Govinda R. Timilsina The World Bank, Washington, DC

Skopje, Macedonia

March 1, 2011

Sectoral Models for Energy and Climate Policies

Presentation Outline

► Introduction

► Typology of models

► Energy Demand Models

► Energy supply models

► Energy system models

Introduction

Energy modelling has a long history (Since the early 1970s, a wide variety of models became available for analysing

energy systems or sub-systems, such as the power system)

Energy modelling has multiple purposes (Better understanding of current and future markets – supply, demand, prices;

facilitating a better design of energy supply systems in short, medium and long term; ensuring sustainable exploitation of scarce energy resources; understanding of the present and future interactions energy and the rest of the economy; understanding of the potential implications to environmental quality)

Based on different theoretical foundations (Engineering, economics, operations research, and management science)

Apply different techniques (Linear programming, econometrics, scenario analysis)

Classifying Energy Models

Energy Model

Model for energy market forecast

Energy demand model

End-use accounting model

Econometric model

Energy supply model

Optimization model

Simulation model

Energy system model

Model for energy – economic interaction

Input-Output model

General equilibrium model

Methodologies

for Energy Demand

Forecasting

Methodologies for Energy Demand Forecasting

End-use Approach

Bottom-up or engineering approach

Use physical or engineering

relationship between energy and

energy utilizing devices and

processes (e.g., capacity, efficiency,

utilization rate)

Follows growth of driving variables

(i.e., devices and processes), which

are derived often scenario analysis

or economic models

Could produce more disaggregated

(i.e., end-use and sector) and the

forecasts are relatively precise

Complex and data consuming;

more appropriate for long-term

Econometric Approach

Econometric approach

Use historically established

relationships between energy

demand and economic variables

(e.g., GDP, population, household

income)

Follows growth of driving variables

(i.e., economic variables)

Estimation are made at more

aggregated level or at sectoral level

but not at end-use level

Simple but relatively less accurate;

more appropriate for short-term

Methodologies for Energy Demand Forecasting

End-use Approach

Normally do not account pricing

effect on demand, which is very

critical when demand for a fuel is

highly elastic

Econometric Approach

This approach normally considers

single fuel or aggregate energy

(gasoline, electricity) and does not

account substitution possibilities

between fuels

Use of flexible functional forms (e.g.,

translog, normalized quadratic ) is

growing

They are unable to account

technology specific features which

are key determinants of fuel

consumption

Comparison of some energy demand

forecasting models

Criteria DTI NEMS MAED/ MEDEE

LEAP POLES

Type Top-Down Hybrid Bottom-up Bottom-up Hybrid

Approach Econometric Accounting

Geography National Flexible Global

Level of disaggregation

Domestic, transport, service, industry Agriculture is also included

Technology coverage

Renewable and conventional

Both conventional and renewable

Data need Time series and survey

Energy Supply

Models

Energy Supply Models

These models either stand alone (e.g., MARKAL,

WASP) or serve as a module of a energy system model

(e.g., electricity market module, coal market module in

US NEMS model)

Demand forecasts, energy resources and technologies

characteristics, costs are the key driving variables

Can accommodate any policy instruments or constraints

such as emission constraints

Methodologies for Energy Supply Planning

Optimization

Ensure cost minimization meeting

all constraints such as resource

availability, system reliability,

environmental quality (if desired)

More appropriate when a large

number of supply alternatives are

available

Example: MARKAL, EFOM, WASP

Simulation

Simulates behavior of energy

consumers and producers under

various signals (e.g. price, income

levels)

Forecasts can be sensitive to

starting conditions and behavioral

parameters

Example: ENPEP/BALANCE,

Energy 20/20

Energy Supply Model: MARKAL

MARKAL is a “bottom-up” model with detailed representation of

energy resources and production technologies

It follows the principal of reference energy system and finds a

least cost set of technologies to satisfy end-use energy service

demands and user-specified constraints

MARKAL is found extensively used for both academic and

consulting studies

The MARKAL Energy PerspectiveThe MARKAL Energy Perspective

Industry, e.g.

-Process steam

-Motive power

Services, e.g.

-Cooling

-Lighting

Households, e.g.

-Space heat

-Refrigeration

Agriculture, e.g.

-Water supply

Transport, e.g.

-Person-km

Demand for

Energy Service

Industry, e.g.

-Steam boilers

-Machinery

Services, e.g.

-Air conditioners

-Light bulbs

Households, e.g.

-Space heaters

-Refrigerators

Agriculture, e.g.

-Irrigation pumps

Transport, e.g.

-Gasoline Car

-Fuel Cell Bus

End-Use

Technologies

Conversion

Technologies

Primary Energy

Supply

Fuel processing

Plants e.g.

-Oil refineries

-Hydrogen prod.

-Ethanol prod.

Power plants e.g.

-Conventional

Fossil Fueled

-Solar

-Wind

-Nuclear

-CCGT

-Fuel Cells

-Combined Heat

and Power

Renewables e.g.

-Biomass

-Hydro

Mining e.g.

-Crude oil

-Natural gas

-Coal

Imports e.g.

-crude oil

-oil products

Exports e.g.

