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