2 nd International Expert Meeting on Bottom-up Based Analysis on Mitigation Potential. Overview of DNE21+ Systems Analysis Group

Transcription

1 2 nd International Expert Meeting on Bottom-up Based Analysis on Mitigation Potential Novotel Paris Tour Eiffel, Paris, France, 21st October, 28 Overview of DNE21+ (Dynamic New Earth 21+) model Fuminori Sano and Keigo Akimoto Systems Analysis Group Research Institute of Innovative Technology for the Earth (RITE)

2 Overview of DNE21+ model Sectoral details Power sector Industrial sector Transportation sector Residential & Commercial sector Contents 2

3 Assessment Framework: DNE21+ Model Linear programming model (minimizing world energy system cost) Target gas: CO 2 from fossil fuel combustion We have different model for evaluation of other GHGs (CH4, N2O and Fgas). Evaluation time period: 2-25 Representative time points: 2, 25, 21, 215, 22, 225, 23, 24, 25 World divided id d into 54 regions Large area countries are further divided into 3-8 regions, and the world is divided into 77 regions. Bottom-up modeling for technologies both in energy supply and demand d sides. Primary energy: coal, oil, natural gas, hydro&geothermal, wind, photovoltaics, biomass and nuclear power Electricity demand and supply are formulated for 4 time periods: instantaneous peak, peak, intermediate and off-peak periods Interregional trade: coal, crude oil, natural gas, syn. oil, ethanol, hydrogen, electricity and CO 2 Existing facility vintages are explicitly modeled. -The model has high resolutions in regions and technologies to analyze sectoral approach. - Consistent analyses among regions and sectors can be conducted. 3

4 Region Divisions of DNE21+ 4 World divided into 54 regions

5 Overall flow in DNE21+ 5 Fossil fuels Coal Oil (conventional, unconv.) Gas (conventional, unconv.) Unit production cost Cumulative production Renewable energies Hydro power & geothermal Wind power Photovoltaics Biomass Unit supply cost Annual production Nuclear power Energy conv. processes (oil refinery, coal gasification, bioethanol, gas reforming, water electrolysis etc.) Electric Power generation CCS Industry Iron & steel Cement Paper & pulp Chemical (ethylene, propylene, ammonia) Aluminum Solid, liquid and gaseous fuels, and electricity <Top-down modeling> Transport vehicle Solid, liquid and gaseous fuels, and electricity <Top-down modeling> Residential & commercial Refrigerator, TV, air conditioner etc. Solid, liquid and gaseous fuels, and electricity <Top-down modeling>

6 Power sector (1/3) Capital costs and generation efficiencies of power generation plants (coal, oil, gas, biomass, nuclear, IGCC/IGFC with CO 2 capture, oxy-fuel combustion power generation using natural gas, and hydrogen) are assumed exogenously. Post-combustion CO 2 capture technologies for power generation plants are also modeled. Annual expense rates, facility utilization rates and lifespan are assumed for all technologies. Assumptions of coal power generation plants Technologies Capital costs [US$/kW] Power generation efficiency [LHV %] Low efficiency Medium efficiency High efficiency 1, IGCC/IGFC with CO 2 capture 1,7 1,

7 Power sector (2/3) For hydro power & geothermal, wind power and photovoltaics, the costs per power generation amount [US$/MWh] are assumed. For huge connection of wind power and photovoltaics to grid, storage battery technology costs for maintaining stability of power system are assumed. 7 Assumptions of costs per power generation Wind power Photovoltaics 12 5 ion cost (US2$ $/MWh) Generat Grade 1 Grade 2 Grade 3 ion cost (US2$ $/MWh) 4 3 Grade 4 2 Grade 5 Generat 1 Grade 1 Grade 2 Grade 3 Grade 4 Grade Year Year

8 Power sector (3/3) Example of calculation results - Global electricity generation - 8 Base case (<$/tco 2 ) [TWh/yr] PV Wind power Nuclear 3 Comparison (Y22) PV ity generation Electrici Year Hydro&Geothermal Biomass Gas Oil Electric city generatio on [TWh/yr] Coal 1 5 Wind power Nuclear Hydro&Geothermal Biomass Gas Oil Coal Base case ( $/tco2) $25/tCO2

9 Industrial sector (1/6) Bottom-up modeling: Iron&Steel, Cement, Paper&Pulp, Chemical (Ethylene, Propylene, Ammonia) and Aluminum 9 Top-down modeling (Energy savings are modeled with long-term price elasticity): Other industrial sectors Capital costs and energy efficiencies of various technologies in 5 bottom- up modeling sectors are assumed exogenously. CCS technologies are assumed for Iron&Steel sector. Material production of each sector is assumed as exogenous scenario; industrial structure change is not evaluated endogenously, but exogenously.

