Overview of Bioenergy Scenarios in TIMES modelling

Transcription

1 Overview of Bioenergy Scenarios in TIMES modelling Prof. Brian Ó Gallachóir Chair IEA ETSAP TCP Executive Committee IEA-ETSAP IEA-Bioenergy Session, 72 nd IEA ETSAP Workshop ETH Zurich, Dec

2 What is IEA ETSAP? One of 38 IEA Technology Collaboration Programmes 41 years international cooperation on energy systems modelling (since first oil crisis) Develop and maintain (MARKAL and TIMES) tools Assist policy makers to build future energy pathways Focus on key role of technology to meet goals Biannual workshops and training Collaborative research and analyses

3 IEA ETSAP Activity Unique network of Energy Modelling teams from almost 70 countries use MARKAL & TIMES models analyse energy systems and support decision making in energy policy.

4 Key Recent Developments Kazakhstan and Australia have joined ETSAP as Contracting Parties Enel Foundation and GE Energy have joined as sponsors. Japan and USA have reengaged as active ETSAP participants Modelling teams have formed in South Africa, Portugal, China and Pakistan ETSAP providing training to Argentina 2016, Brazil 2017 and Mexico 2018 Improved techniques for modelling interactions between energy systems and i) macro-economy, ii) power systems and iii) society Joint workshops with IEEJ (Japan), Univ of Sao Paolo (Brazil), DoE Fossil Energy (USA) and IEA-GHG TIMES listed as one of the four selected modelling tools in the UNFCC guide for preparing the national communications for non-annex I parties (NDCs provide significant opportunity for capacity building).

5 IEA ETSAP Outputs > 100 publications per annum (including 50 peer review journal papers) from: i) Global Models: incl. IEA ETP model, original TIMES Integrated Assessment Model (TIAM), derived TIAM models, ETSAP-TIAM model ii) Regional Models: Pan European TIMES model, MARKAL TIMES Models for Europe, Asia and North America. Multi-regional models iii) National Models of 32 countries (including China). iv) Sub National Models: Western China, Reunion Island (France), Lombardy (Italy), Pavia (Italy), and Kathmandu Valley (Nepal). v) Local Models for rural areas and cities in Austria, Germany and Italy, other bigger cities such as Madrid (Spain), Beijing, Guangdong and Shanghai (China), Johannesburg (South Africa) and New York City (United States).

6 11,295 Chapter downloads - one of the top 25% most downloaded ebooks in the relevant SpringerLink ebook Collection in 2016 IEA ETSAP Book 2015 Methodologies and case studies Demonstrating use of energy systems models Supporting energy and climate policy Critical analysis of rich and varied applications Includes diverse global case studies Role of technology in energy systems

7 TIMES Model linear programming bottom-up energy model integrated model of the entire energy system medium to long term analysis climate and energy policy analysis ( years) partial and dynamic equilibrium (perfect market) optimal technology selection minimize the total system cost environmental constraints system understanding of how technical challenges and technoeconomic costs change over time, and for different levels of (mitigation or renewable or ) ambition

8 TIMES Model Given Technology data End-use demands Fuel Supply curves Emission constraints Other parameters Discount rate Time period definition Time slice definition Models provide Technology investments Technology activities Emission trajectories Adjusted demands Marginal energy prices Imports/Exports Permit trading Total system cost

9 ETP modelling framework Primary energy Conversion sectors Final energy End-use sectors Service demands Renewables Electricity Gasoline Industry TIMES models Material demands Fossil Nuclear Electricity and heat generation Buildings Long-term simulation etc. Transport Fuel/heat delivery ETP-TIMES Supply model (bottom-up optimisation) Mobility Model (MoMo) Four soft-linked models based on simulation and optimisation modelling methodologies Model horizon: in 5 year periods Electricity T&D Fuel conversion Diesel Natural gas World divided in model regions/countries depending on sector For power sector linkage with TIMES dispatch model for selected regions to analyse electricity system flexibility Heat Space heating Water heating Lighting Passenger mobility Freight transport OECD/IEA 2017

10 Bioenergy-based technology routes in the supply-side model Primary bioenergy Biofuel conversion processes End-use sectors Agriculture residues, manure Hydrogen Gasification (w/o and w CCS) Biogas Anaerobic digestion Gasification (w/o and w CCS) Final energy (solid, liquid and gaseous bioenergy; hydrogen) Agriculture Forest residues Bio-ethanol (w/o and w CCS) Starch Sugar cane Lignocellulose Power sector technologies Buildings Energy crops Municipal waste Biodiesel FAME (fatty acid methyl ester) HVO (hydrogenated vegetable oils) Fischer-Tropsch (w/o and w CCS) Solid bioenergy Transport & processing Charcoal production Torrefaction Electricity-only and CHP ICE (internal combustion engine) Open-cycle gas turbine Combined-cycle turbine Steam turbine (grate firing, FBC) Biomass co-firing BIGCC w/o and w CCS Heat boiler Electricity District heat Process heat Industry Transport Global trade in liquid biofuels From industry sector Black liquor Bagasse OECD/IEA 2017

