• Boundary conditions (defaults energy system andmaterials).

• Analysis of different system lay outs (scenario’s).


Structure optimalisation modelInvoergegevens

o.a. afvalaanbod, technologieën, logistieke kengetallen

Vastgelegd hergebruikniet brandbare stromen

Nieuw aanbod

Bestaande verwerkingsinstallaties

Nieuw aanbod

AfvalbewerkingsstructuurAantal opties (hergebruik en verwerking)

energie en kosten

Optimalisatienaar energie of kosten

Nieuwe bewerkingsoptie(hergebruik of verwerkingsinstallatie)

t/maanbod = 0

energie, kosten

energie, kosten

energie, kosten

energie, kosten

technologie (t)verwerking ¦ hergebruik

Schaal (S)

Locatie (l)

Matrix model calculations:f (scale, technology, location)


System boundaries

biomassa- enafvalaanbod

Scheiden

brandstof,elektriciteit

geschiedenaanbod

Transport

brandstof

Verwerking

brandstof,warmteelektriciteit

verlieswarmte

Hergebruik

Warmte-distributie

warmte elektriciteit

warmte

brandstofUitsparingprimairproduktie


Waste supply for 2 scenario’s (kton)

Afvalaanbod in kton

02000400060008000

100001200014000

scho

on ho

utach

tigstr

o, ho

oi

berm

gras

, tuinb

ouw

pluim

veem

est

VGI-afv

al, sw

ill

oud e

n bew

erkt

hout

GFTge

mengd

afva

l

shre

dder

afva

lau

toban

den

rwzi-

slib

plasti

cpa

pier

Referentie LAP prognose


Waste supply for 2 scenario’s in PJ

Avalaanbod in PJ (stookwaarde)

0.020.040.060.080.0

100.0

scho

on ho

utach

tigstr

o, ho

oi

berm

gras

, tuin.

..plu

imve

emes

t

VGI-afv

al, sw

ill

oud e

n bew

erkt.

.. GFTge

mengd

afva

lsh

redd

eraf

val

autob

ande

nrw

zi-sli

bpla

stic

papie

r

Referentie LAP prognose


Gasification technologies:BIG/CC…

Pre-treatment Gasifier Fuel gas

clean-up

Fuel gasexpander Gas turbine HRSG

Air

Steamturbine

Ash Particles/alkalis

Fluegas

Fuel gascooler

Steam

Poplar wood

Natural gas

AirBurner

Flue gasInert gasGas

coolerSteam

Air

forpressure lockingDolomite

Hotwater

•Now: ACFB ~3500 U$/kWe,30% eff., ~10 Mwe•M.T.: ACFB ~1500 U$/kWe,50% eff., >100 MWe•L.T.: PCFB + HT, ~1000U$/kWe, 55% eff., >200 MWe

Power

Pre-treatment:

- grinding- drying

Gasification: Gascleaning:

FT liquids

Offgas

Recycle loop

FTsynthesis:

Gasturbine

Gasprocessing:

- reforming- shift- CO2 removal

and Fischer-Tropsch/DME…)


Performance technologies vs.capacity (costs)

Technologievergelijk - kosten

-5

0

5

10

15

20

25

30

0 200 400 600 800 1000

Schaal MWth-input

Euro

/GJ u

itg

. p

rim

air

Vergas s ing/m o to r

B IG/C C

IG/C C

Verg.-a a rdga s S TEG

AVI-ro o s te r

AVI-we rve lbe d

P yro lys e /bijs to o k-ko le n

HTU/bijs to o k-ko len

Vergis ting

B ijs to o k-ko le n indire c t

B ijs to o k-ko le n ve rg.

B io m as s a ve rbra nde n-WKK

He rge bruik-ine rt

Auto ba nde n

Vee vo e de r

M e s ts to f

Die rvo e de r

P la s tie k, m a te ria a l

F is che r-Tro ps ch

M e tha no l

P a pie rindus trie

P la s tie k, B TF


Performance technologies vs.capacity (efficiency)

Te chnologie ve rge lijk - e ne rgie

0

0.2

0.4

0.6

0.8

1

1.2

1.4

1.6

1.8

2

2.2

0 200 400 600 800 1000

Schaal MWth-input

MJ p

rim

air/M

J sto

okw

aa

rde

Ve rga s s ing /m o to r

B IG /C C

IG /C C

Ve rg.-a a rdga s S T E G

A VI-ro o s te r

A VI-we rve lbe d

P yro lys e /bijs to o k-ko le n

H T U/b ijs to o k-ko le n

Ve rgis t ing

B ijs to o k-ko le n ind ire c t

B ijs to o k-ko le n ve rg .

B ijs to o k-c e m e nt

B io m a s s a ve rbra nde n-WKK

A uto ba nde n

S pa a np la t

Ve e vo e de r

M e s ts to f

D ie rvo e de r

P la s tie k , m a te ria a l

F is c he r-T ro ps c h

M e tha no l

P a p ie rindus trie

P la s t ie k , B T F


Overview main characteristics wastetreatment infrastructure

naam aanbod achterafscheiden

warmte technologieën Bestaandeinstallaties

optimalisatie

Ref_energie referentie geen referentie geen beperking groene wei energieRef_kosten referentie geen referentie geen beperking kostenAchter_RDF referentie plastiek in

