1. A few thoughts about energy scenarios from an industrial perspective Renaud Crassous, EdF Ecole de Physique des Houches 02/03/2014

2. What do we need? 1. A broad view of possible future states of the world (growth, technologies, lifestyles, ressources, environment, institutions, etc.)

3. 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

4. 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’

5. …overwhelming data…

6. ... and puzzling uncertainties?

7. 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?

8. 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

9. 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? • Price signals • Innovation strategies • Redistribution, transfers • Skills, human capital

10. 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

11. Models

12. 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

13. An illustration of the necessary check-out of model results: future energy demand in France

14. ‘Marker Scenarios’ from the national debate (DNTE)

15. A look behind: sustained efficiency gains in the OECD during the last 40 years

16. Past efficiency gains in buildings

17. For the last 10 years: an apparent stability that hides opposite dynamics

18. Further efficiency gains: Continuity or disruption?

19. Power demand: a broadinterval of scenarios thatis not ‘pure unertainty’ Low scenario: behavioral change, 100% technicalpotential, strong substitution towardbiomass= negativeGDP elasticity Median scenario: close to a « business-as-usual», withcurrent trends going on (decreasingindustrialactivity, decrease use of electricity in heating, few innovation in new uses) = elasticity tends to 0,2 - 0,4 High scenario: where CO2 reductioncomes more from substitutions to low CO2 electricity uses, alongwithambitious EE gains= elasticityremainsarounditspre-crisislevel, around 0,8  RTE

20. Unsolved issues/ Further needs - Technical change with ‘realistic’ learningcurves (asymptotic) - Inequalities, redistributiveeffects of energypolicies - Intermittency - New electric uses in buildings - Debtconstraints and investment - macroeconomic impact of energyprices - Global treatment of uncertainties