11 How far can technology take us? 40 Reference Technology Scenario RTS GtCO Technology area contribution to global cumulative CO 2 reductions Global CO 2 reductions by technology area Gt CO 2 cumulative reductions in degrees Scenario 2DS Beyond 2 degrees Scenario B2DS Efficiency 40% 34% Efficiency 40% Renewables Renewables 35% 15% 35% Fuel switching Fuel 5% switching 5% 18% Nuclear 6% Nuclear CCS 14% 6% 1% CCS 14% 32% Pushing energy technology to achieve carbon neutrality by 2060 could meet the mid-point of the range of ambitions expressed in Paris. OECD/IEA 2017

12 Post Paris - Beyond Example 80% 1 IEA Mitigation ETP Current bioenergy use = 63 EJ per annum (half of which traditional bioenergy use) = 11% of final energy use globally Sustainable bioenergy potential ~ EJ per annum In IEA ETP 2017, bioenergy use is focussed on sectors with limited decarbonisation options IEA ETP 2017 estimates we need approx. 145 EJ p.a. bioenergy for 2DS (2 O C Scenario) with a focus on transport (30 EJ) with 2-3 EJ from biogas B2DS (Below 2 O Scenario) with a key need for negative emissions (i.e. bioenergy with CCS (BECCS))

13 Post Paris - Beyond Example 80% 1 IEA Mitigation ETP Global bioenergy use 2015 source IEA 46 EJ final demand from 63 EJ primary energy

14 Optimising the use of sustainable biomass EJ Bioenergy use by sector RTS 2DS B2DS Today 2060 Transport Industry Buildings Agriculture Fuel transformation w BECCS Fuel transformation Power w BECCS Power Around 145 EJ of sustainable bioenergy is available by 2060 in IEA decarbonisation scenarios, but gets used differently between the 2DS and the B2DS. OECD/IEA 2017

15 Post Paris - Beyond Example 80% 1 IEA Mitigation ETP Bioenergy contribution to final energy use Comparing 2DS and B2DS Source IEA ETP 2017

16 Post Paris - Beyond Example 80% 1 IEA Mitigation ETP Elec gen from Bioenergy - Comparing 2DS and B2DS - Source IEA ETP 2017

17 Post Paris - Beyond Example 80% 1 IEA Mitigation ETP IEA ETP DS - global bioenergy use in transport

18 Post Paris - Beyond Example 80% 2 Mitigation Ireland Chiodi A.; Gargiulo, Deane, J.P., Ó Gallachóir, B.P The role of bioenergy in Ireland s low carbon future is it sustainable? Journal of Sustainable Development of Energy, Water and Environment Systems 3(2), pp Czyrnek-Delêtre M., Chiodi A.; Murphy J.D.; Ó Gallachóir B Impact of including land use change emissions from biofuels on meeting GHG emissions reduction targets - the example of Ireland Clean Technologies and Environmental Policy 18 Pages

19 Post Paris - Beyond Example 80% 2 Mitigation Ireland Hypothesis Impact of LUC emissions on the Irish energy system is significant Objectives Analyse current and future domestic bioenergy sources and bioenergy trade networks Implement DLUC and ILUC emissions factors for all bioenergy commodities in the Irish TIMES Assess the implications of above for Irish energy system

20 Post Paris - Beyond Example 80% 2 Mitigation Ireland DLUC emissions DLUC assumptions Based on literature Exploratory EU CAP Zero DLUC Negative DLUC Conservative approach Conversion of grassland to arable land is restricted Corn, sugar beet, wheat, oilseed rape domestic and from EU Miscanthus and willow : as perennial they accumulate soil organic carbon Sugar beet and sugarcane ethanol, oilseed and palm biodiesel from outside EU

21 Post Paris - Beyond Example 80% 2 Mitigation Ireland ILUC emissions ILUC assumptions Based on literature Controversial ILUC+ optimistic ILUCconservative No widely accepted/used methodology No or low ILUC emissions High ILUC emissions

22 Post Paris - Beyond Example 80% 2 Mitigation Ireland ILUC+ and ILUC- ILUC + ILUC - Grass biomethane Miscanthus, willow, wheat ethanol and oilseed biodiesel Oilseed biodiesel, sugar beet and wheat ethanol Abundance of grass Biomes converted to barley Biomes converted to cropland Tropical rainforest converted to pasture Biomes converted to barley Biomes converted to cropland Sugarcane ethanol Cerrado grassland converted to pasture Tropical rainforest converted to pasture Palm oil biodiesel Peatland rainforest to cropland Lowland rainforest to cropland Corn ethanol Grassland converted to cropland (non EU) Forest and grassland to cropland

