9 Assessing the Impacts by Pan-European TIMES Model...Bottom-up models Top-down models Attempt to...

Assesing the Impacts by Pan-EuropeanTIMES Model

Markus Blesl

Universität Stuttgart

MODEDR Conference, Praha

24th November 2009

1 Institut für Energiewirtschaft und Rationelle Energ ieanwendung, Universität Stuttgart

Markus Blesl TIMES PanEU 2 / 58

Categories of energy models

Simulation Optimization Computational

General Equilibrium

Econometric

Characteristics:i. Sectoral coverage or Entire energy system

ii. Single region or Multi regions

iii. Short term or Long-term

iv. Recursive dynamic or Perfect foresight

Characteristics:i. Single region or Multi regions

ii. Recursive dynamic or Perfect foresight

Integrated Assessment

ModelsClimate Models

Energy Models

Bottom-up models Top-down models

Attempt to link

model types


Goals of the TIMES development

- Restrictions in modelling of load curves- Changes the model horizon difficult+ Modelling flexible processes

PERSEUSPRIMES

LEAP

EFOM-ENV MARKALMESSAGE

- Load curves only for electricity and districtheat

- Changing the model horizon difficult- Rigid Processes

+ All processes and technologies depictable on subannuallevel

+ Any desired time resolution possible+ Changes in the model horizon possible (distinction

between input and model data)+ Flexible process description+ Easy extension of model features

TIMES


ETSAP

IEA (International Energy Agency)

Implementing Agreement Implementing Agreement

Implementing Agreements

Energy Technology Systems Analysis Programme (ETSAP)

Technology oriented analysis of energy system modelswith focus on greenhouse gas abatement strategies:

- Analysis of national and multinational strategies- Technology data review- Model development (MARKAL, TIMES)

Operating Agent

www.etsap.org

Outreach


Advanced Features/Variants

● Elastic demands

● Endogeneous learning

● Discrete capacity expansion

● Macroeconomic linkage

● Climate extension

● Stochastic programming

● Alternative objective functions

● Multi-criteria optimization

Methodology• Bottom-up Model

• Perfect competition

• Perfect foresight

• Optimization (LP/MIP/NLP)

Min/Max Objective functions.t.Equations, ConstraintsDecision Variables <=> SolutionInput parameters

Development• By ETSAP

• Implementation in GAMS

TIMESTIMES(The Integrated MARKAL (The Integrated MARKAL

EFOM System)EFOM System)

Applications of the model• IER:

- Ostfildern (local)

- Baden-Württemberg

- Bavaria

- Saxonia

- Hessen

- Germany (TIMES-D)

- European electricity and gas sector model (TIMES-EG)

- European energy system model

(TIMES PanEU)

- Global model (ETSAP-TIAM)

• Other places:

- Finland (VTT, Helsinki)

- Belgium (KUL, Leuven)

- Italy (Turin)

- South Africa model, Village model (ERC, Cape Town)

- EU-NEEDS project

- Global models (EFDA, ETSAP-TIAM)


Fundamental features of TIMES● Model structure

i. Flexible time horizon

ii. User-defined time slice resolution within a year

iii. Multi-regional

● Model formulationi. Partial Equilibrium Model

ii. Technology description:1. Single process type with access to all model features

2. Vintaged technology properties

3. Transformation eqn with overall and commodity-specific efficiencies

iii. Objective function:1. Different treatment of technology investments based on investment lead time

2. Other opimization functions than total system costs can be defined by modeller

● User constraintsi. Framework to formulate virtually any linear relationship between decision variables


Har

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Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Ste

am

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

NP

VTK

M

PK

M

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers

Process heat boilers

Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis

GasificationLiquefication

CH

2

Win

d

Area PV, Solarthermal,Energy crops

Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Reference energy system (simplified)

Dis

trict

Hea

t


Horizontal linkages: Technology chains

Electri

city HV

Coal, p

ower

CO 2

Supercriticalcoal plant

Coaltransport

Grid HV &Transf.

Lighting

Urban trains

Industry

Domesticmining

Coalimports

Grid MV &Transf.

