Technology Bundle Approach with Parameter estimated from Bottom-up model to Integrate between Top-down and Bottom-up Model
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Technology Bundle Approach with Parameter estimated from Bottom-up model to Integrate between Top-down and Bottom-up Model
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Technology Bundle Approach with Parameter estimated from Bottom-up model to Integrate between Top-down and Bottom-up Model
- 1. INTERNAL USE ONLYINTERNAL USE ONLY Hiroshi Hamasaki Research Fellow, Economic Research Centre, Fujitsu Research Institute Visiting Fellow, Centre for International Public Policy Studies hiroshi.hamasak@jp.fujitsu.com hamasaki@cipps.org Amit Kanudia Partner, KanORS-EMR Technology Bundle Approach with Parameter Estimated from Bottom-up Model to Integrate between Top-down and Bottom-up Model 66th Semi-annual ETSAP meeting, 17-21 November 2014
- 2. INTERNAL USE ONLYINTERNAL USE ONLY Contents I. Overview of Linkage between CGE and TIMES II. Top-down Model: CRESH & Tech Bundle Approach in CGE Model III. Bottom-up Model: JMRT (Japan Multi-Regional Transmission Model) IV. Test Simulations V. Lessons Copyright 2014 FUJITSU RESEACH INSTITUTE1
- 3. INTERNAL USE ONLYINTERNAL USE ONLY I. Overview of Linkage between CGE and TIMES Copyright 2014 FUJITSU RESEACH INSTITUTE2 TIMES MODEL JMRT (Japan Multi-regional Transmission) Model CGE MODEL Based on GTAP Model CGE MODEL with Tech Bundle Technology Information in Electricity Sector Parameter
- 4. INTERNAL USE ONLYINTERNAL USE ONLY II. TOP-DOWN MODEL: CRESH & TECH BUNDLE APPROACH IN CGE MODEL Copyright 2014 FUJITSU RESEACH INSTITUTE3
- 5. INTERNAL USE ONLYINTERNAL USE ONLY Base CGE Model & Database GTAP Model version 6.2 2007 Based GTAP DB8 Copyright 2014 FUJITSU RESEACH INSTITUTE4 Description CHN China IND India JPN Japan KOR Korea ASIA Other Asia USA USA CAN Canada AUS Australia EU12 EU12 DEU Germany FRA France GBR UK RUS Russia CEU Central & Eastern Europe RoA1 Rest of Annex LSA Latin & South America RoW Rest of the World Description agr Agriculture coa Coal oil Oil gas Gas p_c Petroleum & Coal Product ely Electricity i_s Iron & Steel nfm Non-ferrous Metal min Mineral Product crp Chemical, Rubber and Paper omf Other Manufactruing trp Transport ser Service Sectors (13) Regions (17)
- 6. INTERNAL USE ONLYINTERNAL USE ONLY Step 1: Include “E” part in Conventional CGE Copyright 2014 FUJITSU RESEARCH INSTITUTE5 Output VA K L Intermediate Output VA Capital-Energy Composite L Intermediate ElectricityNon-Electricity Coal Non-Coal Gas Oil Petroleum Product Conventional CGE CGE Reflects “E” Part CapitalEnergy • This assumes that there is only one electricity generation technology. • This reflects just fuel- substitution, but technology substitutions. • Some of technologies do not use fossil fuels.
- 7. INTERNAL USE ONLYINTERNAL USE ONLY Step 2: Technology Bundle in Japan Ely Copyright 2014 FUJITSU RESEARCH INSTITUTE E G H E K L Nuc Gas Coal PV Ely_Nuc Generation VA Capital-Energy Composite L Intermediate ElectricityNon-Electricity Coal Non-Coal Gas Oil Petroleum Product CapitalEnergy Ely_Nuc Ely_Oil Ely_Gas Ely_Coal Distribution +Sales ＋ Generation Technology Distribution & Sales Electricity 𝝈 = 𝟎 I-O Table
- 8. INTERNAL USE ONLYINTERNAL USE ONLY • If all is equal, the production function is CES. • If , Leontief • If , Cobb-Douglas CRESH Production Function (Hanoh, 1971) Copyright 2014 FUJITSU RESEARCH INSTITUTE7 Ely_Nuc Generation Ely_Oil Ely_Gas Ely_Coal Ely_Wind : Electricity generated by technology i : Total Electricity Generation : Price of Electricity Generated by Technology i : Price of Electricity : CRESH Parameter for technology i Bottom-up Model VA Capital-Energy Composite L Intermediate ElectricityNon-Electricity Coal Non-Coal Gas Oil Petroleum Product CapitalEnergy 𝛾𝑖 𝛾𝑖 = 1 𝛾𝑖 = 0 Distribution & Sales Electricity 𝝈 = 𝟎
- 9. INTERNAL USE ONLYINTERNAL USE ONLY III. BOTTOM-UP MODEL: JAPAN MULTI-REGIONAL TRANSMISSION (JMRT) MODEL 8 Copyright 2014 FUJITSU RESEARCH INSTITUTE