10 Industrial sector (2/6) 1 Iron ore, etc. Overview of Iron&Steel sector model Coal Natural gas or H2 Coke oven, sintering furnace, BF, BOF, casting, and hot rolling Steel product derived from BOF steel Type I IV IV : BF-BOF route Total steel (constraint) Scrap, etc. Electricity (grid) DRI production, EAF, casting, and hot rolling Type VIII, IX : DRI-EAF route EAF, casting, and hot rolling Type V VII : Scrap-EAF route Steel product derived from DRI-based EAF steel Steel product derived d from scrap-based EAF steel (Max.and Min. constraint)

11 Industrial sector (3/6) An example for high energy efficiency process (Type III & Type IV) in Iron&Steel sector 11 Coal for steel sector 24.1 GJ 23.8 GJ 22.5 GJ Type III: Current coke oven Recycling of waste plastics and tires.25 GJ Waste plastics and tires.25 GJ Type IV: Next-generation coke oven Blast furnace, sintering furnace, BF, BOF, casting, and hot rolling Type III and IV: High-eff. Intersection (Sophisticated steelmaking process with many energy saving facilities including CDQ, TRT, COG and LDG recovery) (Larger scale capacity plant) Electricity (grid) Power Electricity generation 455 kwh facility 91 kwh Carbon capture from BFG Utility 41GJ kwh.98 GJ Process gases recovery 8.6 GJ Steel product derived from BOF steel 1 ton of crude steel equivalent for each type BF: blast furnace, BOF: basic oxygen furnace, CDQ: Coke dry quenching, TRT: top-pressure recovery turbine, COG: coke oven gas, LDG: oxygen furnace gas Compressed CO 2.6 tco 2 Heavy oil

12 Industrial sector (4/6) Current differences in energy efficiency are considered as technology stock. 12 Comparison of energy efficiency Energy consum mption per unit prod oduction of ) crude steel (toe/ton-cs) US BF-BOF Iron & steel (2) scrap-eaf Canada UK France Note: Electricity is converted by using 1MWh=.86/.33toe. Source: Estimates by RITE from IEA (26), IISI (25) etc. Note: Electricity is converted by using 1MWh=.86/.33toe. Waste biomass use is excluded in the energy efficiency. Source: Estimates by RITE from Humphreys and Mahasenan (22), IEA (26) etc. Ge ermany Japan Australia Korea China India Energy co onsumption per unit production Russia US toe/ton-clinker toe/ton-cement Canada Cement (2) UK France Germany Japan Australia Korea China India Russia

13 Industrial sector (5/6) Production scenarios are assumed based on historical trends, scenarios of population&gdp, etc. r) steel production ion ton per year 粗鋼生生産量 ( 億トン / 年 )_ Crude s (1 2 mill Statistics 統計値 Assumed production scenarios Year China India US Japan Korea Russia Germany UK Spain Brazil Indonesia Iron & Steel (Crude steel production) Cement (Cement production) 統計値 Statistics China India 13 Cement produc tion (1 セメント生産量 2 million ton ( pe 億ト er トン year) / 年 ) Year US Japan Korea Russia Germany UK Spain Brazil Indonesia

14 Base case (<$/tco 2 ) Industrial sector (6/6) Example of calculation results - Global crude steel production - 14 Crudesteel/yr] roduction [Mton Crude steel pr 2 Scrap based EAF (High eff.) Year Scrap based EAF (Middle eff.) Comparison (Y22) Scrap based EAF (Low eff.) 18 Scrap based EAF (High eff.) DRI (High eff.) DRI (Middle eff.) BF BOF BOF (High eff. With Next generation coke oven) BF BOF (High eff.) BF BOF (Middle eff.) BF BOF (Low eff.) rudesteel/yr] Crude steel pro oduction [Mton C Scrap based EAF (Middle eff.) Scrap based EAF (Low eff.) DRI (High eff.) DRI (Middle eff.) BF BOF BOF (High eff. With Next generation coke oven) BF BOF (High eff.) BF BOF (Middle eff.) 2 Base case ( $/tco2) $25/tCO2 BF BOF (Low eff.)

15 Transportation sector (1/5) Bottom-up modeling: Small passenger car, Large passenger car, Bus, Small truck and Large truck 15 Top-down modeling (Energy savings are modeled with long-term price elasticity): Other transportation sector Capital costs and energy efficiencies of various technologies in 5 bottom- up modeling sectors are assumed exogenously. Traffic service demand of each category is assumed as exogenous scenario; Modalshift is not evaluated endogenously, but exogenously.

