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Outline Background Methodology Assumptions / Scenarios Results

Towards an effective and efficient res target fuLfillment – from bau to stRengthened national policies with proactive risk mitigation. Outline Background Methodology Assumptions / Scenarios Results.

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Outline Background Methodology Assumptions / Scenarios Results

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  1. Towards an effective and efficient res target fuLfillment– from bau to stRengthenednational policies with proactive risk mitigation

  2. Outline Background Methodology Assumptions / Scenarios Results

  3. (1) Cost estimates of energy needed to reach the MS’ 2020 targets incorporating the impact of alternative / existing financing instruments http://ec.europa.eu/energy/renewables/studies/doc/renewables/2011_financing_renewable.pdf Objective / Overview:The aim of this research is to provide valuable estimates of the cost for reaching the 2020 RE objectives at MS level. A set of policy scenarios on the future deployment of RE technologies within the European Union up to 2020 have been calculated. Besides analyzing the consequences of policy choices on RES support instruments we focus in this model-based scenario assessment on the illustration of the impact of proactive risk mitigation measures to alleviate the financing of the necessary RES deployment. Results offer details on the future development of technology-specific investment and generation cost, and a sound depiction of the required corresponding expenditures(i.e. capital – and support (consumer / societal) expenditures).

  4. (2) Green-X … a simulation model for energy policy instruments (for RES) Mid-term (up to 2020)realisable potentialsin year n& corresponding costs for RES at country level by RES technology (subdivided into several bands) costs band 3 … n+1 band 2 The Green-X approach:Dynamic cost-resource curves&a detailed energy policyrepresentation band 1 potential Technology diffusion (‘S-curve’)(non-economic barriers by technology/country) Potential Technological change((global) learning curves by technology) Cost (efficiency) costs Realisable yearly potentialsin year n potential Energy policy (energy prices, RES support) e.g. Feed-in tariffs, Investment incentives, Tendering schemes, Quotas with tradable green certificates costs PFIT Deployment in year nand corresponding costs & benefits potential

  5. Support instruments have to be • effectiveforincreasingthe deployment of RES& • efficientwith respect tominimising the resulting support costsover time. (2) evaluation criteria for (RES) support instruments ►Key criteria for the evaluation of support instruments support expendituresor transfer costs for consumer / society(due to the support of RE) …… consumer  producer … do not consider any indirect costs / benefits or externalities Transfer costsfor consumer / society • Increasing the efficiencyof RES support: • Minimise generation costs • Lower producer profits(to sufficient & adequate levels)

  6. (3) Assumptions In order to ensure maximum consistency with existing EU scenarios and projections the key input parameters of the scenarios presented in this report are derived from PRIMES modelling and from the Green-X database with respect to the potentials and cost of RE technologies (task 1). The table below shows which parameters are based on PRIMES and which have been defined for this study. More precisely the PRIMES scenario used is the draft Reference case as of April 2010 (NTUA, 2010)

  7. (3) Scenarios [1] Beyond the scope of the mechanisms agreed under the current RES directive [2] Subject to sensitivity analysis (in line with the scope of this study) – i.e. w/o proactive risk mitigation measures in the case of strengthened national and alternative policies in order to demonstrate the impact of them in a clear manner.

  8. (4) Results:Towards an effective and efficient RES target fulfillment – from BAU to strengthened national support with proactive risk mitigation Comparison of RES-E deployment & corresponding consumer expenditures due to supportfor new RES-E(installed 2011 to 2020) in the EU-27 for all selected cases – i.e. BAU andstrengthened national support (national perspective) w/o proactive risk mitigation

  9. Results:Example … Capital expenditures Comparison of the resulting 2020 RES deployment and the corresponding (yearly average) capital expenditures for new RES (installed 2011 to 2020) in the EU-27 for all key cases  No impact of proactive risk mitigation on CAPEX, but differences between policy paths are observable

  10. Results:Example … Additional generation cost & consumer expenditures due to RES support Comparison of the resulting 2020 RES deployment and the corresponding (yearly average) additional generation cost & consumer expenditures due to RES support for new RES (installed 2006 to 2020) in the EU-27 for selected cases (i.e. BAU as well as strengthened national / alternative policy cases with proactive risk mitigation)  Less innovative technologies means less additional generation cost & support expenditures, “pure” national solutions lead to higher support expenditures

  11. Results:Example … Consumer expenditures (due to RES support) Comparison of the resulting 2020 RES deployment and the corresponding (yearly average) consumer expenditures for new RES (installed 2011 to 2020) in the EU-27 for all key cases • Impact of proactive risk mitigation on consumer expenditures is apparent (5 to 10% savings), besides (as stated in prior) differences between policy paths are observable

  12. Results:Example … Consumer expenditures due to RES support by MS Resulting consumer expenditures due to RES support by 2020 accounted to the countries according to • the national RES exploitation (right) • the national RES targets(below)

  13. Results:Example … Technology-specific deployment (RES in the electricity sector) Technology-specific breakdown of RES-E generation from new installations(2011 to 2020) in the year 2020 at EU-27 level for selected cases (i.e. strengthened national / alternative policy cases with proactive risk mitigation) Wind energy (on- & offshore) and biomass dominate the picture. Depending on the assumed support conditions, also PV would achieve a significant exploitation in various cases.

  14. Conclusions • The impact of improving financing conditions is apparent: While overall capital expenditures remain unaffected, consumer expenditures due to RES support can be decreased by 5 to 10% depending on the specific policy path, whereby on average a reduction of about 9% appears reasonable. In general, the impact for RES in the electricity sector is of slightly larger magnitude as therein more novel technologies can be found that would benefit from proactive (technology) risk mitigation. • Minor differences are observable when comparing the assessed policy cases – as preconditioned for all assessed policy paths (of strengthened national supportor alternative policies (harmonised technology-specific premiums for wind offshore & biomass)). • Obviously, it can be seen that capital and consumer expenditures as well as additional generation costare lower if less innovative technologies deploy on the market (compare the variant “European perspective with less innovative technologies” with the other variants). • And, as far as feasible, “pure” national RES target fulfillment would lead to an expenditure increase compared to its pendant reflecting more intensive cooperation between MS’s (“European perspective”). • National RES targets as given by the new RES directive and preconditioned in this assessment lead to a redistribution of monetary expenses between the different countries. • It appears that this process causes a fairer distribution of the resulting policy cost by country where economic wealth seems to be better reflected. • A general exception is Latvia, which would require comparatively high consumer expenditures for fulfilling their 2020 RES obligations compared to its economic wealth.

  15. Thank you for your attention! busch@eeg.tuwien.ac.at

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