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Emissions reduction potential assessment in regions of Kazakhstan
using TIMES-16RKZ model
B. Suleimenov, R. De Miglio, A. Kerimray
National Laboratory Astana
Nazarbayev University
IEA-ETSAP Workshop
18th-19th November 2016
CIEMAT, Madrid, Spain
Content
• Introduction
• TIMES-16RKZ model
• Scenarios
• Results
• Conclusions
Sankey diagram of energy balance in Kazakhstan 2014, Mtoe
53% of production is exported
Ratio between final energy consumption and domestic energy supply = 56%
High losses and energy industry own use
Regions of Kazakhstan16 administrative regions:
• GDP and its structure differs from region to region
• Different fuel energy mix by regions due to existing energy infrastructure (Soviet Heritage)
• Different climate conditions
• GRP per capita varies from the lowest 2.2k USD2005 to the highest 18.2k USD2005
• 11 times difference in regional energy intensity from the lowest to the highest
Regions of Kazakhstan
Regions of extractions of sub-bituminous coal (values in TJ, extraction in 2011)
Regions of Kazakhstan
Regions of extractions of crude oil (values in TJ, extraction in 2011)
Regions of Kazakhstan
Regions of extractions of associated gas (values in TJ, extraction in 2011)
Regions of Kazakhstan
Installed power capacity by region (values in MW in 2011)
TPES by region
0 2000 4000 6000 8000 10000 12000 14000 16000 18000 20000
AKM
AKT
ALM
ATY
WKZ
ZHA
KAR
KST
KZL
MAN
SKZ
PAV
NKZ
EKZ
AST
ALC
Total primary energy supply by fuel type in 2014, (ktoe)
Coal Crude Oil Gas Biofuels and waste
• 16 regional energy balances were collected and reclassified
Generating capacities, oil refinery, heavy industry
CHP plants, Heavy industry
Oil Refinery, oil and gas extraction
So why regional model?
• Resource availability
• Different growth rates by regions
• Economic structure
• Climate differences
• Region oriented climate and energy policies test
TIMES-16RKZFo
ssil
fuel
s m
inin
g (O
il an
d g
as, c
oal
)
Transformation sectors
Power sector (electricity and
heat)
Refinery
Gas processing
Coal transformation
Demand sectors
Residential sector(Heating, cooling, lightning, washing,
refrigerators and etc.)
Commercial sector(Heating, cooling, lightning, washing,
refrigerators and etc.)
Industry(Iron and steel, aluminum, non-ferrous
metals, cement, chemicals, mining, construction and etc.)
Transport(Cars, light and heavy trucks, busses and etc.)
Agriculture
direct consumption
Electricity and heat
Oil products
LPG and stripped gas
Coke oven coke, blast furnace gas and etc.
Drivers
0.000
1.000
2.000
3.000
4.000
5.000
6.000
7.000
8.000
9.000
2011 2020 2030 2040 2050
GRP growth rate (2011=1)AKM
AKT
ALM
ATY
WKZ
ZHA
KAR
KST
KZL
MAN
SKZ
PAV
NKZ
EKZ
AST
ALC
0.000
0.500
1.000
1.500
2.000
2.500
3.000
2011 2020 2030 2040 2050
Population growth rate (2011=1)AKM
AKT
ALM
ATY
WKZ
ZHA
KAR
KST
KZL
MAN
Model drivers: GDP, GDPP and population are very different from region to regionService elasticities to drivers from national model, inelastic demand projections
0.5
1
1.5
2
2.5
3
Historic GDP growth of Kazakhstan
GDP
Scenarios
INDCLimits GHG emissions from fuel combustion to 198.9 Mt CO2 eq. at national level (stabilization at current level)
-50000.00
0.00
50000.00
100000.00
150000.00
200000.00
250000.00
300000.00
350000.00
400000.00
450000.00
1990 1995 2000 2005 2010 2014
GHG emissions trend in Kazakhstan, kt CO2 eq.
5. Waste
4. Land use, land-usechange and forestry(1)
3. Agriculture
2. Industrial processes andproduct use
1. Energy
1990 minus 15% (INDCtarget)
BaUWithout implementing any constraint on GHG emissions.
• INDC unconditional target of Kazakhstan is to reduce GHG emissions by 15% compared to 1990 level (317.3 Mt)
• In 2014 the target has been already exceeded by 7%
• Ambitious target!
Results
Most emissions reductions occur in 3 regions: Almaty, Karaganda and Pavlodar. Last 2 regions are regions with heavy industries and main electricity generation capacities.
194.5211.1
230.8210.6
198.9
0.0
50.0
100.0
150.0
200.0
250.0
1 2 3
Total GHG emissions from fuel combustion, Mt
BaU
INDC
-5
0
5
10
15
20
Differences in GHG emissions from fuel combustion between BaU and INDC scenario by
regions in 2030, Mt
Total GHG emissions in the system from fuel combustionDifference between BaU and INDC scenario is about 32 Mt CO2 eq in 2030
Emissions reduction has lower cost
in supply side than in demand
side. Therefore 28.6 Mt GHG emission reduction comes from supply and only 3.3 Mt from demand side.
