Comparing Feed-In-Tariffs and Renewable Obligation Certificates the Case of Wind Farming

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1 Comparing Feed-In-Tariffs and Renewable Obligation Certificates the Case of Wind Farming Tim Mennel, Centre for European Economic Research (ZEW) Sara Scatasta, University of Stuttgart Hohenheim International Energy Workshop 2010 June 20-23, 2010, Stockholm

2 EU 2020 targets Increase Share of Renewable Energy in Total EU Energy consumption to 20% in 2020 (today 8,5%) Share in 2005 Target in Austria Belgium Czech Republic France Germany Greece Hungary Italy Latvia Lithuania Netherlands Poland Portugal Slovakia Slovenia Spain United Kingdom

3 Support Schemes in the EU Feed-in-Tariffs (FiT) Germany, Denmark, Spain... Renewable Energy Quotas (REQ) Britain, Italy

4 Feed-in-Tariffs the German FiT of 2000 (EEG) technology specific fixed tariffs for electricity from renewables obligation of TSO to buy electricity, consumer pays a levy digression of tariffs, e.g. wind (onshore) from 8.03 to 5.07 ct/kwh Tradable Quotas the British Renewable Obligation Certificates (ROC) renewable quotas for electricity suppliers, e.g. 10.4% in 2010 electricity generators buy ROCs to cover their obligation penality payment for non-achieving quota

5 Comparison of Quotas in Britain and Germany UK GER Quotas (real and set) Quota Percent Quota (Real) Quota (Set) Percent Quota Year Year Share of electricity from renewable energy (source: BERR and BMWi) Wind in renewable energy: 27% UK, 46% in GER

6 Comparison of Costs for ROC and EEG ROC UK EEG GER ROC UK FiT Germany (EEG) Price 8 6 Price ROC (p/kwh) Price ROC + Elec (c/kwh) Price ROC + Elec (c/kwh) Price 8 6 Wind (c/kwh) EEG-Av (c/kwh) Year Year Costs of ROC vs EEG (source: OFGEM and BMU)

7 Comparing FiT and ROC Mitchell, Bauknecht, Connor (2006) Observation: German EEG more effective than British ROC Risks for renewable plant in price, volume and balancing Reason for effectiveness: Risk reduction for the investor Central question of our paper: Assuming that FiT and ROC differ mainly in allocation of price risk, what is their effect on investment and innovation for a wind park owner?

8 Description of model decision of single investor to renew his wind plant discrete, infinite time horizon uncertainty about cost of capital (Markov process) technological change modelled as deterministic increase of capacity (innovation) support schemes modelled as electricity price process - FiT: deterministic price process - ROC: stochastic price process (Markov)

9 Innovation by larger capacity: Average capacity of installed wind turbines in Germany

10 Formalization of model

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16 Calibration of the model average feed-in-tariff according to EEG average German price of electricity from EUROSTAT average cost of unit capacity from time series of German association of wind energy (BWE) average growth of capacity from BWE average quantity of electricity generated from wind energy in 2004 from BWE average fix costs and life of a wind plant from a dataset provided by Energy Centre of the Netherlands (ECN) biannual time period, 5% discount rate five states of technology

17 Results of the model Analyse the policy function for given state of technology and age (t,a) Invest (2,8) R21 R19 R17 R15 R13 R11 price R9 R7 R5 0,8-1 0,6-0,8 0,4-0,6 0,2-0,4 0-0,2 R capital R1 Red Adopt, Blue Non-Adopt

18 Propensity to Invest in different scenarios Definition: The propensity to invest (pti) is the share of the red area in the graph. Start: three scenarios A) No price uncertainty, capital price fixed at long term mean B) No price uncertainty (FiT), capital price uncertainty C) Price uncertainty (TRQ), capital price uncertainty -the price process and capital price process are detrended-

19 Propensity to Invest in scenario A Propensity to invest by period for different states of technology

20 Propensity to Invest in scenario B (FiT) Propensity to invest by period for different states of technology

21 Propensity to Invest in scenario C (TRQ) Propensity to invest by period for different states of technology

22 Comparison of scenarios Common features of scenarios PTI weakly increases with age of wind plant For lower technologies, PTI increases later, but steeper than for higher technologies

23 Comparison of scenarios Differences between scenarios A and B (adding uncertainty in capital prices): weak increase in PTI over all states the increase in PTI is the greater, the older the plant B and C (adding uncertainty in electricity prices): weak increase in PTI over all states the increase in PTI is the greater, the lower the technology and the older the plant

24 Propensity to Invest: Full calibration FiT TRQ

25 Conclusion model studies effect of uncertainty on the propensity to innovate without risk aversion Propensity to invest higher for older plants and in lower states of technology capital price uncertainty weakly increases propensity to invest Propensity to invest higher under Tradable Renewable Quota than under Feed-in-Tariff