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O gallachoir b_20150708_1500_upmc_jussieu_-_room_201

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O gallachoir b_20150708_1500_upmc_jussieu_-_room_201

  1. 1. Linking Energy system Models with Economic Models: Learning from the IEA ETSAP experience Brian Ó Gallachóir, James Glynn, Our Common Future under Climate Change UNESCO, Paris | 7th - 10th June 2015
  2. 2. IEA-ETSAP • … is a multilateral international agreement, promoted and sponsored by the International Energy Agency. • cooperation started after the first oil crisis, in order to understand alternatives to oil through systems analysis, • ETSAP has established, and now maintains / enhances the flexibility of consistent multi-country energy / engineering / economy / environment analytical tools and capability (the MARKAL-TIMES family of models), through a common research programme. • ETSAP members also assist and support government officials and decision-makers by applying these tools for energy technology assessment and analyses of other energy and environment related policy issues. In fact they implement several economic-equilibrium technology-explicit models of global, regional, national, and local systems.
  3. 3. IEA-ETSAP Collaborative Network Only those countries with at least one MARKAL/TIMES modelling team active during the period are “painted.”
  4. 4. IEA-ETSAP Co-Authors • Economic Impacts of Future Changes in the Energy System—Global Perspectives • Economic Impacts of Future Changes in the Energy System—National Perspectives • James Glynn, Patrícia Fortes, Anna Krook-Riekkola, Maryse Labriet, Marc Vielle, Socrates Kypreos, Antti Lehtilä, Peggy Mischke, Hancheng Dai, Maurizio Gargiulo, Per Ivar Helgesen, Tom Kober, Phil Summerton, Bruno Merven, Sandrine Selosse, Kenneth Karlsson, Neil Strachan and Brian Ó Gallachóir
  5. 5. Policy Experience in Hybrid Models UK – Markal Macro MACRO LABOUR GDP CONSUMPTION CAPITAL INVESTMENT USEFUL ENERGY SERVICES ENERGY PAYMENTS MARKAL ENERGY SOURCES TECHNOLOGY CHARACTERISTICS ENVIRONMENTAL CONSTRAINTS & POLICIES TECHNOLOGY MIX FUEL MIX EMISSIONS SOURCES & LEVELS FUEL & EMISSION MARGINAL COSTS RANKING OF MITIGATION OPTIONS
  6. 6. Impacts on GDP of 80% GHG reductions scenario Scenario % of GDP 2020 2030 2040 2050 Central scenario 0.46 1.70 2.43 2.81 With accelerated technological change 0.45 1.60 2.35 2.58 With higher fossil fuel prices 0.45 1.54 2.27 2.64 With accelerated energy efficiency -0.07 0.63 1.63 2.04
  7. 7. UK Experience in Hybrid Models 5 Critical Directions for Future 1. Multi-sectoral TIMES-Macro models • To facilitate a more nuanced investigation of energy quantity/price and technology/infrastructure selection on alternate parts of the economy 2. Detailed disaggregation of CGE models based on household income and characteristics • To allow analysis of the impact of energy and environment policies on households differentiated by income 3. A greater level of sectoral detail for energy intensive economic sectors 4. An extended treatment of natural capital stocks within CGE models • Via nested production functions which focus on the substitutability between these natural and conventional inputs to the economy 5. A renewed emphasis on model transparency and replication • This is a particular challenge given the complexity and computation sophistication of energy-economic hybrid models