16 Transportation sector (2/5) 16 Gasoline Ethanol Overview of Transportation sector model Gasoline + Ethanol (<2%) Gasoline + Ethanol ( 2%) Light Oil Light oil + Bio diesel (<2%) Bio diesel GTL CNG Electricity Hydrogen Light oil + Bio diesel ( 2%) Light oil + GTL (<2%) Light oil + GTL ( 2%) Gasoline Engine base Passenger car (Small/Large) Bus Truck (Small/Large) Diesel Engine base Passenger car (Small/Large) Bus Truck (Small/Large) Passenger car (Small) Truck (Small) Passenger car (Small/Large) Bus Truck (Small/Large) Passenger car (Small) Passenger car (Large) Bus Truck (Small) Truck (Large) Pa assenger tr ransport [p- -km] Freigh ht transpor rt [t-km]

17 Transportation sector (3/5) 17 Technology description of small passenger car Fuel : Gasoline Ethanol Gasoline + Ethanol (<2%) Gasoline + Ethanol ( 2%) ICEV-Gasoline (Low-Eff.) ICEV-Gasoline (High-Eff.) ICEV-B-Gasoline ICEV-CNG Traffic Service Diesel engine base ICEV-Diesel (Low-Eff.) Light oil Bio diesel / GTL CNG Electricity Light oil + Bio diesel / GTL (<2%) Light oil + Bio diesel / GTL ( 2%) HEV-Gasoline HEV-B-Gasoline/ HEV-CNG HEV-Gasoline (Plug-In) HEV-B-Gasoline (Plug-In) Gasoline engine base EV ICEV-Diesel (High-Eff.) ICEV-B-Diesel / ICEV-GTL-Diesel HEV-Diesel HEV-B-Diesel / HEV-GTL-Diesel HEV-Diesel (Plug-In) HEV-B-Diesel / HEV-GTL-Diesel (Plug-In) Hydrogen FCHEV ICEV:Internal combustion engine vehicle, HEV:Hybrid-electric vehicle, HEV(Plug-In):Plug-In HEV EV:Electric vehicle, FCHEV:Fuel cell HEV, B:Vehicle which consumes high concentrated bio fuel

18 Transportation sector (4/5) Service scenarios are assumed based on historical trends, scenarios of population&gdp, etc. 18 Assumed service scenarios ce [Trillion p km/yr] Traffic Servi Year United States EU 27 Japan FUSSR Other Annex I countries China India Other Asia Middle East&Africa South America Traffic Service [Trillio n t km/yr] Small passenger car Large truck United States EU 27 Japan FUSSR Other Annex I countries China India Other Asia Middle East&Africa South America Year

19 Transportation sector (5/5) Example of tentative calculation results - Global passenger car traffic - 19 Base case (<$/tco 2 ) 25 Passeng ger car [1 9 km/y yr] Year FCHEV EV Plug In HEV HEV (Alternative fuel) HEV (Diesel) HEV (Gasoline) ICEV (Alternative fuel) ICEV (Diesel) ICEV (Gasoline) Passe enger car [1 9 km m/yr] Comparison (Y22) FCHEV EV Plug In HEV HEV (Alternative fuel) HEV (Diesel) HEV (Gasoline) ICEV (Alternative fuel) ICEV (Diesel) Base case ( $/tco2) $25/tCO2 ICEV (Gasoline)

20 Residential&Commercial sector Bottom-up modeling: Major appliances (Refrigerator, Television, Lighting, Air-conditioner for space cooling and gas stove) 2 Top-down modeling (Energy savings are modeled with long-term price elasticity): Other Residential&Commercial sector Capital costs and energy efficiencies of major appliances are assumed exogenously. Service demand of each appliance is assumed as exogenous scenario.

21 Assumption of Population & GDP 21 Population: UN26 Medium Scenario 1 (million people) Population Latin America Africa Middle East Other developing Asia India China Transition economies OECD Pacific OECD Europe OECD N. America Year GDP Y23: Based on the prospects by World Bank, Global Economic Prospects 27 Managing the Next Wave of Globalization (26) Y23 25: Based on IPCC SRES B2 (2) rates) prices and ex. r (trillion US$ at 2 GDP Year Latin America Africa Middle East Other developing Asia India China Transition economies OECD Pacific OECD Europe OECD N. America

22 Evaluation scheme of mitigation potential Technology-frozen case (Sectoral) fixes sectoral CO 2 intensity (CO 2 /output) at the level of 25. Base case of DNE21+ is fully considered the mitigation measures with negative cost. Mitigation potentials with positive cost are defined by differences from emissions i in Base case. CO 2 emission [G GtCO 2 /yr] Technology frozen case (Sectoral) Base case ( $/tco2) Year Negative cost Positive cost 22

23 Reduction Emission Reduction Potentials in Reduction Potentials from Sectoral Technology-frozen Case Marginal costs Emission reduction levels $/tCO $/tCO $/tCO2 <$/tco2 CO2 emission reduction potential [MtCO2/yr] Unit ed States EU-27 Japan Russia China India Note: emission reduction potentials of CCS excluded Annex I & OECD Major developing countries Other developing countries

24 Thank you for your attention. ti