global energy perspectives to 2050 and beyond - tu wien · global energy perspectives to 2050 and...

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NebojNebojšša Nakia NakiććenovienoviććVienna University of Technology Vienna University of Technology xx

International Institute for Applied Systems Analysis International Institute for Applied Systems Analysis [email protected]@eeg.tuwien.ac.at

International Conference within Austrian EU PresidencyInternational Conference within Austrian EU PresidencyEnergy Paths Energy Paths –– Horizon 2050, Horizon 2050, PalaisPalais AuerspergAuersperg, Vienna , Vienna –– 6 March 20066 March 2006

Global Energy PerspectivesGlobal Energy Perspectivesto 2050 and Beyondto 2050 and Beyond

NakicenovicNakicenovic ##22 20062006

Global Energy ChallengesGlobal Energy Challenges

Access to modern forms of energy Access to modern forms of energy (a prerequisite for reaching MDGs)(a prerequisite for reaching MDGs)

Growing demand for Growing demand for energy servicesenergy services

Security and reliability of supply Security and reliability of supply

Deep CODeep CO22 and GHG reductionsand GHG reductions

Investment in R&D and deploymentInvestment in R&D and deployment

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0

500

1000

1500

2000

2500

3000

1800 1825 1850 1875 1900 1925 1950 1975 2000

Poun

ds (2

000

£)/ m

lum

en-h

ours Gaslight

Kerosene-light

Electric-light PricePrice

Energy serviceEnergy service

The Example of LightingThe Example of Lighting

SourceSource: : Fouquet&PearsonFouquet&Pearson (2003)(2003)



0

50

100

150

200

250

1900 1910 1920 1930 1940 1950

Tri

llion

lum

en-h

ours

Electric-light

Gaslight

United KingdomUnited Kingdom

Kerosine-light

0

50

100

150

200

250

1900 1910 1920 1930 1940 1950

Tri

llion

lum

en-h

ours

Electric - light

Gaslight


Kerosine-light

3






0

50

100

150

200

250

1900 1910 1920 1930 1940 1950

Tri

llion

lum

en-h

ours

Electric - light

Gaslight


Kerosine-light


0

500

1000

1500

2000

2500

3000

1800 1825 1850 1875 1900 1925 1950 1975 2000

Poun

ds (2

000

£)/ m

lum

en-h

ours Gaslight

Kerosene-light

Electric-light PricePrice

Energy serviceEnergy service





0

50

100

150

200

250

1900 1910 1920 1930 1940 1950

Tri

llion

lum

en-h

ours

Electric-light

Gaslight


Kerosine-light

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Global Primary EnergyGlobal Primary Energy

0

50

100

150

200

250

300

350

400

450

1850 1900 1950 2000

Prim

ary

Ener

gy (

EJ)

Biomass

Coal

Oil

Gas

Renewable

NuclearMicrochip

Steam motor

Gasolinetube

CommercialNuclear

Television

aviation

engine

engineElectric

Vacuum

energy

INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)

Variations of the EarthVariations of the Earth’’s Surface Temperatures Surface Temperaturefor the past 140 yearsfor the past 140 years

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Summary of Scenario CharacteristicsSummary of Scenario Characteristics

x3x3x4x4

<x1<x1x3x3

x1.5x1.5x2.5x2.5

<x3<x3x4x4

x1.5x1.5

FactorFactor

120120--160160

4040x1000x10000.040.04Mobility Mobility (km/person/day)(km/person/day)

0.30.3

1313

0.30.3

11

18001800

6.46.4

420420

3030

66

20002000 20502050FactorFactor

x20x20

x30x30

x100x100

x6x6

55--1515

COCO2 2 Emissions (Emissions (GtCGtC))

600600--10401040

Primary Energy (EJ)Primary Energy (EJ)

8585--110110

GDP (trillion 1990 $)GDP (trillion 1990 $)

99Population (billion)Population (billion)


Global Final Energy by FormGlobal Final Energy by FormIIASA IPCC SRES ScenariosIIASA IPCC SRES Scenarios

B1, A2

B1

A1

B2

A2

0

20

40

60

80

100

2000 2020 2040 2060 2080 2100

Fina

l Ene

rgy

Shar

es (%

)

B2, A1

Grids (electricity, gas, district heat, hydrogen)

Liquids(oil products, methanol, ethanol)

Solids (biomass, coal)

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NakicenovicNakicenovic ##1111 20062006 14

Carbon Reservoirs

BiomassBiomass~500 ~500 GtCGtC

SoilsSoils~1,500 ~1,500 GtCGtC

Atmosphere 800 GtC (2004)

OilOil~270 ~270 GtCGtC

N. GasN. Gas~260 ~260 GtCGtC

Unconventional Fossil Fuels15,000 to 40,000 GtC

CoalCoal5,000 to 8,000 5,000 to 8,000 GtCGtC

Source: Edmonds, 2005Source: Edmonds, 2005


Methane HydrateMethane Hydrate

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0

10

20

30

Gas CC Coal Wind Hydro Nuclear Solar-Thermal

SolarPV

ELECTRICITY COSTSC

ENTS

PER

kW

h

Source: Kheshgi, Exxon Mobil (2002)


