Post-2020 Mitigation Scenarios and Carbon Pricing Modelling - - PowerPoint PPT Presentation

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Post-2020 Mitigation Scenarios and Carbon Pricing Modelling - - PowerPoint PPT Presentation

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PMR Technical Workshop Post-2020 Mitigation Scenarios and Carbon Pricing Modelling Session Key modeling issues and challenges facing ETS design and implementation Kazakhstan case Aidyn Bakdolotov Nazarbayev University Research

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PMR Technical Workshop “Post-2020 Mitigation Scenarios and Carbon Pricing Modelling” Session “Key modeling issues and challenges facing ETS design and implementation” Kazakhstan case

Aidyn Bakdolotov Nazarbayev University Research and Innovation System aidyn.bakdolotov@nu.edu.kz Brasilia, 03 February 2016

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  • Overview of Kazakhstan’s ETS
  • Modeling capacities
  • Modeling activities undertaken
  • Modeling activities planned
  • Conclusions

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2009 – the ratification of the Kyoto Protocol 2010 – start of ETS development – Cap-and-Trade scheme

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ETS Design Element Kazakhstan Coverage Companies in Oil, coal, and gas; power; mining and metallurgy; chemical Emission Coverage Phase I: About 55% of Kazakhstan’s GHG emissions and 77% of CO2 Gases Covered Carbon Dioxide (CO2) Threshold for Inclusion 20,000t/CO2e/yr

National allocation plan for 2013 Number of enterprises 178 Free allowances 147 MtCO2 Reserve 20 MtCO2 Sectors covered: energy, oil & gas, industry National allocation plan for 2014-2015 Number of enterprises 166 Free allowances 307 MtCO2 Reserve 38 MtCO2 Sectors covered: energy, oil & gas, industry National allocation plan for 2016-2020 Number of enterprises 140 Free allowances 746 MtCO2 Reserve 22 MtCO2 Sectors covered: energy, oil & gas, industry

Overview of Kazakhstan’s ETS

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  • Overview of Kazakhstan’s ETS
  • Modeling capacities
  • Modeling activities undertaken
  • Modeling activities planned
  • Conclusions

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TIMES-KAZAKHSTAN MODEL

TIMES - The Integrated MARKAL-EFOM system developed by ETSAP of IEA Developed since 2011 under the project funded by Ministry of education and science of RK System boundaries: national (monoregional) and subnational (multiregional) Time horizon: 2011-2050 GOAL: to explore the evolution of the system in the long-term, to design and test national energy-environmental related policies and strategy

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Supplies end-use energy services at minimum system cost by simultaneously making equipment investment and

  • perating,

primary energy supply, and energy trade decisions

  • Technology

investments (costs and capacities)

  • Flows of energy
  • Emissions
  • Trade
  • The existing system (capacities

and flows)

  • Assumptions on final energy

demands

  • Technical and economical

parameters of future technologies

  • Country-specific technical and

natural constraints

  • A set of P&M, projects

INPUT TIMES Output

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NEB Reclassification methodology

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Reclassified fuel-energy balance of Kazakhstan, 2013 (ktoe)

Coal Crude Oil Oil Products Gas Hydro Combustible Renewables & Waste Electricity Heat Total Production 49925 82203 24469 662 874 158133 Imports 798 7531 8305 4472 72 21179 Exports