  8. 8. HYBTEP - Portugal Soft Linked Hybrid  Detailed technological information of the BU TIMES_PT;  Explicit representation of economy and its factors (production, consumption, labour) from the Computable General Equilibrium model GEM-E3_PT. Assess the real impact of RES policies in the economy and the most cost- efficient technology portfolio to achieve it Technology explicitness TIMES_PT GEM-E3_PT Behavioural realism HYBTEP HYBTEP → soft-link between TIMES_PT and GEM-E3_PT
  9. 9. Coal Natural gas Oil Electricity σELFU = 0 Leontief Production Capital (K) Labour-Energy-Materials (LEM) Energy (ELFU) Labour (L) Materials (M) CES CES σKLEM σLEM Biomass Agriculture Land Transport Iron & Steel ... Other Market Services σM 9 GEM-E3_PT changes • Standard • HYBTEP Production Capital (K) Labour-Energy-Materials (LEM) Energy (ELFU) Labour (L) Materials (M) Fossil Fuels (FU) Natural gasOil Electricity (EL) Agriculture Land Transport Iron & Steel ... Other Market Services CES CES CES CES CES σKLEM σLEM σELFU σM σFU Coal i. Energy consumption and fuel mix defined exogenously; ii. New energy commodity: biomass; iii. Energy prices evolution defined exogenously;
  10. 10. 𝐷𝑗,𝑡 = 𝐷𝑗,𝑡−1 ∙ 1 + 𝐷𝑅𝐺𝑅𝑗,𝑡 × 𝐸𝐿𝐴𝑆𝐼𝑗 ∙ (1 − 𝐴𝐸𝐸𝐼𝑗) 10 HYBTEP FRAMEWORK GEM-E3_PT Demand Generator Step I ▪ Economic drivers (GDP, sector production, private consumption…) TIMES_PT Step II ▪ Energy services (materials, mobility) demand Energy Link ▪ Energy Consumption in physical units ▪ Energy prices ▪ Policy monetary values (CO2 price, energy subsidies, energy taxes…) Step III ▪ Energy Consumption in monetary units ▪ Energy prices evolution ▪ Technical Progress on Energy ▪ Policy monetary values (CO2 price, energy subsidies, energy taxes…) Step IV Each cycle represents 1 iteration Convergence criteria: Min energy services demand difference Common scenario assumptions - Fossil Fuel Import prices - Discount rate - Energy constraints - Policy assumptions
  11. 11. Res Heat Ind Heat Person Km Freight Km… Transformation Refinery, Power Plants, Gas Network, Briquetting... Primary energy prices, Resource availability Primary energy Final energy Service Demands GDP, Population, Industrial Activity TIAM-MSA Hard Linked Hybrid Domestic sources Imports Consumption Industry, Services, Transport, Residential... MACRO Stand Alone (MSA) General Equilibrium Macroeconomic Model Energy Costs Labour ConsumptionInvestmentCapital Demand Response CrudeOil RawGas Gasoline NaturalGas Electrcity 𝑀𝑎𝑥 𝑈 = 𝑛𝑤𝑡 𝑟 𝑟 𝑇 𝑡=1 . 𝑝𝑤𝑡𝑡. 𝑑𝑓𝑎𝑐𝑡 𝑟,𝑡. 𝑙𝑛 𝐶𝑟,𝑡      R r YEARSy yREFYR yr yrANNCOSTdNPVMin 1 , ),()1( Coal Heat Light Motion
  12. 12. • Global, technology rich, long-term energy system model • Economic optimisation: determination of cost optimal configuration of the system • 20 world regions with trade of energy, emission certificates and captured CO2 • All energy supply and demand sectors (from resource extraction to the final end use of energy) • Comprehensive energy technology portfolio, e.g. hydrogen and synfuel production, CCS in power, industry and upstream sector, renewables for heat and power • Emissions: CO2, CH4, N2O Soft Link TIAM-ECN & E3ME Separate regions: Mexico Colombia Venezuela Brazil Argentina Chile
  13. 13. Soft Link TIAM-ECN & E3ME
  14. 14. Benchmarking Scenarios for China Soft linking global BU and TD models
  15. 15. TIAM-World – GEMINI E3
  16. 16. Iron and Steel Consumption and Trade Flow 2050 Global 2DS
  17. 17. Conclusions from Experiences 1. Coupling adds value to individual model results i. Economic feedback for energy systems models ii. Improved technology system dynamics representation in CGE models 2. Different approaches for disaggregating CGE models 3. Challenging tasks – harmonisation, calibration, convergence, … 4. Black box versus transparency (…. lost in coupling)
  18. 18. Thank You www.ucc.ie/energypolicy

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