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© OECD/IEA 2013
The World Energy Model
Marco Baroni
Directorate of Global Energy Economics International Energy Agency
Paris, 20 June 2013
© OECD/IEA 2012
The global energy system, 2010 (Mtoe)
A complex energy world requires a well integrated model to capture all the interactions among markets, sectors, fuels and countries
© OECD/IEA 2012
World primary energy demand by scenario
0
5 000
10 000
15 000
20 000
1990 2000 2010 2020 2030 2035
Current Policies Scenario New Policies Scenario
450 Scenario
Mto
e
Energy demand rises by over one-third in 2010-2035 In the New Policies Scenario, underpinned by rising living standards in China, India & the Middle East
© OECD/IEA 2012
World Energy Model (WEM)
Partial equilibrium model that allows scenario analysis Detailed sectoral and regional energy demand balances Regional supply of all fuels and trade matrixes CO2 emissions from fuel combustion Investment needs in the supply and end-use technologies
Time horizon to 2035, with annual data complete update every year (e.g. in WEO 2012 the last complete data set was 2010, but
many data available for 2011 are integrated)
Regional resolution: 25 regional models of which 12 country models, including US, China, India, Japan, Russia, Brazil…
Three main modules Final Energy Consumption – Industry, Transport, Residential, Services, Agriculture,
Non-Energy Use Energy Transformation – Power Generation, Heat Production, Refinery/Petrochemicals,
Other Transformation Supply and Trade – Coal, Oil, Gas and Biomass
http://www.worldenergyoutlook.org/weomodel/
© OECD/IEA 2012
World Energy Model (WEM) overview
© OECD/IEA 2012
Change in global primary energy demand by measure and by scenario
12 000
13 000
14 000
15 000
16 000
17 000
18 000
19 000
Mto
e
2010 2015 2020 2025 2030 2035
450 Scenario New Policies Scenario Current Policies Scenario
Energy savings in 2035 CPS
to NPS NPS
to 450 Efficiency in end-uses 67% 66%
Efficiency in energy supply 5% 8%
Fuel and technology switching 12% 12%
Activity 16% 14%
Total (Mtoe) 1 479 2 404 Note: CPS = Current Policies Scenario; NPS = New Policies Scenario; 450 = 450 Scenario.
Efficiency is the single largest contributor to energy savings in achieving the New Policies Scenario and in moving beyond it, reflecting its large economic potential
© OECD/IEA 2012
Policy implications
Impact of policies under consideration on global energy trends
Role of emerging economies on global energy demand and supply
Implications of technological developments of carbon-free technologies
Exploitation of the economic energy efficiency potential, its costs and benefits
Environmental impact of energy use and the effect of policies to limit it
Competitiveness within the energy sector and among countries
© OECD/IEA 2013
Power sector modeling in the World Energy Model
Brent WANNER
International Energy Agency
Paris, 20 June 2013
© OECD/IEA 2013
World Energy Model (WEM) overview
Electricity and heat end-user prices
© OECD/IEA 2013
Power generation sub-modules
Renewables
Distributed Generation
Electricity from CHP
Desalination
Nuclear
CCS
Main driver(s)
Support, learning, potentials
Economics
Political support, economics
CO2 price, support, learning
TFC fossil fuel demand and prices
Heat demand
Water demand
Heat from CHP
Heat Plants
Heat Production
Electricity generation
Thermal plants
Transmission & Distribution
Wholesale & End-user prices
Power demand, integration of renewables
Market structure, power mix, fuel and CO2 prices, investment
© OECD/IEA 2013
Generation by plant
The module determines which plants are added and how they operate
Key Results
Effective Capacity Factors
Total installed capacity by plant
CO2 by plant type
Refurbishments
Plant Investment needs
Retrofits
Early retirements
T&D Investment needs
Renewables support
End-user prices
Additions of new plants
Investment assumptions
Fuel and CO2 prices
Efficiencies
Max Capacity Factors
Historical capacity by plant
Retirements of existing plants
