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Experience curve analysis on South Korean nuclear technology and comparative analysis with South Korean renewable technologies

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  • Kim, Dong Wook
  • Chang, Hyun Joon

Abstract

Increasing awareness on environmental damage and climate change has induced many nations to engage in green growth. South Korea, as one of the largest consumers of energy, is no exception and has shown its determination to pursue green growth in the future. In order to do so, South Korea plans to substitute fossil fuel with alternative sources in electricity generation. However, the key constraint to green growth is the high cost faced by renewable electricity generation. Fortunately, nuclear energy can serve as an economic alternative to fossil fuel. To achieve CO2 emission reduction and faster economic growth, it is wise to analyze prospects of alternatives using experience curve framework. The results and industry background are consistent for nuclear technology, and the results suggest that nuclear should serve as the main substitute. Consideration of policy risk inherent in renewable also strengthens the argument. Renewable technologies, on the other hand, showed overstated learning capacity that is partially inconsistent with technological background. Nevertheless, the renewable (photovoltaic and fuel cell22Although it may seem peculiar to many readers, this classification is based on Korean Government and Korean Power Exchange's classification. They classify fuel cell as a renewable energy source.) should help nuclear marginally in substituting fossil fuel in South Korea's Electricity Generation.

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  • Kim, Dong Wook & Chang, Hyun Joon, 2012. "Experience curve analysis on South Korean nuclear technology and comparative analysis with South Korean renewable technologies," Energy Policy, Elsevier, vol. 40(C), pages 361-373.
    • Handle: RePEc:eee:enepol:v:40:y:2012:i:c:p:361-373
    DOI: 10.1016/j.enpol.2011.10.021
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    as
    1. Kahouli-Brahmi, Sondes, 2008. "Technological learning in energy-environment-economy modelling: A survey," Energy Policy, Elsevier, vol. 36(1), pages 138-162, January.
    2. Park, Hojeong & Lim, Jaekyu, 2009. "Valuation of marginal CO2 abatement options for electric power plants in Korea," Energy Policy, Elsevier, vol. 37(5), pages 1834-1841, May.
    3. Arnoldo C. Hax & Nicolas S. Majluf, 1982. "Competitive Cost Dynamics: The Experience Curve," Interfaces, INFORMS, vol. 12(5), pages 50-61, October.
    4. Schaeffer, Roberto & Salem Szklo, Alexandre, 2001. "Future electric power technology choices of Brazil:: a possible conflict between local pollution and global climate change," Energy Policy, Elsevier, vol. 29(5), pages 355-369, April.
    5. Neij, Lena, 2008. "Cost development of future technologies for power generation--A study based on experience curves and complementary bottom-up assessments," Energy Policy, Elsevier, vol. 36(6), pages 2200-2211, June.
    6. Ansar, Jasmin & Sparks, Roger, 2009. "The experience curve, option value, and the energy paradox," Energy Policy, Elsevier, vol. 37(3), pages 1012-1020, March.
    7. Choi, Sungyeol & Jun, Eunju & Hwang, IlSoon & Starz, Anne & Mazour, Tom & Chang, SoonHeung & Burkart, Alex R., 2009. "Fourteen lessons learned from the successful nuclear power program of the Republic of Korea," Energy Policy, Elsevier, vol. 37(12), pages 5494-5508, December.
    8. Papineau, Maya, 2006. "An economic perspective on experience curves and dynamic economies in renewable energy technologies," Energy Policy, Elsevier, vol. 34(4), pages 422-432, March.
    9. Jun, Eunju & Kim, Wonjoon & Chang, Soon Heung, 2009. "The analysis of security cost for different energy sources," Applied Energy, Elsevier, vol. 86(10), pages 1894-1901, October.
    10. Allan, Grant & Eromenko, Igor & McGregor, Peter & Swales, Kim, 2011. "The regional electricity generation mix in Scotland: A portfolio selection approach incorporating marine technologies," Energy Policy, Elsevier, vol. 39(1), pages 6-22, January.
    11. Lee, Seong Kon & Mogi, Gento & Kim, Jong Wook, 2008. "The competitiveness of Korea as a developer of hydrogen energy technology: The AHP approach," Energy Policy, Elsevier, vol. 36(4), pages 1284-1291, April.
    12. Neij, Lena, 1997. "Use of experience curves to analyse the prospects for diffusion and adoption of renewable energy technology," Energy Policy, Elsevier, vol. 25(13), pages 1099-1107, November.
    13. Schilling, Melissa A. & Esmundo, Melissa, 2009. "Technology S-curves in renewable energy alternatives: Analysis and implications for industry and government," Energy Policy, Elsevier, vol. 37(5), pages 1767-1781, May.
    14. Spalding-Fecher, Randall & Matibe, David Khorommbi, 2003. "Electricity and externalities in South Africa," Energy Policy, Elsevier, vol. 31(8), pages 721-734, June.
    15. van Sark, W.G.J.H.M. & Alsema, E.A., 2010. "Potential errors when fitting experience curves by means of spreadsheet software," Energy Policy, Elsevier, vol. 38(11), pages 7508-7511, November.
    16. Marvin B. Lieberman, 1987. "The learning curve, diffusion, and competitive strategy," Strategic Management Journal, Wiley Blackwell, vol. 8(5), pages 441-452, September.
    17. Hadley, S. W. & Short, W., 2001. "Electricity sector analysis in the clean energy futures study," Energy Policy, Elsevier, vol. 29(14), pages 1285-1298, November.
    18. Chang, Hyun-Joon, 2003. "New horizons for Korean energy industry--shifting paradigms and challenges ahead," Energy Policy, Elsevier, vol. 31(11), pages 1073-1084, September.
    19. Kobos, Peter H. & Erickson, Jon D. & Drennen, Thomas E., 2006. "Technological learning and renewable energy costs: implications for US renewable energy policy," Energy Policy, Elsevier, vol. 34(13), pages 1645-1658, September.
    20. Ferioli, F. & Schoots, K. & van der Zwaan, B.C.C., 2009. "Use and limitations of learning curves for energy technology policy: A component-learning hypothesis," Energy Policy, Elsevier, vol. 37(7), pages 2525-2535, July.
    21. Tooraj Jamasb, 2006. "Technical Change Theory and Learning Curves: Patterns of Progress in Energy Technologies," Working Papers EPRG 0608, Energy Policy Research Group, Cambridge Judge Business School, University of Cambridge.
    22. Klaassen, Ger & Miketa, Asami & Larsen, Katarina & Sundqvist, Thomas, 2005. "The impact of R&D on innovation for wind energy in Denmark, Germany and the United Kingdom," Ecological Economics, Elsevier, vol. 54(2-3), pages 227-240, August.
    23. Sichao, Kan & Yamamoto, Hiromi & Yamaji, Kenji, 2010. "Evaluation of CO2 free electricity trading market in Japan by multi-agent simulations," Energy Policy, Elsevier, vol. 38(7), pages 3309-3319, July.
    24. Brand, Bernhard & Zingerle, Jonas, 2010. "The renewable energy targets of the Maghreb countries: Impact on electricity supply and conventional power markets," EWI Working Papers 2010-2, Energiewirtschaftliches Institut an der Universitaet zu Koeln (EWI).
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