Coal, w

ashe

d

Electri

city M

V Electri

city LV

ELCSCPCOLSCPSPC FLOFLO ,, =⋅η

2,,, COSCPCOLSCPCOLSCP FLOFLO =⋅ε

ELCSCPSCPELCSCP CAPACT ,, ⋅≤ α

ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=




ELCSCPSCP FLOACT ,=

Appliances

ELCDEMELCSCP FLOFLO ,, = ELCDEMELCSCP FLOFLO ,, = ELCDEMELCSCP FLOFLO ,, = ELCDEMELCSCP FLOFLO ,, = ELCDEMELCSCP FLOFLO ,, =

Backward Loops


Vertical linkages: Competition

Electri

city HV

Coal, p

ower

CO 2

Supercriticalcoal plant (exst)

Coaltransport

Grid HV &Transf.

Lighting

Urban trains

Industry

Domesticmining

Coalimports

Grid MV &Transf.

Coal, w

ashe

d

Electri

city M

V Electri

city LV

Appliances

Ultrasupercriticalcoal plant (new)

Natural gasGT (exist)

Natural gasCC (new)

Natur

alga

sLig

nite

Supercriticallignite plant (exst)

Supercriticallignite plant (new)

Competing options to produceelectricity:

• between technologies

• between old and new plants

Influenced by:

• Technology costs

• Efficiencies

• Emission factors

• Fuel prices…


Vertical linkages: Substitution

Har

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alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Ste

am

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PK

M

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Substitution options

Dis

trict

Hea

t


Interdependencies in the energy system

Har

d co

alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Ste

am

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PK

M

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

tAt optimal solution: • Equilibrium between electricity supply and demand

Changes in the system (e.g. phase-out of nuclear)yield new equilibrium e.g.:

1) Missing nuclear substituted by coal (or natural gas, renewables in CO2 reduction scenario)

2) Increase in electricity price (and CO2 certificate price)3) Substitution of electricity in the end-use sectors


Interdependencies in the energy system

Har

d co

alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Ste

am

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PK

M

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t


28 29 30 31 32

Har

d co

alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Stea

m

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PKM

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t

2005

Dynamic model

Har

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alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Stea

m

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PKM

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t

2010

Har

d co

alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Stea

m

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PKM

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t

2015

Har

d co

alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Stea

m

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PKM

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t

2020H

ard

coal

Lign

ite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Stea

m

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PKM

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t

2025

Har

d co

alLi

gnite

Oil

Nat

ural

gas

Bio

mas

s Ele

ctric

ity

Die

sel

Gas

olin

eG

as

LH2

Stea

m

Roo

m h

eat

War

m w

ater

Roo

m h

eat

War

m w

ater

GD

PTK

M

PKM

Pro

cess

hea

t

Gas heating

Oil heating

Elc. heating

Local heat grid

Gas water boiler

Elc. water boiler

Room heat boilers


Industrial boilers

LH2 car

Busses

Gasoline car

Gasoil car

Elc. heat pump

Warm water boilers

Trucks

Cok

e

Coal processing

Refinery

Gas processing

Coal cond. PP

Lignite cond. PP

Coal IGCC PP

Gas CC PP

Wind converter

Coal CHP

Coal CHP

Gas CC CHP

Biomass CC CHP

Electrolysis


CH

2

Win

d


Area Wind

Residual wood

Gas import

Gas resources

Coal import

Coal resources

Oil resources

Oil import

Lignite resources

Industry

Transport

Commercial

Residential

Elec sector

CHP sector

Primaryenergysupply

Conversionsector

End-usesectors

Dis

trict

Hea

t

2030

03 04 05 06 07 08 09 10 11 12 13 14 15 16 17 18 19 20 21 22 23 24 25 26 27

Model horizon

Milestoneyear

Period


Objective function: List of cost components● Discounted sum of the annual costs minus revenues:

+ Investment costs

+ Costs for sunk material during construction time

+ Variable costs

+ Fix operating and maintenance costs

+ Imports

+ Taxes

+ Surveillance costs

+ Decommissioning costs

- Subsidies

- Exports

- Recuperation of sunk material

- Salvage value

● Distinction between technical and economic lifetime

● General discount rate (discounting to base year) and technology specific discount rate (calculating annuities)

● Investment and decommissioning lead-times

Construction

Operation

Decommissioning

Operation

Decommissioning

Construction


Model formulation of TIMES

Minimizing discounted system costs= Sum of • Import-/Extraction costs, • variable and fix OM costs,• Investment costs,• …

Transformation relationship(→→→→ e.g. Efficiency relationship for power plant)

Energy and emission balances

Capacity-activity constraint(→→→→ e. g. available capacity limits elec gen of power plan t)

Peaking constraint(→→→→ Ensuring reserve capacity at peak load)

Scenario specific constraints(→→→→ e. g. bound on CO2 emissions, quota for renewables)

Share constraints on input/output side of technology (→→→→ e.g. max. ratio of electricity to heat for CHP)

Storage equations (e.g. pump storage)

Cumulated constraints over time(→→→→ e. g. available fossil resources)

Objectivefunction:

Model equations(auto-generated):

Cost data

Efficiencies

Full load hours

Emission factors

Demand

…

Input data

Energy/Emission flows

New capacities

System Costs, Prices

Decision variablesResults

Load curve equations


The Pan-European model (TIMES PanEU)

● PEM is a, 30 region (EU 27 + NO, CH, IS) partial eq uilibrium energy systems, technology oriented bottom-up model.

