1. Predicting the future A view from the electricity industry Ian Rodgers Ian.Rodgers@RWEnpower.com

2. Outline The track record for predicting the future A few rules for predicting the future What can go wrong? How to minimise the risks? Summary of key issues

3. What is the track record in predicting the future? "There is no likelihood man can ever tap the power of the atom." -- Robert Millikan, Nobel Prize in Physics, 1923 "I think there is a world market for maybe five computers." -- Thomas Watson, chairman of IBM, 1943 "640K ought to be enough for anybody." -- Bill Gates, 1981

4. A few rules for predicting the future Learn From the Past Be Aware of Your Perspective Count On the Surprises Octavia E. Butler

5. Conclusions from RAINS review ‘While it is sensible for IIASA to import some of the RAINS components … such externally created scenarios may have a decisive impact on projected emissions and abatement cost curves.’ ‘As a consequence limited knowledge of activity is likely to be the largest source of potential error/misstatement in the RAINS output.’ From Draft Final Report for Commission Comment 16th July 2004

6. Effect of updating energy model assumptions on power plant energy & emissions Updating of model assumptions has resulted in changes of up to 60% between consecutive projections PRIMES model projections. NECD scenario shown is €20/tCO2 case

7. Evolution of EU-15 2010 baseline projections during development of original NECD Developing understanding, correction of errors and redefinition of baseline to be used, resulted in very significant changes in baseline emissions over a period of 3 years 2006 National view

8. What can go wrong? Use of alternative projections may set unattainable targets: UK example Use of UK National energy projections indicates that the EC Thematic Strategy on Air Pollution SO 2 ceiling based on PRIMES may be unattainable at any cost Note: gap between optimised ceiling and MTFR is ~10% of baseline emissions Data: RAINS web: original CAFE projections

9. How objective are projections? Why are national (central) projections often higher than all other projections under consideration for NECD revision? To what extent does the desire for an outcome influence projections? Do policy makers usually over-estimate the likely success of their policies? An ex-post assessment of the process would help to answer these questions

10. Baseline Effects Energy Projections (Country) Baseline Emissions (Country) Traffic Projections (Country) Baseline Emissions (Country) Transfer Matrices (Country) Airborne Concentrations/ Depositions (Grid Square) New Emissions Additional control measures (Country) Environment/ Health/ effects Optimisation of Extent of Adoption Targets Met? Minimum Cost Attainment of Target Target Impacts Benefit of Target Attainment RIA Dose/ Response Functions Additional Controls Costs/Efficiencies (Plant) Plant/ Fuel Mix (Country) NOYES GAINS MODEL Emission Factors Common inputs Baseline Revision Direct industry expert input industry informed comment Agriculture Emissions Cost Curve Target Setting Effects metrics Active involvement of industry stakeholders will help to reduce risks Industry involvement in TFIAM, EGTEI, NECPI

11. Role of plant operation – a significant factor Annual conversion efficiency of a power station depends on how it operates and the abatement equipment fitted. Lower annual load factors result in reduced efficiency and higher emissions per MWh There are practical difficulties in implementing this in GAINS. Not to do so introduces a significant source of error into projections, however. We would welcome the opportunity to explore what can be done further to improve the representation of the sector Illustrative data from UK power plant

12. Key points Energy and emission projections will be wrong in practice (‘learn from the past’) –Sufficient time should be allowed for review and revision by national experts Important to define a realistic (not idealistic) set of projections (‘be aware of your perspective’) –Important concerns such as security and diversity of energy supply are not explicitly acknowledged in all energy projections Important to allow sufficient time for sensitivity studies to understand the policy-relevant implications of the range of potential outcomes (‘count on the surprises’) Not to do this risks significant errors in cost estimates leading to economic inefficiency, and could potentially lead to the setting of unattainable emission ceilings