Allocation of biomass (WP5) energy modeling approach and scenario assumptions

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Allocation of biomass (WP5)energy modeling approach and scenario assumptions

Joost van Stralen (ECN)

Biomass Futures workshop, November 26th, Brussels

June 2009- December 2011- EIE/08/653 26/11/2010 22

Contents • Objective• RESolve• Biomass allocation in RESolve• Scenario assumptions• Conclusions


Objective

“Assess the role of bioenergy in different sectors”

Biomass

Electricity Heat Biofuels Chemicals Food …

• Develop a model that allows for biomass allocation over different sectors• Scenario analysis• Interaction with PRIMES


NREAP figures*

2005 2010 2015 20200

50

100

150

200

250

RES-E

TWh

2005 2010 2015 20200

10

20

30

40

50

60

70

80

RES-H

Mto

e

2005 2010 2015 20200

5

10

15

20

25

30

Biofuels

OtherBiodieselEtOH/ETBE

Mto

e

* 21 EU countries


Production-consumption chains

Production of biomass

Conversion into bio(-energy) commodities

Conversion into bio(-energy) products

Functions of the products Market (demand)

Land availability

(supply)


RESolve: overview

RESolve

Biomass allocation

RES-H/C:RESolve-H/C

Biofuels:RESolve-T

RES-E:RESolve-E

E-prices:COMPETES


RESolve-E*

Market simulation

Policy-based demand forrenewable electricity

Supply curvesbased on

technologycosts & potentials

•Risk•Transaction costs•Lead times

years•Market Green Price(s)•Technology mix•Trade flows

ADMIRE REBUS MODEL

scenarios

• Decoupling of grey market

• Barriers and distortions

• Realisable potentials

*Formerly known as ADMIRE-REBUS


Biomass – technology combinations

Biomass resource Co-firing Combustion Gasification Digestion CHP

Energy cropsForestrySolid manureLiquid manureMunicipal Solid WasteBarley residuesMaize residuesOilcrops residuesRapeseed residuesWheat residuesLandfill gasSewage sludgeIndustrial waste

xxx

xxxxx

xxx

xxxxxx

x

xxx

xxxxx

x

x x

xxxx

xxxxxxx

Per resource, start with lowest cost technology


RESolve-H

0%

20%

40%

60%

80%

100%

0,0 0,2 0,4 0,6 0,8 1,0 1,2 1,4cost/benefit ratio

pene

tratio

n

Non-economic Dispersed All-or-nothing


RESolve-T*

*Formerly known as BioTrans

Find the minimal cost allocations along the biofuel supply chain in a group of countries, given projections of demand (biofuel target), potentials and technological progress

EU countries


How does it work?

Import & export


BioethanolE05/E85 (not in trucks)

Oil crops

Pre-treated biomass

Pure vegetable oilonly intermediate product

Used fats/oils

Sugar crops

Starch crops

Oil extraction Transesterification ofvegetable oil (no palm oil)

Ethanol productionfrom sugar crops

Ethanol productionfrom starch crops

Ethanol production fromlignocellulosic crops

Pretreatment for gasification(torrefraction, pelletisation)

Fischer-Tropsch diesel production (incl. gasification)

Transesterificationof used fats/oils and palm oil

ETBE synthesis

DME production(incl. gasification)

SNG production(incl. gasification)

Import of ethanol from Brazil

BiodieselB05/B100

Bio-DMEDME

Bio-SNGCNG (not in trucks)

Bio-ETBEexcluded from the model

Bio-FT-dieselFT-diesel

Iso-butylene

Agricultural residues

Grassy crops

Forestry residues

Wood processing residues

Woody crops

Glycerine (80%)Pulp (from oil seeds)

Electricity

Stillage

Pulp (from sugar crops)

Resource

Process

Intermediate product

Potential biofuel(excluded from model)

BiofuelTYPE

Auxiliary product Byproduct

Wet manure Biogas production

Import of palm oilfrom Malaysia

Vinasses

What kind of categories are supplied?


What kind of categories are supplied ?

• Fuels• Biodiesel, Bio-FT-diesel, Bio-DME, Bio-SNG• Bioethanol, Lignocellulosic ethanol, Biogas• Emissions• CO2, CH4, N2O as CO2-equivalents• Technologies• Biofuel producing technologies, incl. torrefaction&oil extraction• Countries and Regions• Europe: West, Central/East; Ukraine, Rest of World


Cost supply curves for crops

Example: Austria in 2010Nuts2 level


How to allocate biomass over the different sectors?

• E, H and T treated unbiased• Avoid double counting• Import and export of biomass• Emissions over the chain

New demand segments in RESolve-T:• Bio-electricity• Bio-heat

Extension of RESolve-T


Biomass allocation in RESolve(-T)

Find the minimal cost allocations along the bio-energy supply chain in a group of countries, given projections of demands (biofuel target, demand for bio-electricity and -heat), potentials and technological progress


RESolve-E RESolve-H

-demand bio-heat- RES-H support

-demand bio-electr- RES-E support

RESolve-T

-pfeedstock

-biomass pot. RES-E

RESolve-E

-pfeedstock

-biomass pot. RES-H

RES-E/H demand converged?

RESolve-H

NO

-Final RES-mix-avoided emissions-other indicators

YES



Connection of models - Flowchart


How to deal with demand > supply?

FINE? NOT FINE?

Comparison with RES-E and -H alternatives

Initial pfeedstock↑

pfeedstock↑ till demand =

supply

Continue with iterations

Continue with iterations

General demand too large→ decrease from sector With lowest demand ‘pull’


Current statusRESolve-E RESolve-H



RESolve-T

-pfeedstock

-biomass pot. RES-E

RESolve-E

-pfeedstock

-biomass pot. RES-H

RES-E/H demand converged?

RESolve-H

NO

-Final RES-mix-avoided emissions-other indicators

YES



Current status


Scenarios

Pessimistic

availability

of biomass

Optimistic

availability

of biomass

Slow development

non-biomass RES

‘NREAP’

Large biomassMedium biomass

Low biomass

Fast development

non-biomass RES


CASES

• Zoom in at NREAP scenario in more detail

• CASE 1: Achieving a maximum biofuel contribution

• CASE 2: More electrification in the transport sector

• CASE 3: Additional RES-H support• CASE 4: Focus on minimizing GHG emissions


Conclusions

• A methodology for biomass allocation has been developed (D5.1)

• Implementation is going on → coupling RESolve-X models. RESolve-T used for allocation of biomass

• Draft scenarios have been developed• Interaction with PRIMES needs to be

worked on


Questions?

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Allocation of biomass (WP5) energy modeling approach and scenario assumptions