From long term global energy system to national energy ... · IAEA From long‐term global energy system research to national energy analyses and planning Dr. H‐Holger Rogner International

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From long‐term global energy system research to national energy analyses and 

planning

Dr. H‐Holger RognerInternational Institute for Applied Systems Analysis (IIASA), Austria

Royal Institute of Technology (KTH), Stockholm, Sweden

IAEA

Modelling energy system transformation at IIASA Origin dates back to 1974

Spatial focus: Global – world segregated into 11 regions

Temporal focus:  Long‐term: 50 to 100 years plus 

Objectives:  Analysis of long‐term demand & supply strategies under different 

technology & resource futures  Development of robust technology strategies and related investment 

portfolios to meet a range of policy objectives, and Appreciation of uncertainty

Several models – demand & economic development, supply, resources, impacts

Primus inter pares: MESSAGE (Model of Energy Supply Systems And their General Environmental Impact)

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NAM PAO

WEU

EEU

FSU

MEA

AFR

LAM

SAS

PAS

CPA

1 NAM North America 2 LAM Latin America & The Caribbean3 WEU Western Europe 4 EEU Central & Eastern Europe

5 FSU Former Soviet Union6 MEA Middle East & North Africa7 AFR Sub-Saharan Africa8 CPA Centrally Planned Asia & China

9 SAS South Asia10 PAS Other Pacific Asia 11 PAO Pacific OECD

OECD

REFS

ALM

ASIA

Geographical resolution – the “Regions”

IAEA

Air pollution emission coefficients & abatement costs

IIASA Integrated Assessment Framework

G4MSpatially explicit 

forest management 

modelGLOBIOMIntegrated agricultural, bioenergy and forestry model

MESSAGESystems engineering model (all GHGs, all energy sectors, water)

Consistency of land‐cover changes (spatially explicit maps of agricultural, urban, 

and forest land)

Carbon and  biomass price

Agricultural and forest bioenergy potentials,land‐use emissions and mitigation 

potential

MAGICCSimple climate 

model

GAINSGHG and air pollution 

mitigation model

emissions

Demandresponse

Iteration

MACROAggregated 

macro‐economic model

Energy service prices

Socio‐economic drivers

EPICAgricultural crop model

AccessFuel choice model 

for cooking

Transport Module Modal split,

cost & value of time

Scenario Storyline• demographic change• economic development• technological change• policies

Socio‐economic drivers

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Characterization of MESSAGE

Linear and mixed integer programming (LP & MIP) model Continuous variables for linear processes Integer or binary variables for unit commitment and decisions

Equations to reflect operational constraints Technical Legal Environmental

Optimization target (objective) minimize system cost maximize profit minimize import dependence etc.

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An Energy “Chain”

Oil extractionCoal import

Power plant Refinery

End user

PRIMARY SECONDARY FINAL USEFUL

Conversion ConversionTransmission & Distribution 

OilNatural gasCoalHydroSolarUranium

Diesel                Kerosene               Gas                         ElectricityHeatCoal  

Low temp heatHigh temp heatColdLightMechanical  energy

T&D Network 

Diesel                Kerosene              Gas                         ElectricityHeatCoal  

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MESSAGE: Model for Energy Supply System Alternatives and their General Environmental Impacts

OUTPUT

MESSAGE

INPUT

Energy systemstructure (including vintage of plant and equipment)

Base year energyflows and prices

Energy demandprojections (e.g. MAED)

Technology and resource options & their techno‐economic performance profiles

Technical andpolicy constraints

Primary and final energy mix Electricity generating mix Capacity expansion/retirement Emissions & waste streams Resource use (energy, water, land, 

etc.) Trade & import dependence Investment requirements Prices

TWh

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Schematic illustration of GEA pathways

End‐use transformation

Supp

lytran

sformation

GEA Supply GEA EfficiencyGEA Mix

Supply flexibility

Source: Riahi et al, 2011

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GEA‐Supply

2000 2020 2040 2060 2080 2100

Prim

aryen

ergy, EJ p

er year

0

500

1000

1500

2000

2500

Rapid up‐scaling of all options, including renewables and nuclear

CCS needed as transitional technology& BioCCS for negative emissions

Modest efficiency focus 

Supply‐side Focus(= high demand‐side flexibility)

Source: Adapted from Riahi et al, 2011

Coal wCCSCoal woCCSBiomass wCCSBiomass woCCS

NuclearGas wCCSGas woCCS

Oil

EfficiencyGeothermalSolarWind

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2500GEA‐Efficiency

2000 2020 2040 2060 2080 2100

Prim

ary en

ergy, EJ p

er year

0

500

1000

1500

2000Efficiency & intensity improvements, process and behavioral change

Fossil CCS (optional bridging technology)

Bio‐CCS & negative emissions (long‐term)

Phase‐out of oil in the medium term(necessary)

Coal wCCSCoal woCCSBiomass wCCSBiomass woCCS

NuclearGas wCCSGas woCCS

Oil

EfficiencyGeothermalSolarWind

Efficiency & Demand‐side Focus(= high flexibility for supply)

~50% renewables by 2050

No expansion of nuclear (choice)

Source: Adapted from Riahi et al, 2011

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Zooming from global to national