  • 13708
  • 73235
  • 10044
  • 11367
  • 277
  • 108631

Stock changes

  • 672
  • 202
  • 174
  • 2
  • 1049

Total primary energy supply 36343 16499

  • 1947

17400 662 872

  • 205

69626 Transfers 4

  • 5
  • 1

Statistical differences 1 1 Main activity producer electricity plants

  • 9481
  • 418
  • 662

3876

  • 6685

Autoproducer electricity plants

  • 2089

752

  • 1337

Main activity producer CHP plants

  • 9964
  • 25
  • 1467

2494 3669

  • 5293

Autoproducer CHP plants

  • 2929
  • 52
  • 1280

793 1599

  • 1869

Main activity producer heat plants

  • 3466
  • 430
  • 2664

4254

  • 2305

Oil refineries

  • 15679

15580

  • 99

Coal transformation

  • 2257
  • 2257

Non-specified (transformation) 547 71 618 Energy industry own use

  • 605
  • 192
  • 1571
  • 4508
  • 1471
  • 810
  • 9158

Losses

  • 3
  • 612
  • 128
  • 878
  • 661
  • 1937
  • 4219

Final consumption 7643 16 11972 4102 943 5579 6774 37029 Industry 3628 13 2320 903 1 3398 2200 12463 Iron and steel 2793 519 34 1069 660 5075 Chemical and petrochemical 10 22 254 244 137 667 Non-ferrous metals 1135 900 2035 Non-metallic minerals 607 73 147 114 53 993 Transport equipment 1 3 4 52 10 69 Machinery 20 13 33 3 54 48 171 Mining and quarrying 118 618 322 551 157 1765 Food and tobacco 32 118 86 111 173 520 Paper, pulp and print 2 13 5 11 31 Wood and wood products Construction 38 922 30 1 41 34 1066 Textile and leather 1 4 2 9 8 24 Non-specified (industry) 7 7 8 15 10 47 Transport 5 3 5254 330 78 8 5677 Road 4583 4583 Domestic aviation 370 370 Rail 4 277 61 342 Pipeline transport 3 11 330 17 8 369 Domestic navigation 13 13 Other 3797 4088 2636 941 2103 4567 18133 Residential 2402 1568 2179 919 925 2362 10355 Commercial and public services 1220 2012 439 21 1109 2115 6916 Agriculture/forestry 176 506 19 2 68 89 860 Non-energy use 213 310 233 756 Non-energy use industry/transformation/energy 213 310 233 756

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Sectoral disaggregation and calibration

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  • The National Energy Balance is the main source for the description of flows

and technologies in the energy model.

  • Breakdown of the balance and calibration of the base-year system according

to a bottom-up approach.

BALANCE Commodity 1 Commodity 2 Commodity 3 Commodity 4 Commodity 5 Commodity 6 item 1 X 1,1 X 1,2 X 1,3 X 1,4 X 1,5 X 1,6 item 2 X 2,1 X 2,2 X 2,3 X 2,4 X 2,5 X 2,6 item 3 X 3,1 X 3,2 X 3,3 X 3,4 X 3,5 X 3,6 item 4 X 4,1 X 4,2 X 4,3 X 4,4 X 4,5 X 4,6 item 5 X 5,1 X 5,2 X 5,3 X 5,4 X 5,5 X 5,6 item 6 X 6,1 X 6,2 X 6,3 X 6,4 X 6,5 X 6,6 Service Commodity 1 Commodity 2 Commodity 3 Commodity 4 Commodity 5 Commodity 6 item A,1 =30%*X 1,1 =50%*X 1,2 =10%*X 1,3 =0%*X 1,4 =30%*X 1,5 =20%*X 1,6 item B,1 =40%*X 1,1 =20%*X 1,2 =40%*X 1,3 =70%*X 1,4 =40%*X 1,5 =20%*X 1,6 item C,1 =30%*X 1,1 =70%*X 1,2 =50%*X 1,3 =30%*X 1,4 =30%*X 1,5 =60%*X 1,6 item A,2 =10%*X 2,1 =25%*X 2,2 =10%*X 2,3 =20%*X 2,4 =35%*X 2,5 =50%*X 2,6 item B,2 =60%*X 2,1 =55%*X 2,2 =60%*X 2,3 =40%*X 2,4 =35%*X 2,5 =15%*X 2,6 item C,2 =30%*X 2,1 =20%*X 2,2 =30%*X 2,3 =40%*X 2,4 =30%*X 2,5 =35%*X 2,6

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  • Overview of Kazakhstan’s ETS
  • Modeling capacities
  • Modeling activities undertaken
  • Modeling activities planned
  • Conclusions

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Modelling activities undertaken

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Aim: analysis of the impact of the domestic carbon market on the macroeconomic indicators of economic development Time of modelling: June 2014. Modelling tool: TIMES-KZK. Obstacles:

  • GDP (macroeconomic parameter) is exogenous to the model
  • Mismatch of the sectors in model with sectors covered by NAP
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Projections of GDP and Population

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Two projections of GDP (at June 2014): One projections of Population:

ETS scenarios

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Baseline scenario

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100 200 300 400 2009 2010 2012 2015 2020 2025 2030 Mln CO2-eq

CO2 emissions in three sectors

Power sector Industry sector Upstream sector 0% 20% 40% 60% 80% 100% 2009 2010 2012 2015 2020 2025 2030

