20% RES by 2020 Biomass role in the Renewable Energy Directive 2020 energy futures

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1 20% RES by 2020: Biomass role in the Renewable Energy Directive 2020 energy futures 20% RES by 2020 Biomass role in the Renewable Energy Directive 2020 energy futures Authors: Christian Panzer, Gustav Resch Energy Economics Group, Vienna University of Technology Contact: Web: This presentation reflects research conducted within the European project: Shaping an effective and efficient European renewable energy market AEBIOM conference Brussels, June, 29 th 2011 Slide 1

2 20% RES by 2020: Biomass role in the Renewable Energy Directive 2020 energy futures Content (1) Introduction General modeling approach (2) Results on RES development a specific focus on bioenergy (3) Biomass modeling implementations internal EU biomass trade (4) Conclusions and recommendations AEBIOM conference Brussels, June, 29 th 2011 Slide 2

3 Key criteria for the evaluation of support instruments 20% RES by 2020: Biomass role in the Renewable Energy Directive 2020 energy futures Support instruments have to be effective for increasing the deployment of RES & efficient with respect to minimising the resulting support costs over time. support expenditures or transfer costs for consumer / society (due to the support of RE) consumer producer do not consider any indirect costs / benefits or externalities p MC Market clearing price = price for certificate price, costs [ /MWh] Producer surplus (PS) Transfer costs for consumer / society MC Increasing the efficiency of RES support: Minimise generation costs Lower producer profits (to sufficient & adequate levels) p C Generation Costs (GC) Quota Q Transfer costs for consumer = PS + GC p (additional costs for society) C * Q quantity [GWh/year] p C... market price for (conventional) electricity p MC... marginal price for RES-E (due to quota obligation) MC... marginal generation costs AEBIOM conference Brussels, June, 29 th 2011 Slide 3

4 Cost (efficiency) Potential 20% RES by 2020: Biomass role in the Renewable Energy Directive 2020 energy futures Mid-term (up to 2020) realisable potentials in year n n+1 & corresponding costs for RES at country level by RES technology (subdivided into several bands) costs band 1 Technology diffusion ( S-curve ) (non-economic barriers by technology/country) Technological change ((global) learning curves by technology) costs band 2 band 3 potential The Green-X approach: Dynamic cost-resource curves Realisable yearly potentials in year n Energy policy (energy prices, RES support) potential & e.g. Feed-in tariffs, Investment incentives, Tendering schemes, Quotas with tradable green certificates Deployment in year n and corresponding costs & benefits P FIT costs a detailed energy policy representation AEBIOM conference Brussels, June, 29 th 2011 Slide 4 potential

5 Penetration (as share of longterm potential) [%] Yearly realisable potential (as share of long-term potential) [%] Technology diffusion in accordance with general diffusion theory, penetration of a market by any new commodity typically follows an S-curve pattern applied within the model to describe the impact of non-economic barriers on RES-E deployment Model implementation of dynamic non-economic market barriers F d ΔP Mn P P Mn F General diffusion theory 1 e 1 d ( t t0 ) Markt penetration Diffusion rate Yearly realisble potential (according to market barrier) Long-term realisable potential P d F ( 1 F) 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0% International IAEE Historical record Deployment Market barrier - Model implementation e.g. development of wind power (onshore) in Germany conference 1990 San 1995 Francisco June 22 nd, 2009 Slide 5 Year [t] Realisable potential due to non-economic Markt barriers 14% 12% 10% 8% 6% 4% 2% 0% 0% 20% 40% 60% 80% 100% Penetration (as share of long-term potential) [%]

6 RES-E deployment as share in gross electricity demand [%] Yearly consumer expenditures due to RES-E support [Bill. ] Results: Towards an effective and efficient RES target fulfillment from BAU to strengthened national support w/o intensified cooperation 38% 36% 34% 32% 30% 28% Design & implementation of RES support instruments (improvement of efficiency & effectiveness of RES support) Removal of non-economic barriers and accompanying demand side measures Design & implementation of RES support instruments (improvement of efficiency & effectiveness of RES support) More cooperation between MS 26% 24% 22% 20% BAU (moderate demand & mitigated barriers) BAU - continuing current national support Strengthened nat. support - national perspective Str. nat. support - European perspective 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 without (national perspective) or with intensified cooperation (European perspective) between member states