● Time horizon: 2000-2050

● 12 time slices (4 seasonal, 3 day level)

● GHG: CO2, CH4, N2O, SF6

● Others pollutants: SO2, NOx, CO, NMVOC, PM2.5, PM10

● The database integrates results of LCI and specific Damages with the aim to integrate the treatment of Externalities in the optimization procedure


The Pan-European Model (2)● SUPPLY: Explicit modeling of reserves, resources, e xploration and conversion

● Electricity:

1. Public electricity plants, CHP plants, heating plan ts, auto-producers

2. Country specific renewable potential and availabili ty

(onshore / offshore wind, geothermal, biomass, sola r, hydro)

3. Country specific characterization of conversion tec hnologies (in-use and new)

● DEMAND: is based on a simulation routine linked wit h GEM-E3 /NEWAGE

1. Agriculture

2. Industry: Energy intensive industry (iron and steel , aluminum, copper, ammonia and chlorine, cement, glass, lime, pulp and paper), Other industries

3. Residential and Commercial: Space heating/cooling, water heating, appliances and others)

4. Transport: Passenger, Freight (different transport modes: cars, buses, motorcycles, trucks, passenger trains, freight trai ns) Air, Navigation.

5. Country specific characterization of end-use techno logies


Regional Coverage Pan-European TIMES model


The Environment of the Energy Transformation Sector in TIMES PanEU

Fuel Production Energy Transformation Energy Consumption

• Reserves, quantitiesand costs of domesticenergy carriers

• Electricity, district heatand process heattransformation

• Sektors: Residential, Commercial, Industry, Transport, Upstream

• Import and export costpotential curves

• Three electricity gridlevels with losses and transmission costs

• Demand for effectiveenergy and productiongoods and transportdemand

• Refiniery processes • Public main activityproducers and industrialautoproducers

• Demand projectionfrom equilibrium model

• Emissions of fueltransformation

• Endogenouselectricity trade

• Energy savingpotentials


Regions in TIMES PanEU and planned Interconnection Extensions

950 MW

250 MW

500 MW

1400 MW

600 MW

2330 MW

1200 MW700 MW

1400 MW

1800 MW

900 MW

1800 MW

600 MW

200 MW

1000 MW

800 MW

600 MW

110 MW600 MW

500 MW700 MW

1320 MW

European Priority Projects

20101320UKNL

2015400FRBE

20091200FRES

20131000LTPL

2011800SIIT

2009900CZAT

2012500DKDE

YearP in MW


Interregional Electricity Trade in TIMES PanEU● Endogenous trade between Regions

� Bidirectionale trading processes � no simultaneous import and exportbetween regions in the same time slice

� Interconnection capacities according to ETSO

� Trade driven by marginal electricity generation costs per time slice and transmission costs (incl. losses)

� Limitted trade in peak time slice, since import capacities not secure(auctioning of interconnection capacities at various European borders)

● Exogenous trade with non-EU countries

� e. g. Poland – Ukraine

� constant trade quantities over modeling horizon at 2005 level


Energy Generation Units in TIMES PanEUExisting Capacities

• Clusterd by fuel and technologies for publicand industrial generation units

• Country specific decommissioning curves

Commissioning Capacities

• Technology database for public and industrial power plants, CHP and heatingplants

• Commisssioning of electricity gernerationunits in industry sector as CHP plants withcoupled production of process heat and steam

• Country specific restrictions concerning fueluse and unit size of power plants

• Nuclear phase out in DE, BE, SE, ES, NL as well as commissining of new capacity onlyin coutries with existing nuclear capacity(except PL)

• Minimum electricity quantities fromrenewable energy resources accordingnational policies

0

100000

200000

300000

400000

500000

600000

700000

800000

2000 2005 2010 2015 2020 2025 2030 2040 2050

Inst

alle

d ne

t Cap

acity

[MW

]

