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Use of experience curves to estimate the future cost of power plants with CO2 capture


  • Rubin, Edward S.
  • Yeh, Sonia
  • Antes, Matt
  • Berkenpas, Michael
  • Davison, John


Given the dominance of power plant emissions of greenhouse gases, and the growing worldwide interest in CO2 capture and storage (CCS) as a potential climate change mitigation option, the expected future cost of power plants with CO2 capture is of significant interest. Reductions in the cost of technologies as a result of learning-by-doing, R&D investments and other factors have been observed over many decades. This study uses historical experience curves as the basis for estimating future cost trends for four types of electric power plants equipped with CO2 capture systems: pulverized coal (PC) and natural gas combined cycle (NGCC) plants with post-combustion CO2 capture; coal-based integrated gasification combined cycle (IGCC) plants with pre-combustion capture; and coal-fired oxyfuel combustion for new PC plants. We first assess the rates of cost reductions achieved by other energy and environmental process technologies in the past. Then, by analogy with leading capture plant designs, we estimate future cost reductions that might be achieved by power plants employing CO2 capture. Effects of uncertainties in key parameters on projected cost reductions also are evaluated via sensitivity analysis.

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  • Rubin, Edward S. & Yeh, Sonia & Antes, Matt & Berkenpas, Michael & Davison, John, 2007. "Use of experience curves to estimate the future cost of power plants with CO2 capture," Institute of Transportation Studies, Working Paper Series qt46x6h0n0, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt46x6h0n0

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    References listed on IDEAS

    1. J Landis & M Zhang, 1998. "The second generation of the California urban futures model. Part 1: Model logic and theory," Environment and Planning B: Planning and Design, Pion Ltd, London, vol. 25(5), pages 657-666, September.
    2. D A Plane & P A Rogerson, 1985. "Economic - demographic models for forecasting interregional migration," Environment and Planning A, Pion Ltd, London, vol. 17(2), pages 185-198, February.
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    UCD-ITS-RP-07-27; Engineering;


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