7 5,000 4,000 3,000 2,000 1,000 0 Demand for bio-electricity [ktoe] Biomass consumption by 2020 in terms of final energy [ktoe] Deviation to NREAP projection [%] RES-electricity Biogas 25 5,505 3,659 4,973 5,335-34% -10% -3% Bioliquids 1,096 n.a. n.a. n.a. n.a. n.a. n.a. Solid biomass 13,344 12,461 15,466 17,328-7% 16% 30% Biomass (electricity) 20 19,946 16,120 20,440 22,663-19% 2% 14% RES-heat Biogas 4,450 1,683 2,194 2,586-62% -51% -42% 15 Bioliquids 4,405 n.a. n.a. n.a. n.a. n.a. n.a. Solid biomass 81,192 63,211 68,685 90,379-22% -15% 11% Biomass (heat) 10 90,047 64,895 70,879 92,965-28% -21% 3% Biofuels First generation biofuels 19,059 13,642 13,642 12,642-28% -28% -34% Second generation biofuels 5 2,498 2,028 2,379 2,941-19% -5% 18% Biofuel import / export 7,376 14,718 14,865 12, % 102% 74% Biomass (transport) 28,933 30,388 30,886 28,418 5% 7% -2% 0 Biomass (transport - domestic) 21,558 15,670 16,021 15,583-27% -26% -28% Aggregated level Biomass (domestic) EU27 131,550 96, , ,211-27% -18% 0% Summary: Demand for biomass Demand for biomass Comparison of the NREAPs with recent Green-X scenarios Comparison: Final energy consumption from biomass in the electricity sector EU27 NREAP SNP BAU barriers mitigated* BAU AT BE BG CY CZ DE DK EE EL ES FI FR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK Comparison of scenarios (page 2 of 2) NREAP Green-X Comparison Green-X vs. NREAP BAU BAU barriers mitigated* SNP BAU BAU barriers mitigated* SNP

8 Demand for biomass Comparison of the NREAPs with recent Green-X scenarios Comparison: Final energy consumption from biomass in the heating & cooling sector 20,000 15,000 10,000 5,000 Demand for bio-heat [ktoe] NREAP SNP BAU barriers mitigated* BAU 0 AT BE BG CY CZ DE DK EE EL ES FI FR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK Comparison of scenarios (page 2 of 2) EU27 Biomass consumption by 2020 in terms of final energy [ktoe] Deviation to NREAP projection [%] RES-electricity Biogas 100 5,505 3,659 4,973 5,335-34% -10% -3% Bioliquids 1,096 n.a. n.a. n.a. n.a. n.a. n.a. Solid biomass 13,344 12,461 15,466 17,328-7% 16% 30% Biomass (electricity) 80 19,946 16,120 20,440 22,663-19% 2% 14% RES-heat Biogas 4,450 1,683 2,194 2,586-62% -51% -42% 60 Bioliquids 4,405 n.a. n.a. n.a. n.a. n.a. n.a. Solid biomass 81,192 63,211 68,685 90,379-22% -15% 11% Biomass (heat) 40 90,047 64,895 70,879 92,965-28% -21% 3% Biofuels First generation biofuels 19,059 13,642 13,642 12,642-28% -28% -34% Second generation biofuels 20 2,498 2,028 2,379 2,941-19% -5% 18% Biofuel import / export 7,376 14,718 14,865 12, % 102% 74% Biomass (transport) 0 28,933 30,388 30,886 28,418 5% 7% -2% Biomass (transport - domestic) 21,558 15,670 16,021 15,583-27% -26% -28% Aggregated level EU27 Biomass (domestic) 131,550 96, , ,211-27% -18% 0% Summary: Demand for biomass NREAP Green-X Comparison Green-X vs. NREAP BAU BAU barriers mitigated* SNP BAU BAU barriers mitigated* SNP