- 10. INTERNAL USE ONLYINTERNAL USE ONLY Overview of JMRT 9 Copyright 2014 FUJITSU RESEARCH INSTITUTE Existing PowerStation ElectricityNew Technology USC Industry Domestic Transport IGCC GTCC Nuclear Manufacturing Non-manufacturing Household Office Small Hydro Wind PV Geothermal Existing Pumped-Storage USC: Ultra-super Critical IGCC: Integrated Gasification Combined Cycle GTCC: Gas Turbine Combined Cycle Biomass Oil Conventional Electric Car Fuel Cell Vehicle Hydrogen Fuel Cell
- 11. INTERNAL USE ONLYINTERNAL USE ONLY 10 Grids and Grid Connections Copyright 2014 FUJITSU RESEACH INSTITUTE10 0.6GW 6GW 0.9GW 0.3GW 5.57GW 1.4GW 16.66GW 5.57GW 5.57GW 2.4GW
- 12. INTERNAL USE ONLYINTERNAL USE ONLY 12 Time Slices 3 Time Periods Day（8～13、16～23） Peak（14～15） Night（0～7） 4 Seasons Spring（3～6） Summer（7～9） Autumn（10～12） Winter（1～2） 11 Copyright 2014 FUJITSU RESEARCH INSTITUTE Load Curve in Most Electricity Consumed day Million kW Peak Demand in each Year Million kW hr month
- 13. INTERNAL USE ONLYINTERNAL USE ONLY Existing PowerStation Data 12 Copyright 2014 FUJITSU RESEACH INSTITUTE Existing PowerStation Data include •Type of PowerStation •Latitude, Longitude •Prefecture •Start Year •Life Time •Electricity Generation Capacity •Availability Factor (AF)
- 14. INTERNAL USE ONLYINTERNAL USE ONLY Data of Renewable Potential 13 Copyright 2014 FUJITSU RESEARCH INSTITUTE No. Prefecture Code Lati- tude Long- itude Wind Speed 1 2 3 Geothermal Offshore Wind Onshore Wind GIS Data is from MOE Potential Survey Huge Renewable Potential in Hokkaido Area. Huge Electricity Consumption in Kanto Area including Tokyo. 1 km mesh
- 15. INTERNAL USE ONLYINTERNAL USE ONLY Geological Information (e.g. offshore wind) 14 Copyright 2014 FUJITSU RESEARCH INSTITUTE Wind Speed Availability Factor Wind Speed (m/s) AF (%) 5.5 15.8% 6 19.7% 6.5 23.5% 7 27.3% 7.5 31.0% 8 34.5% 8.5 37.9% Distance from road Sea Depth (Offshore) Distance from grid Initial Cost More than 20,000V http://www.gsi.go.jp/KIDS/ map-sign-tizukigou-h07- 02-01soudensen.htm
- 16. INTERNAL USE ONLYINTERNAL USE ONLY GIS to Calculate Dist. From Grid and Road 15 Copyright 2014 FUJITSU RESEARCH INSTITUTE Onshore Wind Offshore Wind Road Electricity Grid (>=20,000 volt)
- 17. INTERNAL USE ONLYINTERNAL USE ONLY CCS (Carbon Capture Storage) Potential 16 Copyright 2014 FUJITSU RESEARCH INSTITUTE Source: Calculation based on METI Potential (billion ton-CO2) *Japan CO2 emission was 1.16 billion ton-CO2 in 2010 **Total CCS Potential is 32.8 billion ton-CO2.
- 18. INTERNAL USE ONLYINTERNAL USE ONLY Design of Simulations 17 Copyright 2014 FUJITSU RESEARCH INSTITUTE Case Reference Grid Expansion Storage Carbon Abatement (%)* 0, 20, 29.375, 38.75, 48.125, 57.5, 66.825, 76.25, 85.625, 95 Grid Expansion No Yes No Electricity Storage No No Yes Grid Expansion Reduction below 2009 level by 2050 Storage
- 19. INTERNAL USE ONLYINTERNAL USE ONLY Parameter Estimation 18 Copyright 2014 FUJITSU RESEARCH INSTITUTE JMRT Model CRESH Production Function i CRESH Parameter
- 20. INTERNAL USE ONLYINTERNAL USE ONLY Onshore Wind There are huge onshore wind potentials in north part of Japan, Hokkaido, but electricity demands are done in Tokyo. There is very weak grid connection between Hokkaido and Japan main land and the capacity of grid connection is mere 60GW. Grid expansion make possible to access to Hokkaido on-shore wind potential. In addition, storage also plays a role to boost onshore wind. Onshore is intermittent generation technology and storage will charge excess generation from onshore wind and discharge when generated electricity is less than demand. 19 Copyright 2014 FUJITSU RESEARCH INSTITUTE Technology Onshore Condition Reference 1.65*** Storage 5.76*** GE 3.54 *** ***: 0.0001, **:0.001, *:0.01
- 21. INTERNAL USE ONLYINTERNAL USE ONLY Demand & RE Potential 20 Copyright 2014 FUJITSU RESEARCH INSTITUTE Twh High Demand Low RE Potential Low Demand High RE Potential Weak Connection 0.6GW
