Transcript 5-Crassous A few thoughts about scenarios from an industrial

A few thoughts about energy scenarios
from an industrial perspective
Renaud Crassous, EdF
Ecole de Physique des Houches
02/03/2014
What do we need?
1. A broad view of possible future states of the
world (growth, technologies, lifestyles,
ressources, environment, institutions, etc.)
What do we need?
1. A broad view of possible future states of the
world (growth, technologies, lifestyles,
ressources, environment, institutions, etc.)
2. A robust assessment of public policies, to
build optimal strategies and to build a sound
dialog with other stakeholders
Several available methods…
• Narratives – anything that help us to « think
out of the box - e.g. Shell storylines (Moutains
/ Oceans)
• External Quantitative pathways – SRES, World
Energy Outlook, RCPs
• Consultants (Oxford economics, CERA,
Enerdata, research centers, etc.)
• Models to play with at home
• ‘Back of the envelope’ / ‘rule of thumb’
…overwhelming data…
... and puzzling uncertainties?
A ‘reader’s guide’
for external scenarios (1/3)
• Three levels of information:
(i) Storyline: Explicit/Implicit motivation of the
scenario builder(s)
• Energy demand : behavioral change? new acceleration
of efficiency gains ? And/or further decline of industry?
• Energy Supply: A new wave of technical revolution that
allow to fulfill growing needs on the long-run(backstop
technologies) in spite of finite fossil resources.
• Electricity: what role in the future energy mix?
A ‘reader’s guide’
for external scenarios (2/3)
(ii) Concrete indicators of feasibility/likelyhood
Quantitative data for the reader to build his own
assessment of the likelyhood of the trajectory
• Lifestyles (per capita travel time, housing surface,
• Resources (e.g. surface of energy crops/ industrial
biomass for energy)
• Total costs, investment needs, energy prices
A ‘reader’s guide’
for external scenarios (3/3)
(iii) Policies / Conditions of success
What are the stumbling blocks? What changes
and what policies are needed?
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Price signals
Innovation strategies
Redistribution, transfers
Skills, human capital
Deep inside: what model?
• Advantages of using a model:
– Complex calculation (simulation or optimization)
– Consistency (between prices and quantities,
behaviors/technologies, energy/macro)
• Drawbacks:
– Huge efforts do not guarantee sound results
– Black box => low confidence and strategic use
Models
Two frequent Flaws
• Data: too often neglected
– Ready-to-use database (e.g. GTAP for GE models)
– Double check : ‘Check-in’ / ‘Check-out’
• Model: misuses ‘out of the definition domain’
– e.g. Macroeconometric models = short-run only
An illustration of the necessary
check-out of model results:
future energy demand in France
‘Marker Scenarios’ from the
national debate (DNTE)
A look behind: sustained efficiency gains in
the OECD during the last 40 years
450
400
350
300
PIB
250
Energie
Electricité
200
Energie avec élasticité pré-73
150
Electricité avec élasticité pré-73
100
50
0
1960
1970
1980
1990
2000
2010
Past efficiency gains in buildings
Consommations observées de chauffage des bâtiments
(kWh par m2 et par an)
250
200
150
100
France
50
Allemagne
0
1980
1985
1990
1995
2000
2005
2010
source : Enerdata
2015
For the last 10 years: an apparent stability
that hides opposite dynamics
Demand evolution
00-10 (TWh)
Total energy
Power
0
+40
Transport
+10
~0
Industry
-70 (-60 due to the
economic crisis)
-15 (-10 due to the
economic crisis)
Buildings
+60
+55 (+40 due to
specific uses)
Total
Further efficiency gains:
Continuity or disruption?
60-73
73-10
73-85 85-97 97-07
Real GDP growth (per year)
5,7%
2,1%
2,4%
2,1%
2,4%
Total energy demand growth
rate (per year)
7,1%
0,4%
-0,3%
1,2%
0,5%
Electricity demand growth
(per year)
Elasticity of Energy demand
over GDP
Elasticity of Electricity
Demand over GDP
7,2%
3,0%
4,4%
3,0%
1,8%
1,25
0,18
-0,14
0,54
0,22
1,26
1,46
1,87
1,42
0,77
Power demand: a broad interval of scenarios
that is not ‘pure unertainty’
 Low scenario: behavioral change,
100% technical potential, strong
substitution toward biomass =
negative GDP elasticity
 Median scenario: close to a
« business-as-usual», with current
trends going on (decreasing industrial
activity, decrease use of electricity in
heating, few innovation in new uses) =
elasticity tends to 0,2 - 0,4
 High scenario: where CO2 reduction
comes more from substitutions to low
CO2 electricity uses, alongwith
ambitious EE gains= elasticity remains
around its pre-crisis level, around 0,8
RTE
Unsolved issues/ Further needs
- Technical change with ‘realistic’ learning curves
(asymptotic)
- Inequalities, redistributive effects of energy policies
- Intermittency
- New electric uses in buildings
- Debt constraints and investment
- macroeconomic impact of energy prices
- Global treatment of uncertainties
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