OtherWindNatural GasOilLigniteCoalNuclearHydro

Decommissioning Curve EU-27+CH+NO+IS


Technology Database – New Public Fossil Power Plants (excerpt)

Hard Coal

• PCC condensing 350 / 600 / 800 MW

• PCC CCS Post Combustion 560 MW

• IGCC 450 MW

• IGCC CCS 425 MW

• Oxyfuel 600 MW

• Extraction CondensingCHP 200 / 500 MW

• IGCC CHP with CCS

Lignite

• PCC condensing 965 MW

• PCC CCS Post Combustion 560 MW

• IGCC 450 MW

• IGCC CCS 425 MW

• Oxyfuel 760 MW

• Extraction CondensingCHP 500 MW

Natural Gas

• CC 420 / 800 MW

• CC with CCS 475 MW

• Gas Turbine 130 MW

• CC CHP 50 / 100 / 200 MW

• CC CHP with CCS 200 MW

• Internal Combustion smallCHP 0.01 / 0.2 / 2 MW

• Fuel Cell MCFC 0.5 MW

• Fuel Cell SOFC 1 MW


CO2 Storage Potentials of selected European Countries

15000

13000

1600

2200

23000 - 43000

16000

Mt CO2

Aquifers 1

590 – 860France

74513005UK

91563453Norway

5700 - 397001090754Netherlands

017Greece

44002227103Germany

452176Denmark

Mt CO2Mt CO2Mt CO2

Coal Seams 2Gas Fields 1Oil Fields 1

Sources: 1 GESTCO 2004, 2 Recopol 2006

• Total Europe: 122 Gt CO2

• Saline aquifers 54%

• Depleted oil and gas fields 32%

• Enhanced coal bed methan recovery 14%


Technology Database – Renewable Power Plants(excerpt)

Biomass / Biogas

• Internal combustion engines biogas

• Fuel cell biogas

• Condensing CHP wood, straw

• Internal gasification wood

• IGCC CCS Biomass

Hydro

• Run of river small / medium / large

• Dam storage large

• Pump storage

Wind and Solar

• Wind onshore (differentiated by three wind classes)

• Wind offshore

• Solar PV (roof and plant size)

• Solar thermal

Other Renewable

• Geothermal Hot dry rock

• Geothermal Steam turbine

• Tidal stream generator

• Wave energy converter


Hydro small + large Wind onshore Wind offshore Geothermal Photovoltaic Solarthermal Waste Biomass gas / liquid Biomass solid Tide + Wave

„Hot Spots“ of Renewable Energy Production in EuropeGermany

United Kingdom

Spain

Sweden

0

50

100

150

200

250

300

350

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Ann

ual E

lect

ricity

Pro

duct

ion

[TW

h]

0

50

100

150

200

250

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Ann

ual E

lect

ricity

Pro

duct

ion

[TW

h]

0

50

100

150

200

250

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Ann

ual E

lect

ricity

Pro

duct

ion

[TW

h]

0

50

100

150

200

250

2000 2005 2010 2015 2020 2025 2030 2035 2040 2045 2050

Ann

ual E

lect

ricity

Pro

duct

ion

[TW

h]


● Iron&Steel

● Aluminium

● Copper

● Cement

● Ammonia

● Chlorine

● Lime

● Glass

● Pulp&Paper

Energy intensive Industry● Other nonferrous metals

● Other chemicals

● Other non-metallic minerals

● Other Industries

Other Industries

General structure of the industry


● Standard structure

● Mix of 5 main energy uses (Steam, Process Heat, Machine Drive, Electrochemical, Others)

● Fuel demand (PJ)

● Demand based on a simulation routine linked with GEM-E3 / NEWAGE

● Process orientated Reference Energy System (RES)

● Demand of final products in natural units (Mt)

● Demand based on a simulation routine linked with GEM-E3 / NEWAGE

Energy intensive Industry Other Industries

General structure of the industry


Energy intensive Branches: Iron&Steel

• Finishing process Finished steel

• Blast Oxygen Furnace regular (base; CCS),

• Blast Oxygen Furnace scrap

• Electric arc furnace, EAF for DRI

• Cast iron cupola

Crude steel

• Iron blast furnace (base; direct coal injection); COREX, Sponge Iron for DRI, Cyclone Converter Furnace

