competitiveness of conventional and advanced biofuels · competitiveness of conventional and...
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Competitiveness of conventional and advanced biofuelsDaniela Thrän, Markus Millinger, Stefan Majer
Sustainable First and Second Generation Bioethanol for Europe: Opportunities for People, Planet and Profit International Conference, 26 Sep. 2017, Brussels
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BACKGROUND ‐ Biofuels Production and Use
Total biofuels volume and trade has been stabilised
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BACKGROUND – RED recast
� Transport:
• Cap for „conventional fuels“ from agricultural biomass (Art. 7)¾ The maximum contribution of conventional
fuels is limited to 7% and¾ shall be reduced (in a stepwise approach) to
3.8% until 2030
• Mandatory, increasing targets for advanced fuels ¾ The contribution of advanced fuels shall be
increased from 1.5% in 2021 to¾ 6.8% (with a minimum share of 5,3%
advanced biofuels) in 2030.
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7,0%6,7%
6,4%6,1%
5,8%5,4%
5,0%4,6%
4,2%3,8%
2021 2022 2023 2024 2025 2026 2027 2028 2029 2030
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BACKGROUND – Expectation on Future Mobility
� Transport sector emits 20% of e.g. German GHG emissions� Biofuels reduce GHG impact today (.g. 5 Mt CO2eq in Germany
2016) � Biofuels will also reduce GHG impact until e.g. electric vehicles
take over� Costs of biofuels are crucial
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Better understanding of competiveness of different biofuels is key
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BACKGROUND ‐ Biomass Potentials in 2050
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Potenzial in EJ a‐1
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∑ Min ∑ Mi elwert ∑ Max
Uncertainties in energy crop potentials lead to uncertainties in futurebiomass prices
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BACKGROUND – Advanced Biofuels
Advanced lignofuels vs conventional:+ potentially less food/fuel, GHG & LUC(expected)
+ higher potential and better economics(expected)
‐ Not yet in the market: large uncertainties on all parameters
Biomass usage is a complex field connec‐ted to many sectors, with trade‐offs:� Economic: investment vs feedstock cost� Environmental: land use, LUC, GHG, etc.
Æ Scenario modelling of biofuel futuresnecessary to depict complexity andhighlight uncertainties
Haarlemmer, et.al.. Second generation BtL type biofuels – a production cost analysis. Energy & Environmental Science, 5(9):8445, 2012. ISSN 1754‐5692. doi: 10.1039/c2ee21750c.
3x
4x
FT‐diesel investment andproduction cost uncertainty
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APPROACH
1. Long term policy strategies come into practice by day‐to‐day investorsdecisions
2. Assuming the biofuels sector as a level‐playing‐field we wanted toknow which biofuel option will be realised if a country decides forincreasing biofuels utilisation
3. We include R&D effort (technical learning) and higher prices for GHG emission certificates as political elements to govern the system
4. We considered dynamics in the agricultural sector (crop selectionbased on scenarios for feedstock costs)
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APPROACH ‐ Biofuels Options IncludedBiofuel Feedstock Process
Biodiesel Rape seed Transesterification
Bioethanol Sugar beet Fermentation
Biomethane Maize (+ manure)
Anaerobic Digestion
FT-Diesel („BtL“)
„Woody“ biomass
GasificationSynthetic Natural Gas (bio-SNG)
Lignoethanol Pre-treatment + fermentation
• Data: investment cost, O&M, input‐output, conversion efficiency, learning rate, feedstock costs
• Focus on for‐purpose energy crops• BTL and LignoEtOH similar data, latter higher investmentÆ BTL proxy in the results• Bioethanol from grains due to high feedstock costs excluded pre‐modelling
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METHOD BENSIM (BioENergy SImulation Model)
• Myopic least‐cost simulation• Technological learning• Matlab based• Bottom‐up• German frame condition
(biofuel demand: 119‐400 PJ/a)1. If TCtech < MCsystemÆ Investment until
equilibrium2. Production in merit order3. Learning effectÆ Investment cost
reductions
MCsystem
PJ
€
TC
CapacityTech 1
MC
BIOFUEL TARGET
MCsystem
0200400600800
1000120014001600
1990 2000 2010 2020 2030 2040 2050
Biomass potential available for modelling (historic*)
Biomass already used for bionenergy production (historic*)