Wholesale price
Fuel consumption by plant
Load curve
Electricity demand
Merit Order Dispatch
© OECD/IEA 2013
Generation by plant
The module determines which plants are added and how they operate
Key Results
Investment assumptions
Fuel and CO2 prices
Efficiencies
Effective Capacity Factors
Total installed capacity by plant
CO2 by plant type
Refurbishments
Max Capacity Factors
Plant Investment needs
Retrofits
Early retirements
Historical capacity by plant
T&D Investment needs
Renewables support
End-user prices
Retirements of existing plants
Load curve
Wholesale price
Fuel consumption by plant
Electricity demand
Merit Order Dispatch
Additions of new plants
© OECD/IEA 2013
Capacity additions mechanism
Installed capacity is greater than peak demand to allow system to cope with maintenance and unexpected outages ⇒ Capacity Margin
Plants are added each year based on demand growth, maintaining the capacity margin, replacement of retiring plants
Annual data is not enough Need for greater granularity in the year Split the load duration curve (hourly demand
ordered from biggest to smallest) in 4 blocks • Peak load • Mid load 1 and 2 • Base load
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673
110
9614
6118
2621
9125
5629
2132
8636
5140
1643
8147
4651
1154
7658
4162
0665
7169
3673
0176
6680
3183
96
GW
-
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4 000
6 000
8 000
10 000
2000 2005 2010 2015 2020 2025 2030 2035
GW
total capacity
peak power demand
capacity margin
© OECD/IEA 2013
• Plants are added on a least-cost basis, with a portfolio approach • Competition depends on several factors (fuel prices, CO2 prices,
efficiency, investment cost, construction time, WACC, economic lifetime) and is very much time-dependent
Long Run Marginal Cost (LRMC) (also referred to as ‘Levelised Cost of Electricity’)
𝑳𝑳𝑳𝑳𝑳𝑳𝑳𝑳 =𝒇𝒇𝒇𝒇𝒇𝒇𝒇𝒇 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 + 𝑳𝑳𝑪𝑪𝟐𝟐 𝒑𝒑𝒑𝒑𝒑𝒑𝒄𝒄𝒇𝒇× 𝒇𝒇𝒆𝒆𝒑𝒑𝒄𝒄𝒄𝒄𝒑𝒑𝒄𝒄𝒆𝒆 𝒇𝒇𝒇𝒇𝒄𝒄𝒄𝒄𝒄𝒄𝒑𝒑+ 𝑽𝑽𝑪𝑪𝑳𝑳
𝒇𝒇𝒇𝒇𝒇𝒇𝒑𝒑𝒄𝒄𝒑𝒑𝒇𝒇𝒆𝒆𝒄𝒄𝒆𝒆+𝑰𝑰𝒆𝒆𝑰𝑰. 𝒄𝒄𝒄𝒄𝒄𝒄𝒄𝒄 × 𝒑𝒑𝒑𝒑𝒇𝒇𝒑𝒑𝒇𝒇𝒆𝒆𝒆𝒆𝒇𝒇𝒆𝒆𝒄𝒄 𝒄𝒄𝒄𝒄𝒇𝒇𝒇𝒇𝒇𝒇𝒑𝒑𝒄𝒄𝒑𝒑𝒇𝒇𝒆𝒆𝒄𝒄/ �∑ 𝟏𝟏
(𝟏𝟏 + 𝒑𝒑)𝒄𝒄𝒆𝒆𝒄𝒄=𝟏𝟏 � + 𝑭𝑭𝑪𝑪𝑳𝑳
𝒄𝒄𝒇𝒇𝒑𝒑𝒇𝒇𝒄𝒄𝒑𝒑𝒄𝒄𝒆𝒆 𝒇𝒇𝒇𝒇𝒄𝒄𝒄𝒄𝒄𝒄𝒑𝒑× 𝟖𝟖𝟖𝟖𝟖𝟖𝟖𝟖𝟏𝟏𝟖𝟖𝟖𝟖𝟖𝟖
0
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40
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GasCCGT
Coal Ultra-supercritical
Coal Oxyfuelwith CCS
Nuclear Wind onshore
Do
llars
(200
9) p
er M
Wh
Long-run marginal cost of generation in United States in 2020
CO2 price
Fuel
Operation & maintenanceCapital
0
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GasCCGT
Coal Ultra-supercritical
Coal Oxyfuelwith CCS
Nuclear Wind onshore
Do
llars
(200
9) p
er M
Wh
Long-run marginal cost of generation in European Union in 2020
© OECD/IEA 2013
Additions of new plants
Generation by plant
Key Results
Investment assumptions
Fuel and CO2 prices
Efficiencies
Effective Capacity Factors
Total installed capacity by plant
CO2 by plant type
Refurbishments
Max Capacity Factors
Plant Investment needs
Retrofits
Early retirements
Historical capacity by plant
T&D Investment needs
Renewables support
End-user prices
Retirements of existing plants
Load curve
Wholesale price
Fuel consumption by plant
Electricity demand
Merit Order Dispatch
How much each plant generates in a year is determined by the merit order
© OECD/IEA 2013
How much each plant generates in a year is determined by the merit order
Fuel cost, efficiency, and CO2 prices determine a plant’s position in the merit order
0
50
100
150
200
MWh
S/M
Wh
CHP Minimum Renewables
Nuclear CHP
Lignite and steam coal
Gas CCGT
Gas GT
Oil Steam
and GT
© OECD/IEA 2013
The power generation mix is set to change
Global electricity generation by source, 2010-2035
Renewables electricity generation overtakes natural gas by 2015 & almost coal by 2035; growth in coal generation in emerging economies outweighs a fall in the OECD
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14 000
1990 1995 2000 2005 2010 2015 2020 2025 2030 2035
TWh
Coal Renewables
Gas
Nuclear
Oil
© OECD/IEA 2013
