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Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options

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  • Cong, Rong-Gang
  • Wei, Yi-Ming

Abstract

In Copenhagen climate conference China government promised that China would cut down carbon intensity 40e45% from 2005 by 2020. CET (carbon emissions trading) is an effective tool to reduce emissions. But because CET is not fully implemented in China up to now, how to design it and its potential impact are unknown to us. This paper studies the potential impact of introduction of CET on China’s power sector and discusses the impact of different allocation options of allowances. Agent-based modeling is one appealing new methodology that has the potential to overcome some shortcomings of traditional methods. We establish an agent-based model, CETICEM (CET Introduced China Electricity Market), of introduction of CET to China. In CETICEM, six types of agents and two markets are modeled. We find that: (1) CET internalizes environment cost; increases the average electricity price by 12%; and transfers carbon price volatility to the electricity market, increasing electricity price volatility by 4%. (2) CET influences the relative cost of different power generation technologies through the carbon price, significantly increasing the proportion of environmentally friendly technologies; expensive solar power generation in particular develops significantly, with final proportion increasing by 14%. (3) Emissionbased allocation brings about both higher electricity and carbon prices than by output-based allocation which encourages producers to be environmentally friendly. Therefore, output-based allocation would be more conducive to reducing emissions in the Chinese power sector.

Suggested Citation

  • Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," MPRA Paper 52775, University Library of Munich, Germany.
  • Handle: RePEc:pra:mprapa:52775
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    1. Cramton, Peter & Kerr, Suzi, 2002. "Tradeable carbon permit auctions: How and why to auction not grandfather," Energy Policy, Elsevier, vol. 30(4), pages 333-345, March.
    2. Bunn, Derek W. & Oliveira, Fernando S., 2007. "Agent-based analysis of technological diversification and specialization in electricity markets," European Journal of Operational Research, Elsevier, vol. 181(3), pages 1265-1278, September.
    3. Tom Tietenberg, 2003. "The Tradable-Permits Approach to Protecting the Commons: Lessons for Climate Change," Oxford Review of Economic Policy, Oxford University Press, vol. 19(3), pages 400-419.
    4. Derek Bunn & Fernando Oliveira, 2003. "Evaluating Individual Market Power in Electricity Markets via Agent-Based Simulation," Annals of Operations Research, Springer, vol. 121(1), pages 57-77, July.
    5. Kim Keats Martinez & Karsten Neuhoff, 2005. "Allocation of carbon emission certificates in the power sector: how generators profit from grandfathered rights," Climate Policy, Taylor & Francis Journals, vol. 5(1), pages 61-78, January.
    6. Raufer, Roger & Li, Shaoyi, 2009. "Emissions trading in China: A conceptual ‘leapfrog’ approach?," Energy, Elsevier, vol. 34(7), pages 904-912.
    7. Bohringer, Christoph & Lange, Andreas, 2005. "On the design of optimal grandfathering schemes for emission allowances," European Economic Review, Elsevier, vol. 49(8), pages 2041-2055, November.
    8. Ehlen, Mark A. & Scholand, Andrew J. & Stamber, Kevin L., 2007. "The effects of residential real-time pricing contracts on transco loads, pricing, and profitability: Simulations using the N-ABLE(TM) agent-based model," Energy Economics, Elsevier, vol. 29(2), pages 211-227, March.
    9. Szabo, Laszlo & Hidalgo, Ignacio & Ciscar, Juan Carlos & Soria, Antonio, 2006. "CO2 emission trading within the European Union and Annex B countries: the cement industry case," Energy Policy, Elsevier, vol. 34(1), pages 72-87, January.
    10. Hämäläinen, Raimo P & Mäntysaari, Juha & Ruusunen, Jukka & Pierre-Olivier Pineau,, 2000. "Cooperative consumers in a deregulated electricity market — dynamic consumption strategies and price coordination," Energy, Elsevier, vol. 25(9), pages 857-875.
    11. Ma, Tieju & Nakamori, Yoshiteru, 2009. "Modeling technological change in energy systems – From optimization to agent-based modeling," Energy, Elsevier, vol. 34(7), pages 873-879.
    12. Burtraw, Dallas & Palmer, Karen L. & Bharvirkar, Ranjit & Paul, Anthony, 2001. "The Effect of Allowance Allocation on the Cost of Carbon Emission Trading," Discussion Papers 10536, Resources for the Future.
    13. Burtraw, Dallas & Palmer, Karen & Bharvirkar, Ranjit & Paul, Anthony, 2001. "The Effect of Allowance Allocation on the Cost of Carbon Emission Trading," Discussion Papers dp-01-30-, Resources For the Future.
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    More about this item

    Keywords

    Carbon emissions trading Emission-based allocation Output-based allocation Agent-based model;

    JEL classification:

    • Q4 - Agricultural and Natural Resource Economics; Environmental and Ecological Economics - - Energy

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