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An Introduction of the BET model -An Integrated Assessment Model Including End-Use Technologies

An Introduction of the BET model -An Integrated Assessment Model Including End-Use Technologies. Hiromi Yamamoto Masahiro Sugiyama Junichi Tsutsui Central Research Institute of Electric Power Industry (CRIEPI), Tokyo 2013/07/30 32 nd USAEE / IAEE North American Conference, Anchorage.

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An Introduction of the BET model -An Integrated Assessment Model Including End-Use Technologies

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  1. An Introduction of the BET model-An Integrated Assessment Model Including End-Use Technologies Hiromi Yamamoto Masahiro Sugiyama Junichi Tsutsui Central Research Institute of Electric Power Industry (CRIEPI), Tokyo 2013/07/3032ndUSAEE/IAEE North American Conference, Anchorage

  2. Background • An IAM(integrated assessment model) , which evaluates interactions between energy, the economy, and the environment, is a tool to guide policy discussions for long-term, global sustainable development (Weyant1999). • Recently, advanced end-use technologies have received increasing attention as a key component of options for climate change mitigation (Kyle et al. 2011). Advanced electric technologies include heat-pump water heaters and EVs. • A combination of low-carbon power generation (such as renewables, thermal power with CCS, and nuclear) and advanced electric end-use technologies are a promising solution for drastic GHG(greenhouse gas) reduction.

  3. Objectives • To develop an IAM (integrated assessment model) based on a general equilibrium technique (Ramsey’s optimal growth theory) and including advanced end-use technologies such as heat pump water-heater and electric vehicles. • Using the model, to analyze the effects of the advanced end use technologies. • We conduct on-off analyses of the advanced end-use technologies and evaluate the importance of the advanced end use technologies.

  4. BET model • Basic-Energy-Economy-Environment-and-Enduse Technology Model (BET). • A MERGE-RICE type global model hard-linked with enduse technologies like MARKAL-MACRO. • The economic module is an one-sector CES(constant elasticity substitution) type production function. • The energy module is a bottom-up type model that describes vintage of energy facilities and electric load curves. • The primary energy includes coal, oil, natural gas, biomass, nuclear, hydro, wind, photovoltaic, and backstop. • World 13 regions; Simulation period: 2010 to 2230 with 10 year-intervals; an NLP model.

  5. Figure The model structure

  6. Table Energy Services In the model

  7. Regions and Energy systems

  8. Formulation of production function: Patty -Clay type -function. YN: (patty) production; Yt = (1-ζ) Yt-1 + YNt; ζ is a deplation rate. KN: (patty) capital, ln: (patty) labor. DN: Energyservices; DN = f(E). Income identity: EC is the sum of energy systems cost including enduse technologies. Objective function: θ: Negishi weight, df: discount rate..

  9. population Basic performance of BET. GDP TPES

  10. GDP losses(Base case =0%) GHG accumulation targets Off: Advanced End use Techs Are Off; On: Advanced End use Techs Are On.

  11. FigPower generation,upper: 2050lower:2100

  12. FigEnergy services,upper: 2050lower:2100

  13. FigEnergy services in vehicle services,upper: 450-off Lower: 450-on

  14. Conclusions • Using the BET model, we have conducted simulations and obtained the following results. • (1) Turning off the advanced end-use technologies results in GDP losses. Such losses become larger with a more stringent climate policy. The advanced end-use technologies are a way to contain GDP loss when the climate target is stringent. • (2) Electricity demand is relatively stable, but non-electricity demand decreases as the GHG constraints become more stringent. This is because electricity can be supplied using various low-carbon options such as renewables, nuclear , and thermalpower with CCS. • (3) Electrification rates based on energy services are high under stringent GHG constraints. The combination of electrification and advanced electric end-use technologies is a powerful method to achieve strict GHG constraints.

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