Power generation gross capacity additions & retirements in the New Policies Scenario, 2012-2035
-600 -300 0 300 600 900 1 200 1 500 GW
2012 - 2025
2026 - 2035
2012 - 2025
2026 - 2035
Net capacity change
Retirements:
Capacity additions:
Coal
Oil
Nuclear
Bioenergy
Hydro
Wind
Solar PV
Other*
Gas
The bulk of the gross capacity additions projected to 2035 comes from coal- and gas-fired power plants and wind power
© OECD/IEA 2013
Components of the end-user price of electricity
© OECD/IEA 2013
0
40
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280
2011
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2030
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35
2011
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2030
20
35
2010
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2030
20
35
2011
20
20
2030
20
35
Dol
lars
per
MW
h (2
011)
United States European Union Japan China
Wide variations in the price of power
Electricity prices are set to increase with the highest prices persisting in the European Union & Japan, well above those in China & the United States
Average household electricity prices, 2035
Renewables subsidy
Network, retail and other
CO2 price
Fuel Operating and maintenance
Fixed costs
Wholesale price components:
© OECD/IEA 2013
Policy implications
Evolution of the power generation mix in the (currently) highest CO2 emitting sector
Impact of fossil fuel prices, CO2 pricing and support policies to change the power mix
Overall investment needs and revenues for power plants
Impact of supported capacity on the power market structure
Household spending on electricity bills
Competitiveness of energy-intensive industries
© OECD/IEA 2012
Modelling the surge of LTO within the IEA WEM
C. Besson, J. Corben, P. Olejarnik
© OECD/IEA 2011
Supply shock from North American oil rippling through global markets
US EIA data
IEA Mid-Term OMR
© OECD/IEA 2011
IEA WEM model
Supply
Demand
PRICE
Iterations of smooth price trajectory until long term supply can match demand
© OECD/IEA 2011
Supply model splits demand by country and category
© OECD/IEA 2011
Fill the gap by Developping New Reserves
Current production declines, so there is a gap with demand (here of conventional and unconventional crude)
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2035
bb
Demand Natural Decline
© OECD/IEA 2011
Countries and types compete based on NPV each year to develop « tranches » of resources
Costs NPV
Constraints
Resources
Reserves developed
Learning
Inflation
Depletion
© OECD/IEA 2011
And then produce according to a standard profile
0.0%
1.0%
2.0%
3.0%
4.0%
5.0%
6.0%
7.0%
1 6 11 16 21 26 31
% o
f tot
al re
cove
rabl
e
Years from start
Conventional
EHOB
© OECD/IEA 2011
Light Tight Oil: a working definition
Very low permeability formations
Produced with multistage hydraulic fracturing in horizontal wells
Produced from basin center, continuous, source rock • oil is trapped by nature of rock not by geometrical
arrangements of layers
© OECD/IEA 2011
Rapid well decline
Does that invalidate the approach?
0
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1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
b/d
Year
LTO Conv (RHS)
Typical (good) Bakken well and typical (good) offshore well
© OECD/IEA 2011
But not rapid play decline
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Wells
Production (kb/d)
North Dakota DMR projection for the Bakken made in 2012
© OECD/IEA 2011
Drilling a series of wells (with time) leads to a profile not unlike that of conventional
Result of a typical drilling program
0%
1%
2%
3%
4%
5%
6%
7%
8%
9%
10%
1 3 5 7 9 11 13 15 17 19 21 23 25 27 29
LTO Conv
© OECD/IEA 2011
Simple but informative
So can apply the same methodology of « resources tranche » development to a new type of oil
0
0.5
1
1.5
2
2.5
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3.5
2000 2005 2010 2015 2020 2025 2030 2035 2040
mb/
d
Year
With 2012 resources, predicts peak, because of effect of depletion on costs
© OECD/IEA 2011
And you will read more in WEO2013!