Evolution of Global Primary EnergyEvolution of Global Primary Energy

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Global Mean Temperature ChangeGlobal Mean Temperature ChangeSix illustrative SRES scenarios, full range Six illustrative SRES scenarios, full range

s

INTERGOVERNMENTAL PANEL ON CLIMATE CHANGE (IPCC)


The Innovation Chain

• Research and Development• Demonstration projects• Early deployment (cost buy-down)• Widespread dissemination

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Brazil Brazil –– Ethanol Learning CurveEthanol Learning Curve

0

50

100

150

200

0 10 20 30

Cumulative production 106bbl

Producer price

Regression

Oil price

1978 1985 1988 1990 1995Data: Goldenberg, 1996

Cumulativesubsidy1billion $

0.6 billion $

30 % cost reductionfor each doublingof cum. production

0

50

100

150

200

0 10 20 30


Producer price

Regression

Oil price

1978 1985 1988 1990 1995Data: Goldenberg, 1996


0.6 billion $0.3 billion $ ?


0

50

100

150

200

0 10 20 30


Producer price

Regression

Oil price

1978 1985 1988 1990 1995Data: Goldenberg, 1996


0.6 billion $0.3 billion $ ?


0

50

100

150

200

0 10 20 30Cumulative production 10 6 bbl

Oil-

equi

vale

nt p

rice

$/bb

l

Producer price

Regression

Oil price

1978 1985 1988 1990 1995

Estimated


Source: Goldemberg, 1996

??$2billion“Buy-Down”

Source: Source: GrGrüüblerbler, 2002, 2002


http://www.nrel.gov/data/pix/Jpegs/06442.jpghttp://www.nrel.gov/data/pix/Jpegs/06442.jpg

UsinaUsina Santa Elisa mill in Santa Elisa mill in SertaozinhoSertaozinho, Brazil, Brazil

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0.0

0.5

1.0

1.5

0 1 2 3 4 5 6 7 8 9 10 11 12 13 14 15Number of doublings (installed capacity)

Cos

t ind

ex ($

/kW

)

0.0

0.5

1.0

1.5

Nuclear Reactors France 1977-2000

PVs Japan 1976-1995

0.1%

0.1%

50% interval

90% interval

mean learning rate(115 case studies):-20% per doubling

Technological Uncertainties: Technological Uncertainties: Learning rates (push) and market growth (pull)Learning rates (push) and market growth (pull)

COCO22 Emissions from Scenarios with Technological UncertaintyEmissions from Scenarios with Technological Uncertainty

5 10 15 20 25 30

5.5

5.0

4.5

4.0

3.5

3.0

2.5

2.0

1.5

1.0

0.5

0.0

Set of 130,000 Scenarios

GtC in 2100

Rel

ativ

e Fr

eque

ncy

in P

erce

nt

Gritsevkyi&NakicenovicGritsevkyi&Nakicenovic ##2020 IIASA 2000IIASA 2000

Optimal set of13,250 scenarios

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RENEWABLESHoffert et al., Science, 2002

Nakicenovic # 21 IIASA&VUT 2003

Existing and Planned ProjectsExisting and Planned ProjectsSleipner Project, saline formation, North SeaWeyburn, EOR, Saskatchewan, CanadaIn Salah, gas reservoir, Algeria (development)Snohvit, off-shore saline formation, North SeaGorgon, saline formation, Australia (planning)

Nakicenovic #22 Source: Sally Benson, 2003

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Source: AirbusSource: Airbus

Hydrogen Airplane DesignHydrogen Airplane Design


A Future Energy SystemA Future Energy System

Source: Source: WuppertalWuppertal, 2004, 2004

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Letter Horse Hay Agriculture Sunlight

Telegraph Steam Locomotive Coal Coal mine Coal fields

Interntet, Mobile Phone

ICE Automobile Gasoline Oil refinery Crude oil

Convergence Energy, Mobility

InformationHydrogen

Natural gas / fossilsSMR,

decarbonization

Electrolysis

Sunlight

Wind

Uranium

1770s

1870s

1970s

2070s

Energy Services Through Time

Biomass

Electricity

Electricity

Electricity

#25 Source: David Scott, 2004


Global Energy Assessment:Global Energy Assessment:Towards a more Sustainable FutureTowards a more Sustainable Future

•• The The magnitudemagnitude of the change required is of the change required is hugehuge

•• The challenge is to find a way forward The challenge is to find a way forward that addresses all the issues that addresses all the issues simultaneouslysimultaneously

•• A paradigm shift is needed: energy endA paradigm shift is needed: energy end--use efficiency, renewables, new nuclear use efficiency, renewables, new nuclear and carbon capture and storage.and carbon capture and storage.

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[email protected]@eeg.tuwien.ac.at

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