National (sustainable) energy development objectives Long‐term regional/global averages provide indications at best National specificity

• National energy security • Indigenous resources• Detailed representation of the existing infrastructure (vintage, 

performance, reliability)• Variability of demand• Menu of technology options• Investment, finance, market structure and subsidies• Affordability & access• Demand side vs supply side considerations• Local generating costs

MESSAGE adapted to meet national and subnational requirements

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International Atomic Energy Agency (IAEA)

MESSAGE adopted in 1998 (replacement of WASP used since the early 1970s)

IAEA provides energy planning services to its MS Training of MS experts in the use of MESSAGE  Model distribution (to governmental institutions) E‐Learning, E‐Assistance & help desk Note: Data & assumptions are the responsibility of MS

Objective: Capacity building in energy analysis & comprehensive energy planning

Decision support system at the national level Essential for a national decision to introduce nuclear 

power

IAEA

Load curves

Variability of demand: electricity, heat, natural gas Intermittency of renewables Transmission

0

5

10

15

20

25

30

35

0 1,000 2,000 3,000 4,000 5,000 6,000 7,000 8,000

Hours

GW

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Example: Oil exporting country in the region

Transformation of the national energy system Associated gas on the decline Subsidized energy & water not sustainable Galloping electricity & water demands

No compromise on energy security Use current & future oil revenues to finance 

transition Explore different futures and technology options Understanding future uncertainties Communication tool (transparency)

IAEA

Model representation of load curves

 0

1 000

2 000

3 000

4 000

5 000

6 000

7 000

8 000

9 000

10 000

 0

1 00 0

2 00 0

3 00 0

4 00 0

5 00 0

6 00 0

7 00 0

8 00 0

9 00 0

10 000

0 50 100 150 200 250 300 350

MW

DayActual average daily profile Time steps & load pattern modelled

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Investments Fuel costsWaste/decom

Reliability Secutiy Environment Material Acceptance

Wind 1,200 0 15 low intermittend

high very good very high high

Coal (imported fuel)

1,800 4 80base load / intermediate

very high

low high low ‐ high

IGCC (oil) 1,900 0.5 ‐ 12 25base load / intermediate

very high low medium high

Nuclear 4,800 0.7 1,800 base load high very good high low

Gas combined cycle  turbine

1,350 1 ‐ 5 40base load / intermediate

medium medium low high

Gas turbine  400 1 ‐ 6 12 peak low medium low high

Concentrated solar

4,200 0 50 low intermittend

high good high medium

End‐use efficiency 225 0 1 ‐

very high excellent low mixed

Comparative assessment of options

How to interpret the results?

How to combine these criteria?

How

 to com

pare th

ese alternatives?

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Generating capacity – Business‐as‐usual

 0

5 000

10 000

15 000

20 000

25 000

30 000

35 000

40 000

2005 2010 2015 2020 2025 2030

MW

Wind

CSP

SolarPV

Nuclear

CCGT‐MSF

IGCC‐MSF

Steam‐MSF

Steam

IGCC

CCGT

OCGT

GT_plan

CC_plan

Pre‐2006

IAEA

Generating capacity – Transformation (TR)

 0

5 000

10 000

15 000

20 000

25 000

30 000

35 000

40 000

2005 2010 2015 2020 2025 2030

MW

Wind

CSP

SolarPV

Nuclear

CCGT‐MSF

IGCC‐MSF

Steam‐MSF

Steam

IGCC

CCGT

OCGT

GT_plan

CC_plan

Pre‐2006

IAEA

Difference in capacities between BAU and TR 

‐15 000

‐10 000

‐5 000

 0

5 000

10 000

15 000

20 000

25 000

2015 2020 2025 2030

MW

Wind

CSP

SolarPV

Nuclear

CWE_CCGT

CWE_IGCC

CWE_Steam

Steam

IGCC

CCGT

OCGT

GT_plan

CC_plan

Pre‐2006

IAEA

Difference in generation between BAU and TR 

‐ 90

‐ 70

‐ 50

‐ 30

‐ 10

 10

 30

 50

 70

 90

2015 2020 2025 2030

TWh

Imports

Wind

CSP

SolarPV

CCGT‐MSF

IGCC‐MSF

Steam‐MSF

Steam

IGCC

CCGT

OCGT

Nuclear

GT_plan

CC_plan

Pre 2006

IAEA

Fresh water supply in TR

‐ 200

 0

 200

 400

 600

 800

1 000

1 200

1 400

1 600

1 800

2005 2010 2015 2020 2025 2030

Million m

3

MSF_CCGT

MSF_IGCC

MSF_Steam

Stor_out

Stor_in

RO

Pre 2006

IAEA

Sensitivities & solution space for nuclear power

Netback ($/bbl)

77

5

3

9

10

70

40

2030

5060

Discount rate%/year

46

810

1214

1234

65

IAEA

Distribution of MESSAGE to IAEA member States

Model transferred to 102 countries by the end of 2015 

IAEA

MESSAGE has been the tool for

Numerous national electrification and energy plans

Energy policy formulation at various jurisdictional levels 

Utility capacity expansions and investment decisions

Accounting of material (energy and non‐energy) flows

Communication of energy related GHG emissions to UNFCCC

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