Row Iron

• Pellet productionPellet production

• Sinter productionSinter production

Available technologiesProcess step


IIS

Finishing Processes

BY

Finishing Processes

BY

Electric Arc Furnace BY/ adv

Cast Iron Cupola adv

Blast OxygenFurnace

Regular BY/ adv

Argon Oxygen Furnace AOD

regular BY/ adv

BF

G

CO

KE

LCLP

G

OX

YQ

LIR

FC

SC

R

GA

SH

TH

RIR

GA

SB

FG

BF

S

DIR CS

T

LFO

, HF

O, G

AS

ELC

, CO

K, C

OG

, BF

G,

LPG

, HT

H, C

OA

Electric Arc Furnace for

DRI adv

HT

H

BF

GC

OK

ELC

HF

O

CO

A

OX

YP

LT

SN

TG

AS

CO

K

CO

GE

LC

OR

E

Source:Oxygen

Source:Quick Lime

Source:Scrap Iron

Source:Ore

Iron Blast Furnace

BY

Iron Blast Furnace

adv

Iron Blast Furnace direct coal injection

Iron Blast Furnace with CCS

Iron Corexadv

Ferro Chrome Smelting Furnace

Blast Oxygen Furnace Scrap

BY/ adv

Pellet Production

BY/ adv

Sinter Production

BY/ adv

Iron Cyclone Convertor Furnace

Sponge Iron for DRI

adv/ with CCS

Iron&Steel

COK-Coke; Gas- Natural Gas; COG- Coke-Oven Gas; COA- Hard coal; BFG- Blast Furnace Gas; ELC- Electricity; LPG- Liquefied Petroleum Gas; OXY- Oxygen; HFO- Heavy Fuel Oil; LFO- Light Fuel Oil; HTH- Higth Temp. Heat; RIR- Raw Iron; SCR- Scrap Iron;

RFC- Ferrochrome; QLI- Quick Lime; SNT- Sinter; PLT- Pellet; CST- Crude Steel; ORE- Ore; IIS- Iron and Steel Demand; DIR- DRI Iron; BFS- Blast Furnace slag


Energy intensive Branches: Paper&Pulp

• High quality production process Production of high quality paper

• Low quality production process Production of low quality paper

• Mechanical pulp production

• Chemical pulp production

• Recycling pulp production

Pulp production

Available technologiesProcess step


Oxy

gen

Sod.

Hyd

r.

Proc

ess

Hea

t

Source Paper: Sodium

Hydraxide

Source Paper: Wood

Source Paper: Recycled

Low Quality Paper Production

BY

Source Paper: Gypsum

Source Paper: Kaolin

Recycling Pulp Production adv

Rec

ycle

d

Pulp

Kao

lin

Gyp

sum

Hig

h T

emp.

Hea

t

Liq

uefi

ed

Petr

oleu

m G

as

Nat

ural

Gas

Ele

ctri

city

Bio

mas

s

Bla

ck L

iquo

r

Woo

d

Hig

h T

emp.

H

eat


adv.


Adv Drives

High Quality Paper Production

adv.

Low

Qua

lity

Pape

r D

eman

d


Adv Drives.

Hig

h Q

ualit

y Pa

per

Dem

and

Rec

ycle

d

Nat

ural

Gas

Ele

ctri

city

Source Paper: Oxygen

Example RES: IPP

Chemical Pulp Production BY

Chemical Pulp Production adv.

Source Paper: Recycled

Mechanical Pulp Production adv.

Mechanical Pulp Production Airless

drying

Recycling Pulp Production BY

Mechanical Pulp Production BY


BY


Heat supply in industry sector

● Public district heat

● Industrial CHPs

● Boiler (modeled as boilers for branches (BY) and generic industrial boiler (> 2000)

● Kilns (for extra high temperature) [separate heat commodity]

Possibilities of HEAT supply


Residential and Commercial Sectors

● Space Heating

● Water Heating

● Space Cooling

● Lightning

● Cooking

● Refrigeration

● Public Lightning

● Other Electric

● Other Energy

COM Demand categories

● Heat pumps, Fuel Cells, Biomass based Heating Systems, Energy Saving Lamps, Energy Saving Options (Improved Building Isolation)...

