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Model Comparison: Top-Down vs. Bottom-Up Models

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Presentation on theme: "Model Comparison: Top-Down vs. Bottom-Up Models"— 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 Reference Energy System
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 Resource Secondary Energy Technology End-Use

4 Representative Bottom-up Model Flow Chart (MARKAL)

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

6 Comparative Dimensions
Paradigm Space Sector Time Top-Down (Integrated assessment) Global and Atmospheric Macroeconomy Long Term (Economic equilibrium) Global, National, Regional Bottom-Up (Optimization) National, Regional Energy Long Term/Medium Term (Optimization / Accounting) National, Regional, Local Sub-Sector Medium Term/Short Term

7 Model Examples Paradigm Examples Issues Addressed Top-Down
Integrated Assessment Model Impact of market measures (like carbon tax) on atmospheric chemistry and cost to economies Economic Equilibrium models (SGM, CRTM, CETA) Impact of market measures on global emissions and cost to economies Bottom-Up Optimization MARKAL, EFOM, BEEAM Impact 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/Accounting 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-down Bottom-up Market equilibrium approach
Optimization approach Higher sectoral aggregation Better 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 SGM ERB Model Global Energy Prices GDP Prices Energy Balance BOTTOM-UP MODELS Scenarios MARKAL Stochastic MARKAL Technology Details Power Sector LP Model End-use Demand Technology Share End-use Demand Demand Projection AIM/ENDUSE Technology Specifications Health Costs OTHER MODELS Inventory Estimation Model Emissions GIS based Energy & Health Impact Emissions Model Model

10 Model Characteristics: Bottom-Up Models
Objective Output Policy 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

11 Model Characteristics: Top-Down Models
Objective Output Policy 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

12 Model Characteristics: Other Models
Objective Output Policy 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 maps Linking 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

13 Some Top-down Model Results

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

15 Energy Consumption: Carbon Tax cases
Tax Scenarios

16 Some Bottom-Up Model Results

17 Technology Mix in Brick Production
140 High Draught VSBK 120 Clamps (Biomass) 100 Bull trend Kiln 2 Bull trend Kiln 1 Billion Nos. 80 60 40 20 1995 2000 2005 2010 2015 2020 2025 2030 2035 Year

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

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