TOWARDS AN EFFECTIVE AND EFFICIENT RES TARGET FULFILLMENT FROM BAU TO STRENGTHENED NATIONAL POLICIES WITH PROACTIVE RISK MITIGATION Vienna University of Technology, 7 th IEWT Slide 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/d oc/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 Union up to 2020 have been calculated with the well-proven Green-X model. 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). Vienna University of Technology, 7 th IEWT Slide 2
Cost estimates of energy needed to reach the MS 2020 targets incorporating the impact of alternative / existing financing instruments Method: 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) Based on PRIMES Sectoral energy demand Primary energy prices Conventional supply portfolio and conversion efficiencies CO 2 intensity of sectors Defined for this study 20% target Reference electricity prices RES cost (Green-X database, incl. biomass) RES potential (Green-X database) Biomass import restrictions Technology diffusion Learning rates Vienna University of Technology, 7 th IEWT Slide 3
Incorporation of Financing risk WACC pre-tax = g d r d + g e r e = g d [r fd + r pd ] + g e [r fe + β r pe ] / (1 - r t ) Abbreviation / High risk assessment Low risk assessment (proactive risk mitigation) WACC methodology Calculation Debt (d) Equity (e) Debt (d) Equity (e) Share equity / debt g 70.0% 30.0% 70.0% 30.0% Nominal risk free rate r n 4.0% 4.0% 4.0% 4.0% Inflation rate i 2.0% 2.0% 2.0% 2.0% Real risk free rate r f = r n i 2.0% 2.0% 2.0% 2.0% Expected market rate of return r m 4.3% 8.4% 3.9% 7.7% Risk premium r p = r m - r f 2.3% 6.4% 1.9% 5.7% Equity beta b 1.6 1.6 Tax rate (corporation tax) r t 30.0% 30.0% Post-tax cost r pt 3.0% 12.2% 2.7% 11.1% Pre-tax cost r = r pt / (1-r t ) 4.3% 17.5% 3.9% 15.9% Weighted average cost of capital (pre-tax) WACC 8.3% 7.5% Wind offshore Wind onshore Tidal stream & wave power Solar thermal electricity Photovoltaics Hydro small-scale Hydro large-scale Geothermal electricity Biowaste Solid biomass Biogas 0.0 0.5 1.0 1.5 Technology-specific risk factor [1] Vienna University of Technology, 7 th IEWT Slide 4
Overview on assessed cases Business as usual without non-cost barriers Strengthened national policies - National Strengthened national policies - Strengthened national policies - with less innovative technologies Alternative policy option - harmonisation for selected technologies Non-cost barriers Mitigated (gradual removal) Mitigated Mitigated Mitigated Mitigated National support scheme As default Strengthened (according to best practice design criteria) Strengthened (according to best practice design criteria) Strengthened (according to best practice design criteria) Strengthened (according to best practice design criteria) Use of cooperation mechanisms Weak Average Strong (incl. regional cooperation i.e. joint support in the case of quota systems) Strong (incl. regional cooperation i.e. joint support in the case of quota systems) Strong[1](incl. regional cooperation i.e. joint support in the case of quota systems) Financing aspects[2] Commercial loans accompanied by risk mitigation (soft loans) for selected technologies in selected countries Proactive risk mitigation on a national level (loan guarantees, state involvement) Proactive risk mitigation on a national and level (loan guarantees, state involvement) Proactive risk mitigation on a national and level (loan guarantees, state involvement) Proactive risk mitigation on a national and level (loan guarantees, state involvement) Incentivising infrastructure development Moderate Moderate Strong ( offshore supergrid ) Strong ( offshore supergrid ) Strong ( offshore supergrid ) Coordination / Harmonisation of support levels Weak Moderate Strong Strong with phase out of support for innovative technologies Moderate / Harmonisation for selected technologies (e.g. wind offshore, biomass electricity) [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. Vienna University of Technology, 7 th IEWT Slide 5
Results: Towards an effective and efficient RES target fulfillment from BAU to strengthened national support with proactive risk mitigation 36% 80 RES-E deployment as share in gross electricity demand [%] 34% 32% 30% 28% 26% 24% 22% 20% 18% 16% Design & implementation of RES support instruments (improvement of efficiency & effectiveness of RES support) Removal of non-economic barriers and accompanying demand side measures BAU (moderate demand & mitigated barriers) BAU - continuing current national support Strengthened nat. national Yearly consumer expenditures due to RES-E support [Bill. ] 70 60 50 40 30 20 Design & implementation of RES support instruments (improvement of efficiency & effectiveness of RES support) Proactive mitigation of investor's risk BAU - continuing current national support BAU (moderate demand & mitigated barriers) Strengthened nat. national 2011 2013 2015 2017 2019 national 2011 2013 2015 2017 2019 national Comparison of RES-E deployment & corresponding consumer expenditures due to support for new RES-E (installed 2011 to 2020) in the EU-27 for all selected cases i.e. BAU and strengthened national support (national ) w/o proactive risk mitigation Vienna University of Technology, 7 th IEWT Slide 6