Focus on oil Resources
Production
Demand
Refining
Implications (price, trade, investment…)
November 12th
© OECD/IEA 2013
Modelling the potential for industrial energy efficiency in IEA’s WEO
Dr Fabian Kesicki
International Energy Agency
International Energy Workshop, Paris, 20 June 2013
© OECD/IEA 2012
Global industrial energy demand increases by almost 40% up to 2035
Emerging economies determine industrial energy growth
Share of global industrial energy demand
0%
20%
40%
60%
80%
100%
1975 2010 2035
Rest of non - OECD
ASEAN
India
China
OECD
1 770 Mtoe 3 220 Mtoe 4 440 Mtoe
© OECD/IEA 2012
Energy intensive sectors represent around 60% of industrial energy demand
Today’s industrial energy demand
Energy flows in the industry sector, 2010
© OECD/IEA 2012
Modelling industrial energy demand
Industry accounts for more than a third of final energy consumption, but modelling faces difficulties:
No dominating sub-sector, many different production processes
Energy savings can impact on product quality and thus limit deployment
Data problems as energy consumption can evolve quickly and autoproduction can distorts energy consumption
© OECD/IEA 2012
Four energy-intensive sectors are explicitly modelled
WEM industry model structure
Sub-sectors in industry
Sub-sector Activity variables Iron and steel Crude Steel Chemical and petrochemical Ethylene Propylene Aromatics Methanol Ammonia Cement Cement Pulp and paper Paper Other industries Value-added in industry
© OECD/IEA 2012
Description of industry model
Activity projection
Econometric projection based on value added, price and pop.
Energy intensity
Process changes (e.g. primary vs secondary steel-making)
Technical energy savings
Systems optimisation
Operational efficiency
Fuel shares
Multiple logit model, electricity and fuel treated separately
© OECD/IEA 2012
Process steps by sub-sector in industry
Industry modelling in WEM accounts for process changes in the various sub-sectors
© OECD/IEA 2012
How to model energy efficiency policies?
0 2 4 6 8
10 12 14 16 18 20 22 24
0 0.02 0.04 0.06 0.08 0.1
Payb
ack
peri
od [y
ears
]
Energy savings [toe/t of product]
Energy savings as a function of the payback period
Acceptable payback periods and technology penetration vary with the scenario and the corresponding policy assumptions
© OECD/IEA 2012
Capacity growth in industry
While growth will significantly slow down for iron&steel and cement, other industry sectors see continued growth, particularly in non-OECD countries
0%
20%
40%
60%
80%
100% OECD
Non-OECD
Iron & steel Chemicals Pulp & paper Other industries
Cement
2011- 2020
2021- 2035
2011- 2020
2021- 2035
2011- 2020
2021- 2035
2011- 2020
2021- 2035
2011- 2020
2021- 2035
Cumulative new capacity as a share of currently installed capacity
© OECD/IEA 2012
Energy demand development
-2%
-1%
0%
1%
2%
3%
4%
NPS EWS NPS EWS NPS EWS NPS EWS NPS EWS
Efficiency*
Activity
Energy demand
Iron and steel
Chemicals Cement Pulp and paper
Other industries
Average annual change in industrial activity, efficiency and energy demand, 2010-2035
Energy demand will increase in all sub-sectors as rapid growth in industrial production outpaces energy efficiency improvements
© OECD/IEA 2012
Trends by subsector
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1990 2000 2010 2020 2030
Mto
e
Iron and steel
Chemicals and petrochemicals Cement
Pulp and paper
New Policies Scenario Efficient World Scenario
Global final energy consumption by industrial subsector
Energy efficiency can cut industrial energy demand growth by around 30%
© OECD/IEA 2012
Policies to overcome existing barriers
Numerous barriers impede the implementation of energy efficiency: short payback periods, lack of awareness, distraction from core business, production interruption
Efficiency policies
Funding of research
Requirements for energy audits and management systems
Training and capacity building
Performance requirements
Financing mechanisms
© OECD/IEA 2012
Conclusions
Industry is a driving factor behind energy demand growth in the future
Energy efficiency can slow down this growth by around 30%
Recent data and solid characterisation of production process are crucial for industrial energy modelling
Future research needs to shed more light on the black box ‘non-energy-intensive’ industries
