TIMES-Kazakhstan: from a national to a regional analysis and modeling

1. TIMES-Kazakhstan: from a national to a regional analysis and
modelling
Aiymgul Kerimray, Rocco De Miglio,
Aidyn Bakdolotov, Igor Kolyagin,
Bakytzhan Suleimenov, Yerbol Akhmetbekov
June 1st 2015
ETSAP Workshop
Abu Dhabi, Dusit Thani Hotel
National Laboratory Astana

2. ENERGY BALANCE OF KAZAKHSTAN IN
2012
TFC/TPES = 55%
IEA (2013)
High exports
High energy industry
own use and losses

3. GDP ENERGY INTENSITY OF
KAZAKHSTAN
• Kazakhstan takes 11th place in the world with its GDP energy intensity
• There are some differences in IEA and NU assessments (8-15%)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
toe/1000$2005USD
GDP energy intensity in 2011
Kazakhstan IEA
Kazakhstan-NURIS
0
0.2
0.4
0.6
0.8
1
1.2
toe/1000$2005USD
GDP Energy intensity over 2007-
2012
NURIS
IEA

4. REASONS FOR INEFFICIENCIES
Geographical: the continental climate, large
territory, low population density 6 people/sq.m.
and uneven distribution of power generating
capacities over the territory
Administrative and economic: lack of
metering for energy saving, low profitability
Technical: high wear of the equipment in the
energy intensive sectors, high wear of electric
lines, dilapidation of the housing stock
• Low efficiencies of power plants, almost 50
% of generating capacities has run for more
than 30 years
• Huge transmission (5%) and distribution
(13%) losses of electricity
• Up to 35% of losses of heat in distribution
0.56
0.70 0.71
0.83
0.61 0.60
0.68 0.67
0.0
0.1
0.2
0.3
0.4
0.5
0.6
0.7
0.8
0.9
TFC/TPES (2012)

5. TOTAL PRIMARY ENERGY SUPPLY
-10000
-5000
0
5000
10000
15000
20000
25000
30000
35000
40000
Coal &peat Crude oil Natural gas RES&Nuclear Oil products
Total primary energy supply over 2007-2012, ktoe (NU)
2007
2008
2009
2010
2011
2012

6. ENERGY CONSUMPTION BY SECTORS
0
2000
4000
6000
8000
10000
12000
14000
Industry Transport Residential Other Non-energy
use
Energy consumption by sectors, 2007-2012, ktoe (NU)
2007
2008
2009
2010
2011
2012

7. GHG EMISSIONS IN KAZAKHSTAN
-50000
0
50000
100000
150000
200000
250000
300000
350000
400000
1990 1992 1994 1996 1998 2000 2002 2004 2006 2008 2010 2012
ktCO2eq.
GHG emissions historical dynamics, 1990-2012
Fuel combustion Industrial processes Agriculture LULUCF Waste

8. TIMES-KAZAKHSTAN MODEL
Developed since 2011 under the project funded by Ministry of Education and
Science of RoK
GOAL: to explore the evolution of the system in the long-term, to design and test
national energy-environmental related policies and strategy
Collaboration: ASATREM, E4SMA
Geographical boundaries: national (monoregional)
Time horizon: 2009-2050
System boundaries: the entire energy system (from the upstream to the demand)
Additional modules and features:
• Own-price elasticities for the end-use demands
• Endogenous retirement profiles of the power plants
• Domestic and/or International ETS
• LULUCF and industrial processes emissions (III-VI National Communication
UNFCCC)
• Scenarios considered:
 GHG reduction potential
 Energy efficiency improvement potential
 Impact of ETS

9. DRIVERS OF THE MODEL
• The population is assumed to grow at 1.25%pa
• GDP was expected to rise at an annual rate of 6%pa until 2020, and 5%pa until 2030: IMF
projections in 2013)

10. MODELING RESULTS – ENERGY
EFFICIENCY
Two scenarios were :
• reducing energy intensity of GDP by 40% by 2020 (compared to the 2008
level) as set in the Energy Saving-2020 programme
• introducing an incentive of US$20 (at 2000 prices) per ton of CO2 equivalent
reduced starting from 2020 (CO2TAX).
The efficiency gaps (EFF(ET)j <= EFF(NTi)j) between an existing “reference”
technology (ET) and the new ones (NTi) available for the same energy
sector/service (j), as well as the “virtual” savings due to the use of more
efficient technologies (Q(NTi)j).