CO2 emissions in three sectors

Power sector Industry sector Upstream sector

  • Baseline scenario is the basis for calculation of the sectoral caps for the next scenarios
  • The formula for sectoral caps is the same as in the NAP (based on historical values)
  • For the whole time horizon, the caps have been calculated based on emissions from previous years

plus reserve quota for new installations (20 MtCO2-eq)

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Marginal costs of CO2

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0.00 50.00 100.00 150.00 200.00 250.00 300.00 350.00 400.00 450.00 500.00 2020 2025 2030 2020 2025 2030 GDP-I GDP-II Cap Power sector Cap Industy sector Cap Upstream sector Cap-and-Trade

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Trade flows between sectors (CO2 in tones)

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Trade between sectors “Cap-and-Trade” scenario and GDP-I from/to Industy sector Upstream sector 2020 Power sector 13120 5960 Upstream sector 2025 Power sector 15310 Upstream sector 988 2030 Power sector 11033 Upstream sector 10405

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Observations and lessons

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  • The design of the ETS in the model not fully replicated domestic ETS due

to the mismatch of the sectors and levels of disaggregation

  • The standalone TIMES model cannot reflect the trade between the

enterprises in the same sector

  • The standalone TIMES model cannot directly estimate the ETS impact on

macroeconomic parameters (link with CGE can do it)

  • The power sector is the most flexible due to the shifting from coal to gas
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  • Overview of Kazakhstan’s ETS
  • Modeling capacities
  • Modeling activities undertaken
  • Modeling activities planned
  • Conclusions

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PMR Project

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Top-down economic models

  • represent an entire economy
  • able to project long-run balanced growth of the entire economy and by sectors
  • capture the distribution of production factors and commodities

Bottom-up models

  • depict the energy system with a high level of technological detail
  • find the optimal mix of technologies and fuels at each time period as well as their costs/prices

The work on linking aims to combine economic comprehensiveness of top-down models with technological explicitness of bottom-up models. There are three approaches to linking: 1.Independently developed bottom-up and top-down models are linked (soft-linking). 2.A focus is laid on one model type and a “reduced form” representation of the other. 3.The models are completely integrated which allow for jointly solving both models. We focus on the soft-linking approach.

Top-down and bottom-up models and linking methodology

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Iteration cycle of the hybrid model

Demand generator

TIMES-KZ

Linking process

CGE-KZ

  • GDP growth
  • Sectoral output development
  • Households income growth
  • Sectoral energy

service demands

  • Production structure in power

and heat sector

  • Energy consumption per

sector/household

  • Development of prices for

primary energy sources

  • Investment cost per activity
  • Adjustment of time dimensions

(interpolation)

  • Adjustment of model parameters

(Leontief production function)

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First iteration results (baseline scenario)

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INDC and ETS scenarios

First scenario: INDC-optimal: a universal cap (1990-level minus 15%) on GHG emissions from fuel combustion in all energy-relevant sectors (i.e. all sectors covered by TIMES) The result are emission levels for all sectors The link to the second and third scenario will be: a comparison of the current ETS-caps with the optimal ones from TIMES This will show the measures for meeting the INDC target. The following two scenarios make sense: Second scenario: ETS-sectors to provide the required abatement Third scenario: non ETS-sectors to provide the required abatement

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  • Overview of Kazakhstan’s ETS
  • Modeling capacities
  • Modeling activities undertaken
  • Modeling activities planned
  • Conclusions

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Conclusions The Kazakhstan’s ETS is in operation and is the first in the FSU countries The standalone TIMES model cannot fully represent the ETS and its impact on economy The hybrid model can give more insights into impacts of INDC and role of ETS on economy and energy system

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Thanks for attention!

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ETS modelling approach (1)

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Baseline scenario ELCCO2 <= infinity INDCO2 <= infinity UPSCO2 <= infinity 6 5 2 ELCCO2 INDCO2 UPSCO2

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ETS modelling approach (2)

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Cap scenario ELCCO2 <= 8 INDCO2 <= 3 UPSCO2 <= 2 8 Changes 6 $$$ 3 $ 2 ELCCO2 INDCO2 UPSCO2

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ETS modelling approach (3)

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Cap-and-Trade scenario ELCCO2 + ELCINDCO2 + ELCUPSCO2 <= 8 INDCO2 + INDELCCO2 + INDUPSCO2 <= 3 UPSCO2 + UPSELCCO2 + UPSINDCO2 <= 2 8 + Changes 6 + $$$ 5 +

  • 3

+

  • $

+ 2 + + ELCCO2 INDCO2 UPSCO2