-oil products

-coal

Stock changes

(Final Energy) (Useful Energy)

MARKAL: MARKet

ALlocation)

Developed under the

Energy Technology

Systems Analysis

Program of IEA

Linear programming

type optimization ;

based on Reference

Energy System

Detailed modeling of

energy resources and

supply chains

Includes electricity

generation and

transmission planning

Energy Supply Model: MARKAL

Energy Supply Model: MARKAL

Total OECD Countries = 21

Total Developing Countries = 23

Total Other Countries = 13

Electricity Supply Model: WASP

WASP stands for Wien Automatic System Planning

It was originally developed by the Tennessee Valley Authority

and Oak Ridge National Laboratory of the US for International

Association of Atomic Energy

It is the most well-known and widely used optimization model

for examining medium- to long-term expansion options for

electrical generating systems

The software is distributed for use by electric utilities and

regulation agencies in over 90 countries, as well as to 12

international organizations including The World Bank

Electricity Supply Model: WASP

Countries Using WASP

Energy System Models

Energy System Modeling

Energy system models combine both demand and supply, they can be

also used for:

Energy market projections

Energy policy analysis

Projections of environmental pollution (e.g., GHG, SOx, NOx)

from the energy system and policies for their mitigation

They can employ different methodologies for the demand and supply

blocks (e.g., end-use or econometric for demand and optimization or

simulation for supply)

ENPEP – Optimization for supply; econometric for demand

LEAP uses end-use accounting approach for demand and

simulation approach for supply

NEMS uses optimization modules for the electricity sector and

simulation approaches for each demand sector

Name Developer

NEMS US DOE

ENPEP Argonne National Laboratory

LEAP Stockholm Environmental Institute

TIMES Energy Technology Systems Analysis

Program (ETSAP) of the International Energy

Agency (IEA),

MESSAGE International Institute for Applied Systems

Analysis, Austria

POLES LEPII (formerly IEPE - Institute of Energy

Policy and Economics), Grenoble, France

ENERGY 2020 Systematic Inc. (a US private company)

Energy System Models - Examples

MAED

LOAD

WASP IV

BALANCE

WASP IV

MACRO-E

Capacity

Expansion Plan

Load Dispatching

Electricity

Generation

Fuel

Consumption

Emissions

Emissions

Energy Demand

(excluding

electricity)

- Detailed evaluation of

energy demands by

sector, sub-sector, fuels

and useful energy

- Representation of

resource availability and

costs

-Detailed evaluation of

the power system

configurations

Energy System Model - ENPEP

Energy System Model - ENPEP

Global Use of ENPEP

Energy System Model – US NEMS

The National Energy Modeling System (NEMS) is the tool the Energy

Information Administration (EIA) of the United States has been using since

1994 to project US energy market and to analyze various energy-economic,

environmental and energy security policies

NEMS projects the production, imports, conversion, consumption, and prices

of energy, subject to assumptions on macroeconomic and financial factors,

world energy markets, resource availability and costs, behavioral and

technological choice criteria, cost and performance characteristics of energy

technologies, and demographics

Based on NEMS results the EIA publishes its Annual Energy Outlook every

year; it has also been used for a number of special analyses at the request of

the Administration, U.S. Congress, other offices of DOE and other government

agencies: Energy Market and Economic Impacts of H.R. 2454, the American Clean Energy

and Security Act of 2009, requested by Chairman Henry Waxman and Chairman

Edward Markey

Impacts of a 25-Percent Renewable Electricity Standard as Proposed in the

American Clean Energy and Security Act, requested by Senator Markey

Source: EIA, USDOE (http://www.eia.doe.gov/oiaf/aeo/overview/figure_2.html)

Energy System Model – US NEMS

(Model Structure)

Long Range Energy Alternatives Planning System

Developed by Stockholm Environmental Institute

Scenario-based energy accounting model

It accommodates a Technology and Environmental Database

Energy demands by sectors, sub-sectors end-uses and equipment

Energy transformation sectors included (e.g., electricity, refinery, charcoal)

Energy System Model – LEAP

Energy System Model – LEAP

(Overall Model Structure)

D e m o g r a p h i c sM a c r o -

E c o n o m i c s

D e m a n d

A n a l y s i s

T r a n s f o r m a t i o n

A n a l y s i s

S t a t i s t i c a l

D i f f e r e n c e s

S t o c k

C h a n g e s

R e s o u r c e

A n a l y s i s

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N o n - E n e r g y S e c t o r

E m i s s i o n s A n a l y s i s

E n v i r o n m e n t a l

E x t e r n a l i t i e s

Energy System Model – LEAP

(Global Application)

MESSAGE stands for Model for Energy Supply Strategy Alternatives and their General Environmental Impact; it is the International Institute for Applied Systems Analysis, Austria

It is a systems engineering optimization model used for medium- to long-term energy system planning, energy policy analysis, and scenario development

It is a scenario-based energy system model; scenarios are developed through minimizing the total systems costs under the constraints imposed on the energy system; this information and other scenario features such as the demand for energy services, the model configures the evolution of the energy system from the base year to the end of the time horizon

Energy System Model – MESSAGE

Energy System Model – MESSAGE

(Overall Model Structure)

Comparison of Selected Energy System Models

Criteria RESGEN EFOM MARKAL TIMES MESAP LEAP

Approach Optimisation Accounting

Geographica

l coverage

Country Local -

national

Country - multi-

country

National Local -

global

Activity

coverage

Energy Energy &

trading

Energy

Sector Pre-defined User defined Pre-defined

Technology Good Extensive

Data need Variable Extensive Variable

Skill

requirement

Limited High Limited

Documentati

on

Limited Good Extensive Good Extensive

Thank You

Govinda R. Timilsina

Sr. Research Economist

Environment & Energy Unit

Development Research Group

The World Bank

1818 H Street, NW

Washington, DC 20433, USA

Tel: 1 202 473 2767

Fax: 1 202 522 1151

E-mail: gtimilsina@worldbank.org