Technology options (examples)

● Space Heating

● Water Heating

● Space Cooling

● Lightning

● Cooking

● Refrigeration

● Cloth Washing

● Cloth Drying

● Dish Washing

● Other Electric

● Other Energy

RSD Demand categories


Structure of the Transport Sector in the TIMES Pan EU Model

TransportSector

Truck MotoCycle

Rail AviationBusCarNavi-

gation

PassengerLight

Freight

Passenger

Inter-national

Domestic

Long

Dis

tanc

e T

rave

l

Sho

rt D

ista

nce

Tra

vel

MaritimeNavigation

InlandNavigation

InterCity

Urban


Implemented Transport TechnologiesFuel/Vehicle Car Bus Truck Motocycle Rail Aviation Navigat ion

Gasoline +* +* +* +* +hybrid +* +*plug in hybrid +*

Diesel +* +* +* +* +hybrid +* +* +*plug in hybrid +*

Ethanol (E85) + + +hybrid + +plug in hybrid +

Biodiesel + + + +FT-Diesel (BTL/GTL/CTL) + + + + +Electricity + + +LPG +Natural Gas/Biogas + + +

hybrid + +plug in hybrid +

Methanol IC + + +Methanol FC +Dimethyleter + + +Kerosene +Heavy fuel oil +Hydrogen (g) IC +Hydrogen (g) FC + + +

hybrid + + +Hydrogen (l) IC ++ implemented

* Blending with biofuels or synthetic fuels possible


Objective and Scope

● Proposed target distinctions for ETS and Non-ETS

● Effort sharing proposals between member states

● Role of the RES target, including its national allocation

Assessment of the…

● EU Emission Trading Scheme: -21% GHG in 2020 compared to 2005

● Non-ETS: -10% GHG in 2020 compared to 2005

● RES: 20% of final energy consumption in 2020

The Energy and Climate Package aims at achieving 20- 20-20-2020 via

….. and what happens beyond ?


Optimal burding sharing in 2020

-3%

-49%

-32% -33%

30%

-21%

9%

-35%

0%

-19%

-35%

28%

-45%

-24%

-38%

-31%-31.5%

-3.9%

16.3%

-38.5%

3.3%

-44.5%

25.7%

-51.5%

-26.9%

-49.3%

-29.1%

-6%

-17%-19%

-27%

5.7%

36.2%

-29.5%

29.0%

-35.9%-35.4%

-50.5%

-1.9%

-14.7%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

AT BE BG CZ DE DK ES FI FR GR HU IE IT NL PL PT RO SE SK UK

GH

G E

mis

sion

com

pare

d to

200

5

EC Proposal TIMES


-3%

-49%

-32% -33%

30%

-21%

9%

-35%

0%

-19%

-35%

28%

-45%

-24%

-38%

-31%

-3.9%

16.3%

-38.5%

3.3%

-44.5%

25.7%

-51.5%

-26.9%

-49.3%

-29.1%-27%

-19%-17%

-6%

-31.5%

-14.7%

-1.9%

-50.5%

-35.4% -35.9%

29.0%

-29.5%

36.2%

5.7%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

40%

50%

AT BE BG CZ DE DK ES FI FR GR HU IE IT NL PL PT RO SE SK UK

CO

2 em

issi

ons

com

pare

d to

Kyo

to (

2020

-199

0)

EC Proposal TIMES Before

Optimal burding sharing in 2020 (and before theeconomic crises)


-24.4% -24.7%

-31.8%

-50.1%

-21.3%-22.6%

-5.7%

-14.8%

-19.5%

-27.2%

-21.5%

-38.2%

-25.0%

-37.9%

22.1%

-1.5%

7.5%

-6.3%

4.2%

-3.4%

-7.3%-4.7%

-8.8%-11.6%-11.3%

-9.0%-8.4%

-18.6%

-1.2%

-24.1%-27.3%

-44.8%

-19.4%

-13.3%

-7.4%-4.3% -5.4%

-14.0%

8.3%

17.0%

-11.5%-8.6%

-60%

-50%

-40%

-30%

-20%

-10%

0%

10%

20%

30%

AT BE BG CZ DE DK ES FI FR GR HU IE IT NL PL PT RO SE SK UK EU-27

GH

G E

mis

sion

com

pare

d to

200

5

ETS Non ETS

Optimal share between ETS and Non-ETS reduction 2020

EU Target


Optimal RES Allocation vs. EU-Targets

34.0%

13.0%

16.0%

13.0%

30.0%

20.0%

38.0%

23.0%

13.0%

17.0%

14.0%15.0%

31.0%

24.0%

49.0%

14.0%15.0%

36.8%

10.3%

23.5%

18.6%

41.8%

16.5% 16.9%

22.4%

12.4%

7.8%

24.7%26.8%

42.1%

53.9%

21.0%

10.6%

18.0%18.0%

21.2%

30.0%

17.3%

0%

10%

20%

30%

40%

50%

60%

AT BE BG CZ DE DK ES FI FR GR HU IT NL PL PT RO SE SK UK

Sha

re o

f Ren

ewab

leE

nerg

y at

FE

C

EC-Targets 2020 BEST EU-27 Average


Dependency of the CO 2 reduction potential on the spec. CO 2 certificate price

0

20

40

60

80

100

120

140

160

180

200

0 500 1000 1500 2000 2500 3000

Reduction of CO 2 emissions in [Mill. t CO 2]