9 AT BE BG CY CZ DE DK EE EL ES FI FR HU IE IT LT LU LV MT NL PL PT RO SE SI SK UK EU27 Demand for biomass Comparison of the NREAPs with recent Green-X scenarios Comparison: the best match can be observed for SNP A closer look on the deviations to the NREAP figures 150% SNP - deviation to NREAP [%] Biomass (electricity) Biomass (heat) 125% 100% 75% 50% 25% 14% 3% 0% -25% -50% -75% -100% Overall deviation at EU level: 14% for electricity, 3% for heat (general pattern: SNP demands more biomass) PRIMES reference (2010) represents no high energy efficiency scenario i.e. it is characterised by a 8% higher gross final consumption Specifically the demand for heat is higher (11%)

10 Modeling bioenergy in Green-X Potentials and cost supply curve derivation Key consideration by deriving the primary bioenergy potentials: a) A comprehensive assessment of available information on current patterns with respect to biomass supply and use, based on processing of statistical information on agriculture and forestry (e.g. FAOSTAT, Eurostat) complemented by related other information as applicable from National Renewable Energy Action Plans as well as previous / ongoing assessments in this topical area.* b) A transformation of the detailed information on rules / legislations regarding biomass sustainability criteria in order to derive for each key case a different database for model implementation, containing policy information regarding sustainability criteria as well as corresponding potentials & cost for bioenergy. * This comprises e.g. the assessments of biomass potentials & cost as undertaken within the ongoing EU FP7 BEE project (for EU potentials) and the IEE project RESHAPING and the corresponding global assessment as undertaken within IEA Task 40 on bioenergy trade as well as previous studies as conducted at the European level (e.g. the REFUEL project).

11 Green-X allows for targeted information on biomass availability and end-use as well as the related costs and benefits as e.g. in terms of avoided GHG emissions. Additionally, general results are provided with respect to policy costs (i.e. support expenditures), capital expenditures and environmental and economic costs & benefits. Modeling results on technology and member state level is available on an annual basis in the time horizon of 2020/2030, among others, in terms of : Available generation potential of biomass technologies Quantity of biomass production, use and trade (both Intra-European Trade and trade from abroad) Average costs of biomass feedstock Share of forest cover and agricultural land area Quantity of biowaste generated Modeling bioenergy in Green-X Potentials and cost supply curve derivation Greenhouse gas avoidance due to RES (in particular biomass) use Share of RES (in particular biomass) in gross final energy use The geographical scope of the Green-X model is currently constrained to the Members States of the European Union.

12 Modeling bioenergy in Green-X Allocation of feedstock to technology clusters Key consideration by deriving the primary bioenergy potentials on MS level: AP1 (rape & sunflower) AP2 (maize, wheat - corn) AP3 (maize, wheat - whole plant) AP4 (SRC willow..) AP5 (miscanthus) AP6 (switch grass) AP7 (sweet sorghum) AR1 (straw) AR2 (other agri residues) FP1 (forestry products - current use (wood chips, log wood) FP2 (forestry products - complementary fellings (moderate)) FP3 (forestry products - complementary fellings (expensive)) FR1 (black liquor) FR2 (forestry residues - current use) FR3 (forestry residues - additional) FR4 (demolition wood, industrial residues) FR5 (additional wood processing residues (sawmill, bark) FR6 (forestry imports from abroad) FR7 (forestry imports from abroad - class2) BW1 (biodegradable fraction of municipal waste) BG (agricultural biogas) LG (landfill gas) SG (sewage gas) GWh, EUR/GWh, g Support schemes BMC-1 BMC-2 BMC-3 BMC-4 BMC-5 BMC-6 BMC-7 BMC-8 BMC-9 BMC-10 BMC-11 BMC-12 BMC-13 BMC-14 BMC-15 BMC-16 BMC-17 BMC-18 BMC-19 BMC-20 max (profit)= max Feedstock (profit)= support level LRMC/g fuel cost support level allocation LRMC/g fuel cost trade costs Biodiesel T Bioethanol T Bioethanol+ T BtL T Logg w ood N Wood chips N Pellets N Bio-ELE E Bio-CHP C Cofiring E Biow aste C&E District heat H Cofiring CHP C Bio-ELE large H Bio-CHP large C Biow aste large C&E Biogas E Biogas C BCS E BGT E Attention: restrictions are considered by limited potentials or diffusion constraints