Biomass potential available for modelling
Biomass already used for bionenergy production
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METHODESTIMATING POTENTIAL BIOMASS PRICE DEVELOPMENTSAt what price does it make sense for farmers to switch to energy crops?• Assumed development for benchmark feedstock (wheat)• Other feedstocks to achieve same revenue as benchmark per hectareÆ minimum feedstock price developments• Risk considerations for perennials not included
2020 2030 2040 2050
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40MaizeSugar beetRape seedPoplarWillowMiscanthusWheat
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RESULTSConstant wheat price Wheat price +2%/year Wheat price +4%/year
All
fuel
s in
clud
edLi
quid
fuel
s on
ly
Diesel alternatives not competitive!Æ Quotas not most cost‐efficient biomass use
At higher feedstock costincreases, land use efficiencyincreasingly importantÆ Advanced biofuels not better than someconventional
EtOH from sugar beet mostcompetitive in all cases, Biomethane at higherfeedstock costs
Feedstock prices increasing
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RESULTS• Of advanced fuels, Bio‐SNG significantly
more competitive than BTL or LignoEtOH
• Feedstock costs are most importantdriverÆ inhibits investment
• Technological learning plays a small role(efficiency improvements moreimportant)
• Also GHG emission prices will play a roleif there is a wide spread between thebiofuels (e.g. iLUC debate)
• At higher feedstock cost developments, land use becomes keyÆMaize‐basedbiomethane long‐term most competitive
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DISCUSSION
• The BENSIM‐model makes it possible to include a multitude of aspects into one integrated scenarioassessment with extensive sensitivity analsis.Work in progress on e.g. GHG‐abatement, long‐term optimization, end‐use scenarios, EU‐level andelectrofuels.
• Several challenges / possible barriers for a transition to advanced fuels have to be consideredadditionally:• Feedstock transportability („flexible crops“)• Efforts and uncertainties for market
introduction of new technologies• Gas vehicle market• PerennialsÆ Risk for farmers
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CONCLUSIONS AND OUTLOOK
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The choice of (bio)fuels is only one uncertainty of future transport systems. To use their potental for GHG emssion reduction we conclude: • Regarding the biomass: Biofuels from food crops (sugar and maize)
are cost competitive also in the long run• Regarding the biofuel types: Gaseous fuels are advantageous if
advanced fuels are required (SNG) or at high feedstock costdevelopments (biomethane)
• Regarding the actual markets: Diesel alternatives not competitiveÆ quotas do not lead to most cost‐efficient result
• Regarding the uncertainties: Focusing policy on high yielding fuelsdecreases cost uncertaintyÆ But total GHG‐Abatement and ecologyneeds to be taken into account!
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THANK YOU!
Contact:[email protected]@[email protected]
References:EU (2016), Proposal for a directive of the European Parliament and of the council amending Directive 2010/31/EU on the
promotion of the use of energy from renewable sources (recast). COM/2016/0767 final/2 – 2016/0382 (COD).Haarlemmer, et.al. (2012). Second generation BtL type biofuels – a production cost analysis. Energy & Environmental
Science, 5(9):8445, 2012. ISSN 1754‐5692. doi: 10.1039/c2ee21750c.Millinger, M., Thrän, D. (2016): Biomass price developments inhibit biofuel investments and research in Germany: The
crucial future role of high yields. Journal of Cleaner Production. Millinger, M., Ponitka, J., Arendt, O., Thrän, D. (2017): Competitiveness of advanced and conventional biofuels: Results
from least‐cost modelling of biofuel competition in Germany. Energy Policy. 107, 394‐402Naumann, K.; Oehmichen, K.; Remmele, E.; Thuneke, K.; Schröder, J.; Zeymer, M.; Zech, K.; Müller‐Langer, F. (2016):
Monitoring Biokraftstoffsektor. 3. überarbeitete und erweiterte Auflage. Leipzig: DBFZ (DBFZ‐Report Nr. 11). ISBN 978‐3‐946629‐04‐7.
Thrän, D., Schaldach, R., Millinger, M., Wolf, V., Arendt, O., Ponitka, J., Gärtner, S., Rettenmaier, N., Hennenberg, K., Schüngel, J., (2016). The MILESTONES modeling framework: An integrated analysis of national bioenergy strategiesand their global environmental impacts. Environ. Modell. Softw. 86 , 14