Spe

c. C

O2-

certi

ficat

e pr

ices

in [€

/t C

O2]

2040

2030

2025


Scenario analysis

1. Baseline case (REF)• No emission reduction measures• Nuclear phase out according policy of respective EU countries• Minimum renewable energy use

2. BEST climate policy on global trade• EU 20-20 target• GHG emission reduction from 2020 linear to -39% by 2050

3. Second Best• EU 20-20 target• GHG emission reduction from 2020 linear to -50% by 2050

4. Second Best VAR • EU 20-20 target• GHG emission reduction from 2020 linear to -50% by 2050 • Limit the ETS part to stress the Non-ETS sector


0

1000

2000

3000

4000

5000

6000

7000

Sta

tistic

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

2000 2010 2020 2030 2040 2050

Em

issi

ons

of C

O2

[Mt]

Sequestrationof CO2

Transport

Households,commercial,AGR

Industry

Conversion,production

Scenario Comparison, EU27: Carbon Emissions in Mt CO2/yr


0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000

5500

Sta

tistic

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

2000 2010 2020 2030 2040 2050

Net

ele

ctric

ity g

ener

atio

n [T

Wh]

Others / Wastenon-ren.OtherRenewablesBiomass /Waste ren.Solar

Wind

Hydro

Nuclear

Natural gas

Oil

Lignite

Coal

Scenario Comparison, EU27: Net Electricity Production


0

200

400

600

800

1000

1200

1400

GH

G_3

9G

HG

_50

GH

G_5

0_E

TS

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

BA

UB

ES

TS

econ

d B

est

Sec

ond

best

VA

R

2000 2010 2020 2030 2040 2050

Net

inst

alle

d C

apac

ity [G

W]

Other not specified

PV

Wind

Hydro

Biomass solid / Waste

Nuclear

Gas CC CO2 Seq.Oxyfuel

Gas CC CO2 Seq.Pre Comb.

Gas CC

Gas not specified

Oil

Lignite IGCC CO2 Seq.

Lignite IGCC

Lignite ST CO2 Seq.Oxyfuel

Lignite ST CO2 Seq.Post Comb.

Lignite ST

Lignite not specified

Coal IGCC CO2 Seq.

Coal IGCC

Coal ST CO2 Seq.Oxyfuel

Coal ST CO2 Seq.Post Comb.

Coal ST

Coal not specified

Scenario Comparison, EU27: Net electricity generation installed capacity [GW]


Scenario Comparison, EU27: Net Electricity Imports

-250

-200

-150

-100

-50

0

50

100

150

200

250

BA

UB

ES

TS

econ

d B

est

BA

UB

ES

TS

econ

d B

est

BA

UB

ES

TS

econ

d B

est

BA

UB

ES

TS

econ

d B

est

BA

UB

ES

TS

econ

d B

est

2000 2010 2020 2030 2040 2050

Ele

ctric

ity n

et im

port

s [T

Wh]

East Europe

Baltic states

Scandinavia

Greece

Italy+Slovenia

Germany

Alps (AT, CH)

Benelux

France

Iberia

UK+Ireland


Scenario Comparison, EU27: Electricity Prices

0

10

20

30

40

50

60

70

80

90

2000 2010 2020 2030 2040 2050

year

Ele

ctri

city

Pri

ce in

[€/M

Wh]

BAU

BEST

Second Best

Second Best Var


Scenario definition and white certificates

▪ -21% CO2 reduction till 2020 in ETS sector + 450ppm target till 2050

▪ Reduction target Final Energy Consumption [white certificates for FEC]

FEC_450ppm

▪ Business as usual [Reference case]

▪ -21% CO2 reduction till 2020 in ETS sector

REF


▪ Reduction target Final Energy Consumption [white certificates for FEC]

FEC


▪ Reduction target Primary Energy Consumption [white certificates for PEC]

PEC

▪ -21% CO2 reduction till 2020 in ETS sector + 450ppm target till 2050

▪ Reduction target Primary Energy Consumption [white certificates for PEC]