© OECD/IEA 2013
Modelling oil demand from road freight transport using WEM
Timur Gül
International Energy Agency
Paris, 20 June 2013
© OECD/IEA 2012
Motivation
More than 50% of global oil demand today is concentrated in the transport sector, and most of it in road transport
Road transport is central to global oil demand growth, with the main options to reduce demand growth including:
Pursuing energy efficiency policy
Substituting oil-based fuels by other options
Modal shift
Curtailing oil demand growth from passenger cars has been at focus of policy-making, but attention to freight trucks was limited
© OECD/IEA 2012
The transport sector in WEM
Road transport
Rail
Navigation
Other
Passenger - kilometres
Tonne - -kilometres
Activity variables
Population
GDP
Aviation
Sub sectors
End use energy prices
Historical trends
The transport module in WEM encompasses a detailed representation of the transport sector, with a high number of technology choices
© OECD/IEA 2012
WEM analysis of the transport sector
Note: PLDV = passenger light-duty vehicles; LCV = light commercial vehicle; ICEV = internal combustion engine vehicle; t = tonnes
The transport module in WEM deploys many technology options for the assessment of technology evolution
© OECD/IEA 2012
Road freight transport in WEM
Distinguishes three classes of freight transport:
Light commercial vehicles (< 3.5 t)
Medium freight trucks (3.5 – 16 t)
Heavy freight trucks (>16 t)
Efficiency improvements are exogenous (where policies exist) or endogenous (elsewhere) based on payback periods
Fuel substitution occurs either policy-driven or based on cost using a Weibull function at n=4
© OECD/IEA 2012
Deploying more efficient trucks in WEM
Fuel consumption improvement rate (litres/100km)
USD
/veh
icle
Short-term
Long-term
Efficiency choices for trucks in WEM are based on undiscounted payback Periods with minimum payback periods of one to three years
Cost
© OECD/IEA 2012
Results: world transport oil demand in the New Policies Scenario
0 5 10 15 20 25
PLDVs
Road freight
International marine bunkers
Other
mb/d
2011
2035
International aviation bunkers
Domestic aviation
Oil demand from passenger light-duty is central to global oil demand growth, but freight transport is catching up
© OECD/IEA 2012
Incremental road freight growth by region in the New Policies Scenario
0
1 000
2 000
3 000
4 000
5 000
6 000
7 000
8 000
9 000
2005 2010 2015 2020 2025 2030 2035
Billi
on to
nne-
km
Other
India
China
Other
European Union
United States
OECD:
Non-OECD:
Demand for freight service grows particularly fast in non-OECD countries, albeit from a low base
© OECD/IEA 2012
World freight truck oil demand in the New Policies Scenario
0
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4
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18
2011 2035
mb/
d Oil demand
Improvement in fuel economy
Decrease 2011-2035 due to:
Use of alternative fuels
Higher average vehicle use
Fleet expansion
Increase 2011-2035 due to:
Cost-effective efficiency improvements will be instrumental to reducing oil demand growth from freight trucks
© OECD/IEA 2012
Average on-road fuel consumption of heavy trucks in the New Policies Scenario
0
5
10
15
20
25
30
35
40
India China Japan World
l/10
0 km
2011
2020
2035
United States
European Union
45
Regions with fuel economy standards for trucks like the United States see the largest improvement in fuel economy than other regions
© OECD/IEA 2012
Alternative fuel use by freight trucks in the New Policies Scenario
0
0.1
0.2
0.3
0.4
Biodiesel Natural gas Ethanol
mbo
e/d 2011
2.8%
0.1% 0.3%
3.6%
0.3%
2.3%
2035 share in freight truck fuel demand
%
Natural gas sees the highest growth in alternative fuels for road freight transport, but is constrained by the need to build up a refuelling infrastructure
© OECD/IEA 2012
Policy implications
Policy attention on improving fuel economy from passenger cars helps curbing future oil demand growth
Road freight transport oil demand is set to grow strongly as oil substitutes are facing obstacles and efficiency-policy still lacks
Policy can help realise efficiency potential for trucks, which is a market with many small operators that require low payback periods for efficiency investments
