Transcript Asia/World Energy Outlook 2006 -Assumptions and Methodologies-

Modeling the Reference and Alternative
Scenarios
11-12 September 2007, Prince Hotel and Residence
Kuala Lumpur
E.Barcelona
The Institute of Energy Economics, Japan(IEEJ)
Projection Outline
Projection Period： 2005～2030
 Methodology： Final Energy Demand: estimated using econometrics
Electricity generation: based on generation mix submitted by
individual countries;
 Scenarios:
For countries with no projected mix: based on econometrics
and other relevant information
–Reference - Reference scenario anticipates probable assumptions based on
current political situations and the economic growth targets of each EAS countries
which yields future evolution of energy demand and supply
–Alternative Policy Scenario
This scenario develops future picture, in which Asian countries successfully
implement their energy saving goals and action plans.
For countries with no numerical targets, no APS is made hoping that new
information would be provided during this meeting.
In cases where both primary energy intensity targets and energy savings goals
are provided, the latter are used.
Model Structure
Economic Growth Targets
Industry
Transport
Other
For APS, Primary energy intensity
targets or detailed sectoral energy
saving goals, thermal efficiences and
use of biof-uels
Final Consumption
Power
generation
Oil
Refinery
Primary Energy
GDP, Crude oil price, Exchange rate,
Population, Power generation outlook,
thermal efficiencies, etc.
Coal
Products
Incorporating energy conservations
assumptions
Energy Policy etc
Efficiency
Industrial Sector
Main Production
of Industry(Steel,
Cement etc)
By Energy
Coal
Transformation
By Industry
Efficiency
Fuel Prices
GDP
Population
Consumer Spending
Household
Residential
Sector
Oil Refinery
Efficiency
By Energy
Final
Consumption
Commercial
Sector
By Energy
Transformation
(Fuel Input)
Gas Processing
Efficiency
Power
Generation(kWh)
Car Hold
Transport Sector
By Energy
Other Activity
By Mode
Primary Energy
Nuclear
Nuclear 33%
Hydro 100%
Geothermal 10%
Hydro
Geothermal etc
Thermal Efficiency
Fossil fuel Power
Incorporating energy
conservations assumptions
【Final Consumption Sector】
Energy=f(GDP, Trend, Price)・・・・BAU
Energy= f(GDP, Trend, Price)*(1-s）・・・・APS
s: energy saving target ratio
【Transformation Sector】
Gross Electricity Generation = FEC + Loss & Own Use
GEG by fossil fuel = GEG * Share of fossil fuel
Fossil fuel input=GEG by fossil fuel/Efficiency・・・BAU
Fossil fuel input= GEG by fossil fuel/(Efficiency*(1+e))・・・APS
e: thermal efficiency improvement ratio
Application of the
Assumptions

Result are calculated using the submitted
assumptions


Missing assumptions are supplemented by the IEEJ.
Exceptions


Results for Australia are from ABARE’s outlook
(2006).
Results for Japan are based on IEEJ’s outlook (2006),
not by the government for the time being.
Economic and Energy Data

Energy Data: “Energy Balances” of the
IEA



“Combustible Renewables and Waste” of the
Non-OECD countries are not included
“Feedstock Use in Petrochemical Industry” is
included in industry sector, not non-energy
use sector.
Economic Data: “World Development
Indicators” by the World Bank, etc.
Model

IEEJ Model


Not Modeled


Applied to 12 countries: Econometric type
models built by the IEEJ except for Australia,
Cambodia, Lao PDR and Myanmar
Australia: IEEJ used ABARE projections
LEAP Model:


Applied to Cambodia, Lao PDR and Myanmar
Regression software used to forecast final
energy consumption
Definition of BAU and APS

BAU:




Natural trend: no assumption of additional efficiency
improvement
The future intensity data submitted by the countries are
not applied.
Future intensities are derived from model results.
APS: Depends on the submitted assumptions

If both BAU and APS intensities are submitted, the relative
improvement from BAU to APS is applied


e.g. Korea submission: BAU 237 toe/million USD; APS 200
toe/million USD (16% decrease)
IEEJ result: BAU 222 toe/million USD; APS 187
toe/million USD (16% decrease)
TPES/GDP Intensity in 2030
2030
AUS
BRN
KHM
CHN
IND
IDN
JPN
KOR
LAO
MYS
MMR
NZL
PHL (2014)
SGP
THA (2020)
VNM
BAU
182
#N/A
#N/A
#N/A
446
549
74
237
#N/A
#N/A
#N/A
#N/A
320
#N/A
507
#N/A
Submitted
APS
APS/BAU
170
-7%
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
327
-27%
381
-31%
68
-8%
200
-16%
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
#N/A
461
-9%
#N/A
#N/A
(toe/Million USD in 2000 Price)
Result
BAU
APS
APS/BAU
182
170
-7%
354
354
0%
162
162
0%
359
263
-27%
362
265
-27%
471
327
-31%
74
68
-8%
222
187
-16%
320
320
0%
393
393
0%
594
594
0%
209
185
-12%
248
199
-20%
167
167
0%
411
357
-13%
487
440
-10%
Modeling CLM

Final Energy Consumption




Supply of Petroleum Products



Cambodia – trend extrapolation
Lao PDR and Myanmar – regression analysis
Major Variables: GDP, sectoral GDP, population and urbanization
Cambodia and Lao PDR: continue to import oil products
Myanmar: Refining capacity to increase in proportion to demand
Power Generation


Cambodia and Lao PDR – future power plants will be coal and
hydro
Myanmar – exogenous hydro and the balance will be supplied by
coal
Modeling CLM

LEAP Model

Accounting model –






With given demand equations and exogenous variables,
demand is estimated by the model
Sectoral energy saving goals entered as multipliers
Information on transformation processes are supplied which
include configuration of electricity generation system and oil
refining plants
Energy reserves are also supplied to the model if available
Produces energy balances as primary output
Other results such as electricity generation input and output,
CO2 emissions, etc could also be extracted
Summary of Results
Energy Intensity vs GDP per Capita
1,000
900
AUS
800
BRN
KHM
700
CHN
toe/million USD
IND
600
IDN
JPN
500
KOR
LAO
400
MYS
MMR
300
NZL
PHL
200
SGP
THA
100
VNM
0
0
10
20
30
40
GDP/capita ('000 USD)
50
60
70
Energy Intensity vs. GDP per Capita
Lower Income Countries
1,000
900
800
KHM
700
toe/million USD
CHN
600
IND
IDN
500
LAO
MYS
400
MMR
PHL
300
THA
200
VNM
100
0
0
1
2
3
4
5
6
7
8
9
10
GDP/capita ('000 USD)
Thank you for your attention