13 Modeling bioenergy in Green-X Internal European Biomass trade primary energy trade A node to node model is applied in Green-X Bilateral or multilateral trade Information of status quo of trade Potentials for enhanced trade options Only certain feedstock categories are qualified for trading

14 Modeling bioenergy in Green-X Internal European Biomass trade primary energy trade Remark: Modelling of biomass trade within Green-X Intra-European biomass trade is considered on feedstock level for all relevant feedstock categories (i.e. wood pellets, wood chips and other solids as identified being relevant trade commodities) within the Green-X model. Thereby, the impact of trade will be applicable for new biomass installations (2011 to 2020) existing plants can either remain within their prior supply patterns or act on trade market as well but generally long-term contracts are issued, keeping existing plants at their prior supplier. In general, Member States can trade their surpluses of bioenergy on a bilateral basis or on multilateral platforms whereby the cost of transporting are reflected in the price of related feedstock. Green-X assumes that the real way of transportation does not matter in terms of transport fees. Therefore the transport costs are the same regardless the route of transportation through Europe. Moreover, it is assumed that also the type of transportation does not have an impact of the transport fee since a traditional weighted average of the status quo is assumed. Consequently, also the CO2 emissions of the transportation type are averaged according to the cost of transport in order to guarantee the sustainable use of biomass at its final destination.

15 Modeling bioenergy in Green-X Primary biomass in 2020 (NREAPS) Surplus Spain France Poland Bulgaria Portugal Estonia Shortage Germany Netherlands UK Belgium Italy Denmark IE PT Green-X (supply) NREAPS (demand) Surplus/deficit UK NL BE LU FR ES DK DE AT IT SE CZ? SK PL HU GR EE LV LT? BG FI RO MT

16 Modeling bioenergy in Green-X Potential intra EU biomass trade flows for heat and electricity in 2020 Based on surplus/deficit: Exporting countries Spain France Poland Bulgaria Portugal Estonia Greece Lithuania Importing countries Germany Netherlands UK Belgium Italy Denmark Czech Republic IE UK FR BE NL LU DK DE IT AT SE CZ PL SK HU FI EE LV LT RO BG PT ES GR MT

17 Conclusions Comparison of the NREAPs with recent Green-X scenarios Comparison: The search for reasons why the scenario differ what do the NREAPs tell us? what can we learn from an assessment of them? The NREAPs submitted are of different quality and completeness. It appears that several countries have taken the obligation serious to provide a complete and comprehensive RES roadmap up to 2020, indicating what is in place and what needs to be done. Others drew a nice picture on the implemented measures to stimulate an enhanced RES deployment which does not in all cases match with reality. Very few countries provided a minimalistic and incomplete report. It can be seen that substantial optimisation potential exists for all five categories. The strongest deficits exist in the field of administrative procedures and spatial planning followed by the category support measures for RES heating and cooling. The highest optimisation potentials exist in these two areas. But even the section of support measures in the electricity sector receives only a neutral evaluation on average showing room for improvement in many EU member states. (Ragwitz, Resch, 2011 Assessment of the NREAPs (REPAP2020 report interim status)

18 Conclusions Results of the internal EU biomass trade application Their is an substantial market for biomass trade Traded biomass must still be sustainable according to the Directive Most existing plants receive their biomass via long-term contracts Bioenergy trade shall first be used at domestic plants in order avoid an selling out of cheap biomass and therefore increase domestic production costs

19 20% RES by 2020: Biomass role in the Renewable Energy Directive 2020 energy futures Thank you for your attention! Contact Dipl.-Ing. Christian Panzer Energy Economics Group (EEG) Technische Universität Wien Gusshausstraße 25-29/E Wien, Austria AEBIOM conference Brussels, June, 29 th 2011 Slide 19