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Progress and prospect of CCS in China: Using learning curve to assess the cost-viability of a 2×600MW retrofitted oxyfuel power plant as a case study

Author

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  • Wu, X.D.
  • Yang, Q.
  • Chen, G.Q.
  • Hayat, T.
  • Alsaedi, A.

Abstract

Though carbon capture and storage (CCS) gains its momentum in China in context of the energy-mix that features heavy reliance on coal, it is currently obscure and full of uncertainty, of which a primary concern goes to the cost viability of CCS. However, previous technical-economic studies mainly take a static perspective to look into the cost of carbon capture systems, without fair consideration of the potential future cost slide brought by continuous expansion of CCS technologies and technical improvement. In recognition of this, a dynamic cost analysis is undertaken in our work by applying learning curve to exploring CCS prospect in China, together with a detailed review of domestic CCS progress. An oxyfuel power plant retrofitted from a typical traditional 2×600MW power plant in China is chosen as a case study. The result suggests that the unit capital cost for the oxyfuel combustion plant will fall from 4926.30RMB¥/kW to around 2977.02–3981.20RMB¥/kW and the cost of electricity is supposed to drop drastically from the initial level 459.70 RMB¥/MWh to around 342.29–399.37RMB¥/MWh when the aggregated capacity reaches 100GW. The sharp decline forecasts that in the long term CCS technology could be a cost-effective option to be deployed together with other clean energy options. In addition, compared with IGCC and post-combustion systems with carbon capture, the oxyfuel combustion technology is illustrated quite competent in the long-term deployment.

Suggested Citation

  • Wu, X.D. & Yang, Q. & Chen, G.Q. & Hayat, T. & Alsaedi, A., 2016. "Progress and prospect of CCS in China: Using learning curve to assess the cost-viability of a 2×600MW retrofitted oxyfuel power plant as a case study," Renewable and Sustainable Energy Reviews, Elsevier, vol. 60(C), pages 1274-1285.
  • Handle: RePEc:eee:rensus:v:60:y:2016:i:c:p:1274-1285
    DOI: 10.1016/j.rser.2016.03.015
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