75.681.0
91.3
118.9130.1
139.5
80.888.0
129.9110.9
0.0
20.0
40.0
60.0
80.0
100.0
120.0
140.0
160.0
2011 2020 2030 2011 2020 2030
Demand Supply
GHG emissions from fuel combustion, Mt
BaU
INDC
-0.09
0.17
27.88
1.24 1.32 0.56 0.51
-5.00
0.00
5.00
10.00
15.00
20.00
25.00
30.00
Differences in CO2 emissions from fuel combustion between Business as usual and INDC scenario by
regions of KZK, mln t
2020 2030
Emission reduction potential by sectors
Energy sector emission reduction based on both improved efficiency and decreased production.
INDC scenario requires 21% less coal
than BaU. Oil and gas at same level.
But TFC in INDC scenario is only 4% less than in BaU scenario.
INDC target reached by increasing
efficiency of energy supply, TFC/TPES increased by 4.6% in 2030.
0
200
400
600
800
1000
1200
1400
1600
1800
2000
BaU INDC BaU INDC
2011 2020 2030
Total final consumtion, PJ
Agriculuture
Commercial
Residential
Transport
Industry
0
500
1000
1500
2000
2500
3000
3500
BaU INDC BaU INDC
2011 2020 2030
Primary energy supply, PJ
Oil
Gas
Coal
49.9%
54.4% 54.4% 57.9% 62.5%
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
0 BaU INDC BaU INDC
2011 2020 2030
TFC/TPES
Energy supply and demand
Power generation
• In INDC scenario electricity and heat generation decreased by 6.3% and 3.5% accordingly compared to BaU
• Coal based Pavlodar and Karaganda remain main electricity producers in BaU
• In INDC new capacities are installed in the regions with high demand growth
-40000
-30000
-20000
-10000
0
10000
20000
30000
40000
50000
60000
AKM AKT ALC ALM AST ATY EKZ KAR KST KZL MAN NKZ PAV SKZ WKZ ZHA
Difference between BaU and INDC electricity generation, TJ
2020
2030
0
100000
200000
300000
400000
500000
600000
700000
2011 2020 2030 2011 2020 2030
Electricity Heat
Electricity and heat generation, TJ
BaU
INDC
Heat generation is more or less same in two scenarios by regions.
-30000 20000 70000 120000 170000 220000
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaU
BaUA
KM
AK
TA
LCA
LMA
STA
TYEK
ZK
AR
KST
KZL
MA
NN
KZ
PA
VSK
ZW
KZ
ZHA Electricity and heat generation by regions in 2030, TJ
Electricity
Heat
Power and heat generation
Coal consumption decreased and gas
consumption at same level, systems overall efficiency increased
0.0%
10.0%
20.0%
30.0%
40.0%
50.0%
60.0%
70.0%
80.0%
BaU INDC BaU INDC BaU INDC
Generationefficiency
Share of hydro Share of wind
2011
2020
2030
-90000
-40000
10000
60000
110000
160000
Coal Gas Fuel oil
In order to meet INDC target system uses more efficient generation technologies and installed wind power plant with share of generation 4.5%. Hydro power plants generation are same in both scenarios.
Fuel consumption for power generation and RES
Investments
-150
-100
-50
0
50
100
150
200
AKM AKT ALC ALM AST ATY EKZ KAR KST KZL MAN NKZ PAV SKZ WKZ ZHA
Difference in investments by regions in BaU and INDC scenario, mln$
2020
2030
More investments in the regions with high demand growth, less investments in coal regions
Result from national TIMES KZK model
INDC (- 15% 1990)305
424
526
654
329
341399
494
591
380
447
508
307
344
375389
250
350
450
550
650
2011 2015 2020 2025 2030 2035 2040 2045 2050
MtC
O2
eq
GHG emissions scenarios
Baseline INDC ETS
ETS_HS ETS_HS & ADJ ETS_HS & CO2Tax
Differences in the results• National model: In Baseline scenario, the gap between emissions and the INDC target
reaches 59 MtCO2eq in 2030 • Regional model: 32 Mt CO2eq in 2030• National model uses higher GDP growth rate and sectoral drivers from CGE model,
regional model more pessimistic• More work will be done on comparing the results and understanding the differences
Conclusions
• INDC target can be achieved by– gradual retirement of old coal generating capacities
– coal consumption, obviously, must be decreased
– new generating capacities in the regions with highest demand growth
– gas power generation in already gasified regions > no need for gas pipeline (in contrast with national model results)
• Regionalized energy and climate policies needed
• Significant advantages comparing to national model (energy demand distribution, particularly heating, energy prices by regions etc.)
Future work
• Regional renewable energy penetration potential
• Different national and regional economic development scenarios
• Different regional burden sharing of GHG emissions reduction
• Disaggregation of housing stock
This research was funded under the target program
№0115РК03041 “Research and development in the fields of
energy efficiency and energy saving, renewable energy
sources and environmental protection for years 2014-2016”
from the Ministry of Education and Science of the Republic of
Kazakhstan.
The provision of data by the Committee of Statistics of the
Republic of Kazakhstan, Information Analytical Center on Oil
and Gas, Ministry of Energy of the Republic of Kazakhstan is
greatly acknowledged.
Acknowledgements
