The Energy Transition Model
A fresh perspective on modelling
the future of energy
Directorate-General
Energy and Transport,
European Commission
March 2009
Quintel Strategy Consulting
Atrium - Strawinskylaan 3051
1077 ZX Amsterdam
The Netherlands
www.quintel.nl
Introduction
Quintel developed the Energy Transition Model to mitigate the risk of being
precisely wrong when making decisions on the transition to new sources of energy
• Society is entering unchartered waters as it is working towards a sustainable energy
economy through Energy Transition
• Many decision-/policymakers are not aware of the risks of being precisely wrong when
predicting Energy Transition and the impact of their decisions
– Current models on energy systems (e.g. fuel prices) often fall prey to false precision
– Predictions give the impression of being very accurate, when in reality only a low
degree of accuracy exists
• Decision-makers can no longer afford a modelling approach based on conventional
wisdom when dealing with the complex topic of Energy Transition
– They must learn to make intelligent decisions based on an understanding of the
underlying principles and assumptions
• Quintel developed an alternative approach that helps governments and companies
make decisions on the future of energy
– This approach reveals relations between different energy (transition) issues and
stimulates the debate on implicit assumptions and missing information
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Content
1
The issues with current modelling aids
2
A new approach for evaluating energy transition scenario’s
3
ETM as a complementary aid to the Primes Energy Model
2
The issues with current modelling aids
1
It is has become evident that renowned energy institutes are no longer able
to provide reliable forecasts despite their precise modelling approaches
Example oil price: Actuals vs. forecasts
Generic pitfalls of forecasting
• Unknown factors - independent of classic supplyand-demand calculations account for spotty
forecasting record (for example geopolitical events,
economic crises, uncertainties in reserves)
• While prognoses may be accurate during periods of
stability, track record is doubtful in periods of change
• For example: Assumptions of infinite supplies and
rational economic behaviour no longer hold as
supplies become finite and behaviour more ‘erratic’
• Governments are still relying on this imperfect
science for policy making
Typically, complexity is added to forecasting models to capture previously ‘unpredictable’
mechanisms, making it more difficult to understand the results and underlying logic
Source: De nieuwe oliecrisis en overheidsbeleid, International Energy Agency, Peakoil Nederland
3
The issues with current modelling aids
1
As models become less transparent, users tend to make decisions based
on trial and error rather than on causal reflection and systemic learning
Black Box
Model
Energy
Transport
Transparent
Box Model
Energy
Transport
Input
Economic growth
‘Trial and error’ decision making
Modelling continuously required to
predict effect of changing conditions
Economic growth
‘Systemic learning’ decision making
Modelling only initially required to
understand principles/discuss effects
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The issues with current modelling aids
1
It is questionable whether current modelling aids will be helpful in
supporting decision making on Energy Transition
Adoption of new technologies
difficult to estimate
Pricing of fossil fuels less predictable as
supplies become finite and demand unstable
Demand
Q curve
Supply
curve
Q
Today
Time
P
‘New energy’ difficult to model due to immature supply
market and unknown switching behaviour of users
Q Demand
curve
Supply
curve
?
?
P
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Content
1
The risk of being precisely wrong
2
scenarios
A new approach for evaluating energy transition scenario’s
3
ETM as a complementary aid to the Primes Energy Model
6
scenarios
New approach for evaluating energy transition scenario’s
2
Quintel has developed a model to reveal the relations between energy issues
and to stimulate the debate on implicit assumptions and missing information
Key features
• Extensive database containing geographical,
technical and economic data, verified by experts
Not entirely
correct
• Flexible input where users can vary all variables of
model, e.g. GDP, fuel prices, technology adoption
• ‘Real-time’ output so that the user is directly
confronted with impact of initial assumptions
• Developed in partnership with:
– Suppliers: Shell, Gasterra
Enexis: Regional
– Producers: Essent, Eneco, Delta, Enexis
El. transport
– Government: Ministry of Economic Affairs,
City of Amsterdam
– IT specialist: Logica CMG
• Free downloadable version available online to
stimulate the public debate on Energy Transition
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scenarios
New approach for evaluating energy transition scenario’s
2
Due to its unique interactive features, it helps decision makers gain insight
on the challenges of energy transition and confirm/negate key assumptions
Initial output of ETM model
User input on key
assumptions
Output of ETM model
with new assumptions
Pijltjes maken
sliders minder
goed zichtbaar
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scenarios
New approach for evaluating energy transition scenario’s
2
Despite differences in underlying assumptions, experts from participating
companies and government agree on a number of key points
• The model has been tested numerous times in scenario planning sessions with
energy experts across industry and government
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publicatie van
BS die gisteren
uitkwam:
duurzaam %
eemt weer toe
Although opinions on some key assumptions vary greatly, experts from
participating companies and government agree that:
– Dutch energy supply is becoming less sustainable and increasingly
dependent on import from other countries at the moment
– The Netherlands should invest in smart energy conservation, more wind
energy and biomass and the right mix of fossil fuels
– Focus should be on developing long term relationships and mutual
dependency between the Netherlands and energy-exporting countries
– Investing in new energy infrastructures seems a good way to ease the
current economic crisis and will help to keep energy supply in the
Netherlands both sustainable and affordable in the long run
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Content
1
The risk of being precisely wrong
2
A new approach for evaluating energy transition scenario’s
3
Introduce ‘ETM’
phrase
ETM as a complementary aid to the Primes Energy Model
10
ETM as a complementary aid to the Primes Energy Model
3
In the past the Commission has relied on the state of the art PRIMES
energy system model to support decision making on key energy policies
Initial view on pros and cons
to be validated with European Commission
• An energy policy markets analysis tool including
relationships between policy and technology
• Behavioural, price driven model assuming that
producers and consumers respond to changes in
price influenced by policy and technology changes
Input:
 Detailed scenario’s incl. price projections,
policies,..
– Small number of pre-defined scenario’s
 Data comprises EU, candidates and selected
neighbouring countries
• Built by the National Technical University of Athens
with help of EU subcontractors/service providers
Model:
– Black box model for decision maker
• Started in 1993 and continuously improving
Output:
- + Precise prediction on impact of policy
instruments on energy market, but is it correct?
– Less helpful for determining preferred mix of
energy sources
• Examples of applications:
– 1997: Evaluation of EC policies for Kyoto
1999: EU Energy & Emissions Outlook
– 2003/5/7: European energy & transport trends to 2030
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ETM as a complementary aid to the Primes Energy Model
3
ETM can be regarded as an interactive tool for guiding decision making,
while Primes predicts the economic effects of the resulting actions
Collection of key
input
Initial testing of
assumptions & choices
Prediction of
economic effects
Further validation &
variation
For example:
• Technical-economic data
• Discount rates
• Energy import prices
• Tax rates
Selection of
most relevant
assumptions
Energy Transition Model
Energy Transition Model
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ETM as a complementary aid to the Primes Energy Model
3
Suggested next steps
• Incorporate all EU countries and neighbouring countries in ETM model
• Modify ETM and Primes models to ensure consistency
• Conduct pilot project (probably on a subset of EU countries)
• ..
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