- 22. INTERNAL USE ONLYINTERNAL USE ONLY Solar 21 Copyright 2014 FUJITSU RESEARCH INSTITUTE Elasticity is the biggest in storage scenario and storage will work as back-up battery for solar to match between demand and supply. The potential of solar are geologically equally distributed in Japan and geological un-matching between potential and electricity demands are not big. Technology Solar Condition Reference 1.24*** Storage 3.59*** GE 1.23*** ***: 0.0001, **:0.001, *:0.01
- 23. INTERNAL USE ONLYINTERNAL USE ONLY Offshore Wind 22 Copyright 2014 FUJITSU RESEARCH INSTITUTE Same as onshore-wind, offshore-wind benefits from both storage and grid expansion. However, elasticity in storage scenario, 7.57, is more than that in grid expansion scenario, 3.95, because offshore wind potential is geologically equally distributed all over Japan. Technology Offshore Condition Reference 4.27*** Storage 7.57* GE 3.95*** ***: 0.0001, **:0.001, *:0.01
- 24. INTERNAL USE ONLYINTERNAL USE ONLY Elasticities under several systems 23 Copyright 2014 FUJITSU RESEARCH INSTITUTE Technology Hydro Solar Offshore Onshore Scenario Reference 1.36** 1.24*** 4.27*** 1.65*** Storage 2.22 3.59*** 7.57* 5.76*** GE 1.39** 1.23*** 3.95*** 3.54 *** ***: 0.0001, **:0.001, *:0.01
- 25. INTERNAL USE ONLYINTERNAL USE ONLY IV. TEST SIMULATIONS 24 Copyright 2014 FUJITSU RESEARCH INSTITUTE
- 26. INTERNAL USE ONLYINTERNAL USE ONLY Application to the case of JAPAN Japan’s fulfillment of Kyoto Obligation with no international emission trade and under various assumptions regarding the electricity sector: REF: Reference GE: Grid Expansion Case STO: Storage Case Copyright 2014 FUJITSU RESEACH INSTITUTE25
- 27. INTERNAL USE ONLYINTERNAL USE ONLY Renewable Energy Generation Changes Copyright 2014 FUJITSU RESEACH INSTITUTE26 (%) Note: Deviations from the baseline
- 28. INTERNAL USE ONLYINTERNAL USE ONLY Economic Impacts Copyright 2014 FUJITSU RESEACH INSTITUTE27 REF GE STO C -0.65 -0.63 -0.45 I 0.04 0.04 0.05 G 0.27 0.27 0.28 X -4.46 -4.41 -3.86 M -2.94 -2.89 -2.45 GDP -0.65 -0.64 -0.5 Carbon Abatement Cost (US$/t-CO2) GDP Decomposition
- 29. INTERNAL USE ONLYINTERNAL USE ONLY V. Lessons Conventional top-down model fails to represent substantially different technological futures. Common deficiency of tech-bundle CGE is the lack of the real estimates for the model parameters. Using parameter estimated by detailed bottom-up which is complex enough make top-down model reflect technology completeness. Reflect the characteristics of each technology Reflect system changes Copyright 2014 FUJITSU RESEACH INSTITUTE28
- 30. INTERNAL USE ONLYINTERNAL USE ONLY V. Lessons Copyright 2014 FUJITSU RESEARCH INSTITUTE Source: Hourcade, Jaccard, Bataille and Ghersi (2006) 29 TOP-DOWN Strength • Micro-economic Realisms • Macro-economic Completeness Weakness • Fails to represent substantially different technological futures BOTTOM-UP Strength • Technology Explicitness Weakness • Lack of micro-economic realisms • Lack of macro-economic completeness • Reflect geographical character
- 31. INTERNAL USE ONLYINTERNAL USE ONLY 30 Copyright 2011 FUJITSU RESEARCH INSTITUTE
- 32. INTERNAL USE ONLYINTERNAL USE ONLY Future Works Copyright 2014 FUJITSU RESEACH INSTITUTE31 TIMES MODEL JMRT (Japan Multi-regional Transmission) Model CGE MODEL Based on GTAP Model CGE MODEL with Tech Bundle Technology Information in Electricity Sector Parameter Demand Price
- 33. INTERNAL USE ONLYINTERNAL USE ONLY Hydrogen Cycle Copyright 2014 FUJITSU RESEARCH INSTITUTE H2 H2 Transport Buildings Hydrogen Station Hydrogen Electricity Heat Electricity
- 34. INTERNAL USE ONLYINTERNAL USE ONLY Technology Choices in Top-down Copyright 2014 FUJITSU RESEARCH INSTITUTE33 Capital Energy Source: Ban(2010)
- 35. INTERNAL USE ONLYINTERNAL USE ONLY Technology Choices in Bottom-up Copyright 2014 FUJITSU RESEARCH INSTITUTE34 Capital Energy Existing Technology Renewable Technology Source: Ban(2010)