11. MODELING RESULTS – ENERGY
EFFICIENCY
0
200
400
600
0
10
20
30
40
50
2009 202020252030 202020252030 202020252030
BaU Energy intensity
reduction target
CO2TAX
CO2emissionsinMt
Mtoe
Energy Efficiency Improvements (EEI) in different part
of Energy System and CO2 emissions
Coal Transformation 220 kV - transmission 500 kV - transmission
ELC - End-use ELC - distribution ELC - after meters
NGA - End-use NGA - transformation NGA - distribution grids
NGA - transport Heat - distribution Heat - transport
Oil - End-use TOTCO2

12. MODELING RESULTS – ENERGY
EFFICIENCY
0
5
10
15
20
25
0
20
40
60
80
100
120
140
2009 202020252030 202020252030 202020252030
BaU Energy intensity
reduction target
CO2TAX
Consumption(Mtoe)
PrimaryEnergy(Mtoe)
Dynamics of TPES, Electricity and Heat Consumption of
Kazakhstan
Coal Oil Natural gas Renewables Electricity Electric District heat

13. MODELING RESULTS – ENERGY
EFFICIENCY

14. KAZAKHSTAN’S 16 REGIONS TIMES
MODEL
14/19
Geographical boundaries: 14 regions and 2 cities: Astana
(capital) and Almaty (financial center)
Time horizon: 2011-2050
System boundaries: the energy system
GOAL: to explore the potentials and the need of the different oblasts, the
synergies across the regions (energy exchanges), and to assess the energy
related investment location decisions.
State of development: early stage (electricity and heat chains are
described)
Kazakhstan has a large territory of 2.7 mln km2 (9th place in the world )
3000 km from west to east and 1700 km from south to north

15. MAP OF PIPELINES IN KAZAKHSTAN

16. AVERAGE YEAR TEMPERATURE IN
KAZAKHSTAN, ˚C
Heating season varies from 143 to 231 days from region to region
Average year temperature varies from 2ºС in the north to 13ºС in the south

17. FUEL-ENERGY BALANCE – REGIONS
LEVEL (ASTANA CITY E.G.)
Astana city 2011 (ktoe) Coal Crude Oil Oil Products
Combustible
Renewables &
Waste
Electricity Heat Total
Production - - - - - - -
Imports 1,179.45 1,016.89 2,839.87 - 380.25 - 5,416.46
Exports -12.55 -1,018.94 -2,532.07 - -278.51 - -3,842.07
International marine bunkers - - - - - - -
International aviation bunkers - - - - - - -
Stock changes 5.55 1.14 104.70 0.04 - - 111.41
Total primary energy supply 1,172.45 -0.91 412.50 0.04 101.73 - 1,685.81
Transfers 12.80 - -17.39 - - - -4.59
Statistical differences -0.17 0.92 -1.33 0.08 0.03 -0.04 -0.51
Main activity producer electricity plants - - - - - - -
Autoproducer electricity plants - - - - - - -
Main activity producer CHP plants -1,039.44 - - - 204.26 464.78 -370.40
Autoproducer CHP plants - - -0.06 - - - -0.06
Main activity producer heat plants -71.04 - - - - 45.60 -25.44
Energy industry own use -0.02 - -23.21 -0.04 -46.26 -32.42 -101.93
Losses -5.33 - -14.49 - -37.10 -149.72 -206.65
Final consumption 69.25 0.01 356.02 0.08 222.67 328.20 976.22
Industry 20.83 - 38.90 0.04 32.63 18.86 111.26
Iron and steel 12.60 - 0.10 - 0.44 0.16 13.30
Chemical and petrochemical - - 0.00 - 0.00 0.01 0.01
Non-ferrous metals - - - - - - -
Non-metallic minerals 5.64 - 9.21 0.00 3.59 6.37 24.82
Transport equipment - - - - 0.17 - 0.17
Machinery 0.03 - 0.28 - 0.48 1.01 1.80
Mining and quarrying - - 0.05 - 0.01 - 0.06
Food and tobacco 2.20 - 1.32 - 2.13 3.02 8.67
Paper, pulp and print - - - - - - -
Wood and wood products - - 0.05 - 0.03 0.05 0.13
Construction 0.34 - 27.10 0.04 22.96 7.63 58.07
Textile and leather - - 0.01 - 0.03 0.04 0.09
Non-specified (industry) 0.02 - 0.77 - 2.78 0.58 4.15
Transport 0.05 - 219.39 - 0.38 0.14 219.97
Road 0.01 - 208.58 - - - 208.59
Domestic aviation - - 10.35 - - - 10.35
Rail 0.04 - 0.35 - 0.14 - 0.53
Pipeline transport - - 0.10 - 0.25 0.14 0.50
Domestic navigation - - - - - - -
Non-specified (transport) - - - - - - -
Other 48.36 0.01 90.83 0.04 189.66 309.20 638.09
Residential 32.66 - 68.78 - 53.41 215.82 370.67
Commercial and public services 15.65 0.01 18.98 0.04 136.18 93.17 264.03
Agriculture/forestry 0.00 - 0.46 - 0.01 - 0.48
Fishing 0.04 - 2.61 - 0.05 0.21 2.91
Non-specified (other) - - - - - - -
Non-energy use - - 6.90 - - - 6.90
Non-energy use industry/transformation/energy - - 6.90 - - - 6.90
• 48 FEBs for 16
regions were
reclassified (2010-
2012) to IEA format
• Different data
sources
• Analysis of statistical
differences
• Country balances
were updated
accordingly
• For the first time
regions level FEB