Results: Example Capital expenditures Capital expenditures for new RES installations (2011 to 2020) [Bill. ] 100 90 80 70 60 50 40 30 20 10 0 70.0 70.2 69.1 69.2 44.4 44.4 44.5 Strengthened nat. national national 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 45.1 RES in total - yearly average (2011 to 2020) RES-Electricity - yearly average (2011 to 2020) RES in total - by 2020 RES-Electricity - by 2020 61.2 36.7 (less innovative tech.) 61.5 37.5 (less innovative tech.) 66.3 68.4 41.4 43.5 Harmonisation for selected technologies Harmonisation for selected technologies No impact of proactive risk mitigation on CAPEX, but differences between policy paths are observable Vienna University of Technology, 7 th IEWT Slide 7
Results: Example Additional generation cost & consumer expenditures due to RES support 40 Average (2011 to 2020) yearly additional generation cost & consumer expenditures due to support of new RES installations (2011 to 2020) [Bill. ] 35 30 25 20 15 10 5 0 12.5% 15.0% 17.5% 20.0% RES deplyoment as share in gross final energy demand [%] Average (2011 to 2020) yearly consumer expenditures due to support & additional generation cost of new RES installations (2011 to 2020) BAU - continuing current national support BAU (moderate demand & mitigated barriers) national (less innovative tech.) Harmonisation for selected technologies 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 Vienna University of Technology, 7 th IEWT Slide 8
Results: Example Consumer expenditures (due to RES support) Consumer expenditures due to support for new RES installations (2011 to 2020) [Bill. ] 90 80 70 60 50 40 30 20 10 0 41.0 37.2 38.2 21.8 19.0 21.0 Strengthened nat. national national 34.9 34.8 36.6 31.2 34.8 19.1 17.7 15.5 19.3 18.7 RES in total - yearly average (2011 to 2020) RES-Electricity - yearly average (2011 to 2020) RES in total - by 2020 RES-Electricity - by 2020 (less innovative tech.) (less innovative tech.) Harmonisation for selected technologies Harmonisation for selected technologies 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 Vienna University of Technology, 7 th IEWT Slide 9
Conclusions Capital expenditures, additional generation cost & consumer expenditures due to RES support 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 support or 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 cost are lower if less innovative technologies deploy on the market (compare the variant 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 ( ). Vienna University of Technology, 7 th IEWT Slide 10
Results: Example Consumer expenditures due to RES support by MS Resulting consumer expenditures due 3.0% 2.5% to RES support by 2020 accounted to 2.0% the countries according to 1.5% 1.0% the national RES exploitation (right) 0.5% the national RES targets (below) 0.0% Consumer expenditures* due to RES support by 2020 (expressed as share of GDP) [% of GDP] 3.0% 2.5% 2.0% 1.5% 1.0% 0.5% 0.0% Austria Belgium Bulgaria Consumer expenditures* due to RES support by 2020 (expressed as share of GDP) [% of GDP] 3.5% Austria Belgium *based on national RES targets Cyprus Czech Republic Denmark Estonia Finland France Germany *based on national RES deployment Greece Bulgaria Cyprus Czech Republic Denmark Estonia Finland France Germany Greece national (less innovative tech.) Harmonisation for selected technologies Hungary national Ireland Italy Latvia Lithuania (less innovative tech.) Harmonisation for selected technologies Hungary Ireland Italy Latvia Lithuania Luxembourg Malta Netherlands Poland Luxembourg Portugal Malta Netherlands Romania Poland Slovakia Portugal Romania Slovenia Slovakia Spain Slovenia Sweden Spain Sweden United Kingdom United Kingdom EU 27 EU 27 Vienna University of Technology, 7 th IEWT Slide 11
Notes: Example Consumer expenditures due to RES support by MS 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. Vienna University of Technology, 7 th IEWT Slide 12
Results: Example Technology-specific deployment (RES in the electricity sector) Electricity generation (by 2020) from new RES-E installations (2011 to 2020) [TWh] 250 200 150 100 50 0 Biogas Solid biomass Biowaste Geothermal electricity Hydro largescale Hydro smallscale Photovoltaics Solar thermal electricity Tide & wave Wind onshore Wind offshore national (less innovative tech.) Harmonisation for selected technologies 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. Vienna University of Technology, 7 th IEWT Slide 13
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