PEC_450ppm

DescriptionScenario


Net electricity generation by technology (EU-27)

● FEC: Increase of public generation from

condensing power

plants/ decrease auto

production (industry)

● PEC: Increase public CHP/ decrease public

condensing plants (total

decrease)

● 450ppm: Increase of electricity generation in

both scenarios

Key effects:

0

500

1000

1500

2000

2500

3000

3500

4000

4500

5000S

tatis

tic

RE

F

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

2000 2010 2020 2030 2050

Net

ele

ctric

ity g

ener

atio

n [T

Wh]

public cond. public CHP autoproducer CHP autoproducer cond


Final energy consumption (EU-27)

● FEC: less renewables

●450ppm: in both

scenarios higher share

of electricity and

renewables, less oil

● PEC: just small changes compared to

scenario REF (shift to

district heat, less renewables)

Key effects:

0

10000

20000

30000

40000

50000

60000S

tatis

tic

RE

F

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

2000 2010 2020 2030 2050

Tot

al fi

nal e

nerg

y co

nsum

ptio

n [P

J]

Coal Petroleum productsGas ElectricityHeat RenewablesWaste Others (Methanol, Hydrogen)


Reduction final energy consumption by sector (EU-27) [scenario FEC compared to REF]

● Sector view: reduction mainly in

residential and industry

(main driver: space and process heat supply)

● 2025: also clear

reduction in commercial

sector

● Transport: no clear reduction before 2040

Key effects:

0%

5%

10%

15%

20%

25%

30%

2000 2005 2010 2015 2020 2025 2030 2040 2050

Red

uctio

n of

fina

l ene

rgy

cons

umpt

ion

[%]

Industry Commercial HouseholdsTransport Agriculture Total


Burden sharing: Reduction of primary energy consumption [scenarios compared to REF in 2020]

● Key driver: the main

influence has the

conversion/ production

sector, especially the electricity generation

● Burden sharing:according to changes in

electricity generation (less nuclear/coal); also

changes in electricity

trade

Key effects:

-25%

-20%

-15%

-10%

-5%

0%

EU27AT BE BG CY CZ DE DK EE ES FI FR GR HU IE IT LT LV MT NL PL PT RO SE S I SK UK

Red

uctio

n of

prim

ary

ener

gy c

onsu

mpt

ion

[%]

PEC PEC_450ppm


Final Energy Consumption (CZ)

0

200

400

600

800

1000

1200

1400

1600

Sta

tistic

RE

F

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

2000 2010 2020 2030 2050

Tot

al fi

nal e

nerg

y co

nsum

ptio

n [P

J]

Coal Petroleum productsGas ElectricityHeat RenewablesWaste Others (Methanol, Hydrogen)


FEC Industry (CZ)

0

100

200

300

400

500

600

Sta

tistic

RE

F

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

2000 2010 2020 2030 2050

Fin

al e

nerg

y co

nsum

ptio

n In

dust

ry [P

J]

Coal Petroleum products GasElectricity Heat RenewablesWaste Others (Methanol, Hydrogen)


Net electricity generation (CZ)

0

20

40

60

80

100

120

140

Sta

tistic

RE

F

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

2000 2010 2020 2030 2050

Net

ele

ctric

ity g

ener

atio

n [T

Wh]

Coal Lignite OilNatural gas Nuclear HydroWind Solar Biomass / Waste ren.Other Renewables Others / Waste non-ren.


0

20

40

60

80

100

120

140

160

Sta

tistic

RE

F

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

RE

F

FE

C

FE

C_4

50pp

m

PE

C

PE

C_4

50pp

m

2000 2010 2020 2030 2050

Em

issi

ons

of C

O2

[Mt]

Conversion, production Industry Households, commercial, AGR Transport

CO2- Emissions (CZ)


Conclusions

● The development of the Czech energy system is not i ndependent of the EU27 policy and the energy policy in the other member st ates.

● The economic development or in general the requeste d demand influence on the same level the future energy system as the tech nology development and availability. A linkage between a CGE model can fil l this gap.

● In the period between 2030 and 2050 the level of th e GHG reduction target for the EU27 depends on the possibility of cost effecti ve world wide reduction potentials. In general additional policy measures w hich are reducing the flexibility of the energy systems are not cost effi cient.


Thank you for your attention !

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9 Assessing the Impacts by Pan-European TIMES Model...Bottom-up models Top-down models Attempt to...

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