18. REGIONAL INDICATORS
76%
47%
57%
29%
53%
84%
46%
77%
57%
44%
57%
34%
54%
83%
58%
85%
0.00
0.10
0.20
0.30
0.40
0.50
0.60
0.70
0.80
0.90
Akmolaobl.
Aktobeobl.
Almatyobl.
Atyrauobl.
WKO
Zhambylobl.
Karagandaobl.
Kostanayobl.
Kyzylordaobl.
Mangistauobl.
SKO
Pavlodarobl.
NKO
EKO
Astanacity
Almatycity
TFC/TPES
WORLD AVERAGE
8.2 9.9
5.3 6.6 4.7 3.4
32.6
8.7
5.3
14.7
3.7
66.8
11.7 8.7 10.2
5.8
0.0
10.0
20.0
30.0
40.0
50.0
60.0
70.0
80.0
CO2 emissions per capita, t/person
Kazakhstan average
World average

19. -10000 -5000 0 5000 10000 15000 20000
Akmola obl.
Aktobe obl.
Almaty obl.
Atyrau obl.
West-Kazakhstan obl.
Zhambyl obl.
Karaganda obl.
Kostanay obl.
Kyzylorda obl.
Mangistau obl.
South-Kazakhstan obl.
Pavlodar obl.
North-Kazakhstan obl.
East-Kazakhstan obl.
Astana city
Almaty city
Total primary energy supply by fuel type, ktoe
Coal Crude oil Oil products Gas Electricity
REGIONAL INDICATORS
0
100
200
300
400
500
600
Consumption of heat by houses provided by
district heating per living area by regions of
Kazakhstan, kwh/m2
2011 Kazakhstan average Russia Finland

20. REGIONAL INDICATORS
20/19
Final consumption structure differ from region to region:
• Gas consumption varies from 0 to 48%
• Coal consumption varies from 0.1 to 42%
• Oil products varies from 12 to 52%
• Industrial consumption varies from 6 to 72%
0%
10%
20%
30%
40%
50%
60%
70%
80%
90%
100%
Final consumption by type of fuel, by regions, %
Heat Electricity Gas Oil products Crude oil Coal
0%
20%
40%
60%
80%
100%
Akmolaobl.
Aktobeobl.
Almatyobl.
Atyrauobl.
WKO
Zhambylobl.
Karagandaobl.
Kostanayobl.
Kyzylordaobl.
Mangistauobl.
SKO
Pavlodarobl.
NKO
EKO
Astanacity
Almatycity
Final consumption by sector, by
regions %
Non-energy use Agriculture/forestry
Services Population
Transport Industry

21. CONCLUSIONS, FUTURE WORK
21/19
• There is significant room for energy efficiency saving in
Kazakhstan even in BAU optimal solution (22Mtoe in 2030)
• CO2 reduction targets require higher gas penetration
• Regions of Kazakhstan differ significantly and energy efficiency
potential is different
• 16 regions model will improve the quality of modeling results but
requires more data and time

22. THANK YOU FOR YOUR
ATTENTION!
Aiymgul Kerimray
aiymgul.kerimray@nu.edu.kz