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Model Comparison: Top-Down vs. Bottom-Up Models P.R. Shukla.

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Presentation on theme: "Model Comparison: Top-Down vs. Bottom-Up Models P.R. Shukla."— Presentation transcript:

1 Model Comparison: Top-Down vs. Bottom-Up Models P.R. Shukla

2 Classification of Energy Sector Models Energy Models Top-Down Bottom-Up Macro- Optimisation & Simulation Technology Assessment Equilibrium Single-Country Multi-Region

3 Electricity Generation Coal Gas Crude Oil Renewable Nuclear Oil Refinery Lighting Cooking Transport Irrigation Water Supply Heating Drive Light Bulb Heater Motor Pump Stove Car ResourceSecondary Energy Technology End-Use Reference Energy System

4 Representative Bottom-up Model Flow Chart (MARKAL)

5 Representative Top-down Model Flow Chart (SGM 2000)

6 Comparative Dimensions ParadigmSpaceSectorTime Top-Down (Integrated assessment) Global and Atmospheric MacroeconomyLong Term Top-Down (Economic equilibrium) Global, National, Regional MacroeconomyLong Term Bottom-Up (Optimization) National, Regional EnergyLong Term/Medi um Term Bottom-Up (Optimization / Accounting) National, Regional, Local Sub-SectorMedium Term/Short Term

7 Model Examples ParadigmExamplesIssues Addressed Top-Down Integrated Assessment ModelImpact of market measures (like carbon tax) on atmospheric chemistry and cost to economies Top-Down Economic Equilibrium models (SGM, CRTM, CETA) Impact of market measures on global emissions and cost to economies Bottom-Up Optimization MARKAL, EFOM, BEEAMImpact of market measures and other energy policies (like subsidies, technology regulations) on technology mix, fuel mix, emissions and cost to energy system. Bottom-Up Optimization/A ccounting End-use sector models (e.g. AIM/ END USE), Power sector, Coal sector models Impact of subsectoral policies on subsectoral technology mix and emissions; Planning for generation mix; Power plant scheduling; Logistics

8 Relative Strengths Top-downBottom-up Market equilibrium approachOptimization approach Higher sectoral aggregationBetter engineering / technology description Energy flows and demands in monetary units Energy flows and demands in material units Endogenous representation of most macroeconomic parameters like prices and demand elasticities Better for policy analysis involving impact assessment of technology and fuel mix within a sector

9 Soft Linked Integrated Modeling Framework TOP DOWN MODELS Productivity SGMERB Model Global Energy Prices GDP Prices Energy Balance BOTTOM-UP MODELS MARKALStochastic MARKAL Scenarios Demand Projection AIM/ENDUSE End-use Demand Power Sector LP Model End-use Demand Technology Share Technology Details OTHER MODELS Emissions Technology Specifications Health Costs Inventory Estimation Model GIS based Energy & Emissions Model Health Impact Model

10 ObjectiveOutputPolicy Analysis End-Use Demand Projection Demand Projections consistent with macroeconomic scenario End-use Sector Demand Trajectory Sectoral investment, technology and infrastructure policies AIM/ENDUSE Minimize discounted sectoral cost Sectoral energy, and technology mix, investments and emissions Sectoral technology, energy, investment and emissions control policies MARKAL Minimize discounted Energy system cost National energy and technology mix, energy system investments, and emissions Energy sector policies like energy taxes and subsidies; energy efficiency; emissions taxes and targets Stochastic- MARKAL Minimize expected value of discounted system cost Energy and technology mix under uncertain future, Value of information Hedging strategies for energy system investments; identify information needs Model Characteristics: Bottom-Up Models

11 Model ObjectiveOutputPolicy Analysis SGM Determine market clearing prices for economic sector outputs GDP and consumption trajectories;, prices of sectoral outputs and energy; sectoral investment patterns Macro-economic impacts of policy interventions such as energy tax / subsidies; emissions limitations ERB Determine Global / Regional Energy Prices and Energy Use Long-term global and regional energy prices, energy mix and emissions Implications of very long-term global energy resource, tech. expectations Model Characteristics: Top-Down Models

12 Model ObjectiveOutputPolicy Analysis Inventory Estimation Model Estimate national emission inventory for various gases National emission inventory Regional and sectoral emission variability, bench-marking, emission hot-spot assessment GIS Based Energy and Emission Model Determine regional spread of energy and emissions Regional mapsLinking energy and environment policies across time and space Power Sector LP Model Minimize discounted Power sector cost Power plant capacity and generation mix, emissions profile, total costs Power sector technology, energy, investment, emissions control policies Health Impact Model Estimate local pollutant emission impacts on human health Impact of individual plants, per capita and total national human health impacts, sensitivity analysis Plant location and stack height policies, emission norm analysis, enforcement policy assessment Model Characteristics: Other Models

13 Some Top-down Model Results

14 GDP loss over base case: Carbon Tax scenarios Tax Scenarios $100/ tC 50/ tC 25/ tC

15 Energy Consumption: Carbon Tax cases Tax Scenarios

16 Some Bottom-Up Model Results

17 Technology Mix in Brick Production Year High Draught VSBK Clamps (Biomass) Bull trend Kiln 2 Bull trend Kiln 1 Billion Nos.

18 From Industry & Residential Grow 3.5 times Commercial Grows 9 times Agriculture Stagnates Transport Grows 5 times Sectoral Energy consumption (EJ)

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