23 Post Paris - Beyond Example 80% 2 Mitigation Ireland ktoe Total Primary Energy Requirement 2010 CO2-80 CO2-80 DLUC CO2-80 ILUC+ CO2-80 ILUC- CO2-80 CO2-80 DLUC CO2-80 ILUC+ Other Renewables Biogas Bioliquids Solid biomass Gas Oil Coal Increase in bioenergy CO2-80 ILUCktoe

24 Post Paris - Beyond Example 80% 2 Mitigation Ireland ktoe Total Primary Energy Requirement 2010 CO2-80 CO2-80 DLUC CO2-80 ILUC+ CO2-80 ILUC- CO2-80 CO2-80 DLUC CO2-80 ILUC+ Other Renewables Biogas Bioliquids Solid biomass Gas Oil Coal Increase in efficiency Reduction in bioenergy CO2-80 ILUCktoe

25 Overview of Bioenergy Scenarios in TIMES modelling Prof. Brian Ó Gallachóir Chair IEA ETSAP TCP Executive Committee IEA-ETSAP IEA-Bioenergy Session, 72 nd IEA ETSAP Workshop ETH Zurich, Dec

26 TIMES Model Energy prices, Resource availability Cost and emissions balance Domestic sources Imports Primary energy Coal processing Refineries Power plants and Transportation CHP plants and district heat networks Gas network Final energy Industry Commercial and Public Services Households Transportation GDP Process energy Heating area Population Light Communication Power Person kilometers Freight kilometers Demands Service Demands

27 ETSAP TIAM Global model (ETSAP-TIAM) now available in addition to modelling tools (TIMES) 15 Region global TIMES model available to ETSAP Contracting Parties Developed by GERAD and currently updated by ETSAP Collaborative Project Includes several thousand technologies and models climate forcing

28 Maximise net Net social Social surplus Surplus

29 Minimising Minimise Total System System Cost Costs REFYR y NPV = ( 1+ dr, y ) ANNCOST ( y) y YEARS where: NPV is the net present value of the total cost (the OBJ); ANNCOST(y) is the total annual cost in year y; d r,y is the general discount rate; REFYR is the reference year for discounting (2005); YEARS is the set of years for which there are costs in the horizon

30 Total System Cost Capital Costs incurred for investing and dismantling plant; Fixed and variable Operation and Maintenance (O&M) Costs; Costs for exogenous imports and for domestic resource production; Revenues from exogenous exports; Delivery costs for required fuels consumed by plant; Taxes and subsidies associated with fuel flows and plant activities; Salvage value of plant at the end of the planning horizon; Welfare loss resulting from reduced end-use demands.

31 IEA ETSAP in summary Two workshops per year, one organized together with IEW 3-5 TIMES model training sessions around the world approx 200 teams involved from the whole world access to support and discussion forums jobs within TIMES modelling new tools and analyses are shared close collaboration with IEA, IRENA, Worldbank, etc. documentation: Annex report - Meetings - Projects - Model generator & user interface - Technologies -

32 Depicting reality in an ESM Reality Model structure P O Q = η P BHKW _ S BHKW Coal _ BHKW BHKW _ CO2 = ε P Coal _ BHKW = η P BHKW _ H 2_ BHKW Coal _ BHKW Mathematical description Cross-checking results with reality. Feedback 4a Entwicklung der Kernenergiekapazitäten (Netto-Engpassleistung am Jahresende) in Deutschland bis 2030 (Basis PJ 10 0 Household Transport Industry Optimiser (CPLEX/MINOS/CON OPT/XPRESS/etc.) Energieträger Einheit e 2020e 2025e 2030e Kernenergie MW a b Entwicklung Kernenergiekapazitäten (Netto-Engpassleistung am Jahresende) in Deutschland (Basis der bis 2030 Energieträger Einheit e 2020e 2025e 2030e Kernenergie MW b Entwicklung und Erzeugung aus regenerativen Energiequellen (Mindestmengen) Deutsch der Kapazitäten der in Energieträger Einheit e 2020e 2025e 2030e Sonne GW 5.1a 0,11 0,71 1,31 1,61 1,91 5.1b Sonne TWh p.a. 0,07 0,60 1,00 1,28 1,52 5.2a Wind GW 6,11 23,10 25,60 26,90 28,10 5.2b Wind TWh p.a. 9,50 43,54 57,96 64,02 70,08 5.3a Biomasse GW 0,59 0,80 1,00 1,10 1,20 5.3b Biomasse TWh p.a. 1,63 2,55 3,60 4,20 4,80 6 Energie- und Umweltpolitik in Deutschland 2030 bis Größe Einheit e 2020e 2025e 2030e Model results Model Scope CO2-Zertifikatehandel 6,1 nein ja ja ja ja (Strom u. Industrie) 6,2 CO2-Zertifikatepreis 2000/tCO Data 2-3,00 9,00 12,00 14,00

33 ETSAP Tools