RDFreferentie geen beperking groene wei energie

Achter_plastiek referentie plastiekapart

referentie geen beperking groene wei energie

Geen_WKK referentie geen geenwarmtevraag

geen beperking groene wei energie

Optimaal_WKK referentie geen onbeperktewarmtevraag

geen beperking groene wei energie

Tegenval-energie referentie geen referentie BIG/CC slechter, geenHTU

groene wei energie

Tegenval-kosten referentie geen referentie BIG/CC slechter, geenHTU

groene wei kosten

Max_elektr./warmte referentie geen referentie geen hergebruik enbrandstofproductie

groene wei energie

Bestaande referentie geen referentie geen beperking bestaandeinstallaties

energie

Marsroutes Referentie,kostenverwerking

geen referentie BIG/CC slechter,bijstook additonelekosten, toepasbarheidzoals marsroutes

bestaandeinstallaties

energie


Primary energy saved in differentscenario’s

Uitgespaarde primair energie

0

50

100

150

200

250

300

350

400

450

Ref

eren

tie-

ener

gie

Ref

ere

ntie

-kos

ten

Ach

tera

fsch

eid

ing

Ge

en w

arm

te

Opt

imaa

l war

mte

Tege

n te

ch-

.ont

w.-

ene

rgie

Tege

n te

ch-

.on

tw.-

kos

ten

Max

E/W

Max

bra

ndst

of

Bes

taan

de

Mar

srou

tes

Aan

bod

LA

P

PJ

Elektric iteit en w armte Hergebruik Brandstof


Total waste treatment costs of differentscenario’s

Totale kosten

-400

-200

0

200

400

600

800

1000

1200R

efer

entie

-en

ergi

e

Ref

eren

tie-k

oste

n

Ach

tera

fsch

eidi

ng

Gee

n w

arm

te

Opt

imaa

l war

mte

Tege

n te

ch-

.ont

w.-

ener

gie

Tege

n te

ch-

.ont

w.-

kost

en

Max

E/W

Max

bra

ndst

of

Bes

taan

de

Mar

srou

tes

Aan

bod

LAP

m iljoen Euro


Resultsreferencescenario-energy

Saved primaryenergy andtechnology mix

Referentiesecenario - energie

0

50

100

150

200

250

300

350

400

Ver

gass

ing/

mot

or

BIG

/CC

IG/C

C

Ver

g.-a

ardg

asS

TEG

HTU

/bijs

took

-kol

en

Ver

gist

ing

Bijs

took

-cem

ent

Her

gebr

uik-

bran

dbaa

r

Her

gebr

uik-

iner

t

Tota

al e

lect

r./w

arm

te

Tota

al b

rand

stof

Tota

al h

erge

brui

k

Tota

al

PJ

(kol

omm

en: s

took

waa

rde

afva

l; X

: uitg

espa

arde

prim

air e

nerg

ie)

papier

plastic

rw zi-slib

auto banden

reinigingsdienst afvalshredder afval

RDF

gemengd afval

GFT

oud enbew erkt houtVGI-afval,sw illpluimvee mest

bermgras,tuinbouwstro, hooi

schoonhoutachtiguitgespaardeprimair energie


Referentiescenario - kosten

0

50

100

150

200

250

300

350

400

Bijs

took

-cem

ent

BIG

/CC

IG/C

C

Bio

mas

sa v

erbr

.-WK

K

HTU

/bijs

took

-kol

en

Ver

gist

ing

Bijs

took

-cem

ent

Her

gebr

uik-

bran

dbaa

r

Her

gebr

uik-

iner

t

Tota

al e

lect

r./w

arm

te

Tota

al b

rand

stof

Tota

al h

erge

brui

k

Tota

al

papier

plastic

rw zi-slib

autobanden

reinigingsdienstafval

shredderafval

RDF

gemengd afval

GFT

oud en bew erkt hout

VGI-afval, sw ill

pluimveemest

bermgras, tuinbouw

stro, hooi

schoon houtachtig

uitgespaarde primairenergie

Resultsreferencescenario-costs

Costs andtechnology mix


Some findings• Depending on boundary conditions, large shifts

between electricity and heat, savings by recycling andtransport fuels (high sensitivities).

• Key advanced technologies: 1: (B)IG/CC, 2: co-firingand gasification with NGCC, 3: Separate collection &Waste separation, 4: HTU for wet streams (possiblystrong alternative for digestion).

• Large scale facilities generally more attractive.• Increasing heat utilisation has significant potential but

strongly competes with NG and possibly efficiencymeasures.


Biomass production performance data for varioustypes of crops and conditions


Basics energy crop options (EU)Crop Typical yield

ranges (odt/ha*yr)

Energy inputs (GJprim/ha*yr

Typical net energy yield (GJ/ha*yr)

Production cost ranges European context (Euro/GJ)

Short term 2.9 (rapeseed) 2.6 (straw)

11 110 (total) 20 Rape

Longer term 4 (rapeseed) 4.5 (straw)

12 180 (total) 12

Short term 14 13 250 12 Sugar Beet Longer term 20 10 370 8

Shorter term 10 5 180 3-6 SRC-Willow Longer term 15 5 280 <2

Shorter term 9 4 150 3-4 Poplar Longer term 13 4 250 <2 Shorter term 10 13-14 180 3-6 Miscant

hus Longer term 20 13-14 350 ~2


Final remarks• Digestion is a sound and available conversion

technology for wet(ter) biomass streams(including manure) .

• Thermal conversion options strongcompetitors for drier and lignocellulosicbiomass.

• Perennial crops (lignocell…) generally havebetter energy & GHG & environmentalbalances (and economics!) than annualcrops.

• Role of digestion…?

energy balances of bio-energy systems; the relative

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