18th AIM International Workshop(December 15th, 2012)

Multi-Regional Enduse modelin JapanKen Oshiro / Go Hibino
Mizuho Information & Research Institute Inc.
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Why is the Multi-regional model required ?
• Climate condition, renewable energy potential, electricity
grid condition and other factors are different among regionsin Japan, and they affect energy consumption strongly.
• Similar studies have already done, however they wereoften based on few data.
• New statistics are published in recent years, especially inresidential, commercial and power sector.
• This study is intended to revise the model data based on
new statistics, and modify the model.

2

Regional climate condition in Japan• Energy demand varies according to regional climatecondition greatly.
<Household energy consumption (2009)>
Hokkaido

TohokuKansaiTokyo

KyusyuSource: Agency for Natural Resources and Energy

3Electricity grid in Japan• Separated into 10 areas by 10 major utility companies andelectricity interchange capacity is limited very little.
• Multi-regional model is required to analyze supply-demandbalance in detail.

Hokkaido
Okinawa
TohokuHokuriku
Chugoku

TokyoChubuKyusyu

ShikokuKansai

Source: METI

4

Abatement cost (USD/t-CO2)

Technology preference in Multi-regional model•

Technology D is not recruited by one-country model (green) undercarbon constraint of X1.

•

By multi-regional model, technology D is more preferred than C inregion 1.
X1

Tech. D(One country)

Tech. D
Tech. D
Tech. C(Region 2)(Region 1)

Tech. B

Tech. A

Tech. D(Region 3)

Morepreferred

CO2 emission
reduction
One country modelMulti-regional model5

Framework of the model (Tentative)• Residential and power generation:
 Divided into 10 regions consistent with electricity grid areas.
• Industry, commercial, transportation and other energy conversion:
 Not yet divided, still one-country model.
• Other sectors (non-energy, etc.) are not yet included.

Multiregion(10 area)

Residential(separated intoMulti-region)<Energy conversion>
Powergeneration(separated intoMulti-region)

One
countryIndustry
CommercialTransportation

Other energy
conversion

Simply allocated to each region
based on the current statistics

CO2<Enduse model>

Primary energy<Image of model structure>

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Power generation module• Divided into 10 areas.
• Time resolution:
 3 seasons (summer, winter, intermediate) 5 weekdays and 2 holidays in a week 24 hours in a day• Electricity demand curve is based on current status
 Shape is assumed to be constant into the future, but height ofcurve is determined by yearly total electricity demand.
<Example of model output (Weekday of summer, 2020)>

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Relation between Enduse and Power generation• The models are separated at present.
• Parameters such as electricity demand, emission intensity andelectricity consumer price, are shared between them as follows.

<Year>
2010<Enduse>CO2(base year)

Minimizing
total cost

Emission intensity
Electricity pricein base year(given parameter)<Power gen.>

Minimizing
generation costof electricity

Electricity
demandCO22011

Minimizing
total cost

CO2$

CO2 Emission intensity
Electricity priceMinimizing
generation costof electricity
CO22030

Minimizing
total cost

CO2$8

Technology•

Following technologies have regional own parameter Residential insulation:
Efficiency differs by climate condition.
 Residential heat pump:
Efficiency is lower in cold climate region.
 Renewable energy:
Availability differs by regions.

•CCS is not yet included.

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Key assumptions• Exogenous parameter Renewable energy supply: complied with national policy (higher case) Nuclear power plant operation: operating no more than 40 years.
 Fuel cost Activity level and service demand• Carbon price variation
1. Baseline case: no price
2. 100USD case: 1000USD/t-CO2• Time horizon: 2010-2030• Model modification and data collection is ongoing.
 The models and these results are tentative, so some unreasonable
result will be modified in the near future.

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Results: Preferred technology difference by regions• Residential insulation technology is preferred more inHokkaido region.
<Hokkaido (cold climate)><Okinawa (hot climate)>

Moreefficient*Baseline case11

Results: Constraint of renewable energy availability•

Renewable electricity is not fully used in Hokkaido area.

•

Reinforcing interchange capacity and storage system would be effective.
<Electricity output in Hokkaido area>(100USD case)<Wind power potential in Japan>

Hokkaido area
Large wind power
potential

Other Ren.

NarrowinterchangecapacityWindLargedemandWasted*The power generation module cannot analyze high frequency control
at present.

Source: METI

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Results: Power generation••

In baseline case, share of coal increases in place ofnuclear power phase out.
In 100USD case, share of gas increases and electricity
demand also slightly increases in 2030.
<Baseline><100USD>13

Results: CO2 emission• About 30% reduction in 2030 compared to 1990.
<CO2 emission (100 USD case)>*Energy related CO2 only.

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Summary• Findings from tentative analysis
 Preferred technology is different by regional condition inresidential sector, such as insulation.

• The future work planning Modifying the models and collecting data in all sectors,
as well as residential and power sector.
 Combining Enduse model and power generation module.

15Thank you for your attention

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