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A centurial history of technological change and learning curves or pulverized coal-fired utility boilers

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  • Yeh, Sonia
  • Rubin, Edward

Abstract

Recent study of the history of technological change has provided better understanding of the driving forces for technological innovation, as well as quantitative estimates of historical rates of technical change. Although such results are widely used in long-term energy models to estimate future costs over time periods of up to a century, most studies of technological learning for major energy technologies are based on historical trends over time periods not longer than 20–30 years (often because of data limitations). Relatively few studies quantify longer-term (century-scale) trends. This study helps fill that gap by reviewing the history of pulverized-coal (PC) power plants, with a specific focus on the technological progress of PC boiler technology over the last century. Historical data for U.S. plants are used to develop long-term experience curves for the overall thermal efficiency of PC power plants, as well as the capital cost of PC boilers and non-fuel operating and maintenance (O&M) costs of PC plants. Despite a technology plateau experienced by PC power plants two decades ago, recent developments indicate that such plants will continue to improve and remain a competitive and important part of power generation technology portfolios.

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  • Yeh, Sonia & Rubin, Edward, 2007. "A centurial history of technological change and learning curves or pulverized coal-fired utility boilers," Institute of Transportation Studies, Working Paper Series qt4xn4w7rn, Institute of Transportation Studies, UC Davis.
  • Handle: RePEc:cdl:itsdav:qt4xn4w7rn
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    1. Argote, L. & Epple, D., 1990. "Learning Curves In Manufacturing," GSIA Working Papers 89-90-02, Carnegie Mellon University, Tepper School of Business.
    2. James G. Hewlett, 1996. "Economic and Regulatory Factors Affecting the Maintenance of Nucleaer Power Plants," The Energy Journal, International Association for Energy Economics, vol. 0(Number 4), pages 1-31.
    3. Sabine Messner, 1997. "Endogenized technological learning in an energy systems model," Journal of Evolutionary Economics, Springer, vol. 7(3), pages 291-313.
    4. McDonald, Alan & Schrattenholzer, Leo, 2001. "Learning rates for energy technologies," Energy Policy, Elsevier, vol. 29(4), pages 255-261, March.
    5. Socrates Kypreos & Leonardo Barreto & Pantelis Capros & Sabine Messner, 2000. "ERIS: A model prototype with endogenous technological change," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 347-397.
    6. Riahi, Keywan & Rubin, Edward S. & Schrattenholzer, Leo, 2004. "Prospects for carbon capture and sequestration technologies assuming their technological learning," Energy, Elsevier, vol. 29(9), pages 1309-1318.
    7. Dutton, John M. & Thomas, Annie & Butler, John E., 1984. "The History of Progress Functions as a Managerial Technology," Business History Review, Cambridge University Press, vol. 58(2), pages 204-233, July.
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