IE interfaces (산업공학)

Korean Institute of Industrial Engineers (대한산업공학회)
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Forecasting the Grid Parity of Solar Photovoltaic Energy Using Two Factor Learning Curve Model

2요인 학습곡선 모형을 이용한 한국의 태양광 발전 그리드패리티 예측

  • Park, Sung-Joon (Industrial and Management Systems Engineering, Kyung Hee University) ;
  • Lee, Deok Joo (Industrial and Management Systems Engineering, Kyung Hee University) ;
  • Kim, Kyung-Taek (Industrial and Management Systems Engineering, Kyung Hee University)
  • 박성준 (경희대학교 산업경영공학) ;
  • 이덕주 (경희대학교 산업경영공학) ;
  • 김경택 (경희대학교 산업경영공학)
  • Received : 2011.12.09
  • Accepted : 2012.07.30
  • Published : 2012.12.01
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Abstract

Solar PV(photovoltaic) is paid great attention to as a possible renewable energy source to overcome recent global energy crisis. However to be a viable alternative energy source compared with fossil fuel, its market competitiveness should be attained. Grid parity is one of effective measure of market competitiveness of renewable energy. In this paper, we forecast the grid parity timing of solar PV energy in Korea using two factor learning curve model. Two factors considered in the present model are production capacity and technological improvement. As a result, it is forecasted that the grid parity will be achieved in 2019 in Korea.

Keywords

References

  1. Argote, L. and Epple, D. (1990), Learning Curves in manufacturing, Science, 247, 920-924. https://doi.org/10.1126/science.247.4945.920
  2. Arrow, K. J. (1962), The economic implications of learning by doing, The Review of Economic Studies, 29, 155-173. https://doi.org/10.2307/2295952
  3. Bhandari, R. and Stadlera, I. (2009), Grid Parity Analysis of Solar Photovoltaic Systems in Germany using Experience Curves, Solar Energy, 83(9), 1634- 1644. https://doi.org/10.1016/j.solener.2009.06.001
  4. Chang, H. (2007), An Evaluation of Renewable Energy Technology Policies in Korea : Two Factor Learning Curve and Innovation System Approaches, Ph.D. diss., Ajou University.
  5. Chang, H. and Choi, K. (2006), A Theoretical Review on the Experience Curve for Energy Technology, The Korea Socity for Energy Engineering, Journal of Energy Engineering, 15(4), 209-228.
  6. Duke, R. D. (2002), Clean Energy Technology Buydowns : Econmic Theory, Analytic Tools, and the Photovoltaics Case, Ph.D. diss., Princeton University.
  7. Ibenholt, K. (2002), Explaining learning curves for wind power, Energy Policy, 30(13), 1181-1189. https://doi.org/10.1016/S0301-4215(02)00014-9
  8. Hong, S. Hong, S., and Ahn, D. (1991), A Study of Inter-industry R&D investment flows and Direct/indirect productivity, STEPI, Policy Research, 91-14.
  9. Jamasb, T. (2007), Technical change theory and learning curves : Patterns of progress in electricity generation technologies, The Energy Journal, 28(3), 52-72.
  10. Junginger, M., Faaij, A., and Turkenburg, W. C. (2005), Global experience curves for wind farms, Energy Policy, 33(2), 133-150. https://doi.org/10.1016/S0301-4215(03)00205-2
  11. Kahouli-Brahmi, S. (2008), Technological Learning in Energy-environment-economy Modelling : A survey, Energy Policy, 36(1), 138-162. https://doi.org/10.1016/j.enpol.2007.09.001
  12. Kamp, L. M, Ruud, E. H. M. S., and Cornelis, D. (2004), Andriesse Notions on learning applied to wind turbine development in the Netherlands and Denmark, Energy Policy, 32(14), 1625-1637. https://doi.org/10.1016/S0301-4215(03)00134-4
  13. Kang, H. (2007), The Emerging PV Industry, Samsung Economic Research Institute, CEO Information, 616.
  14. Kim, D. (2005), Development of PV Technology and Market Trends, Journal of the Korean Solar Energy Society, 4(3), 3-7.
  15. Klaassen, G., Miketa, A., Larsen, K., and Sundqxist, T. (2005), The impact of R&D on innovation for wind energy in Denmark, Germany and the United Kingdom, Ecological Economics, 54(2), 227-240, https://doi.org/10.1016/j.ecolecon.2005.01.008
  16. Kobos, P. H., Erickson, J. E., and Drennen, T. E. (2006), Technological Learning and Renewable Energy Costs : Implications for US Renewable Energy Policy, Energy Policy, 34(13), 1645-1658. https://doi.org/10.1016/j.enpol.2004.12.008
  17. Korea Power Exchange (2011), Electricity Market Statistics 2010, Korea.
  18. Kouvaritakis, N., Soria, A., and Isoard, S. (2000), Modelling Energy Technology Dynamics : Methodology for Adaptive Expectations Models with Learning by Doing and Learning by Searching, International Journal of Global energy, 14, 104-115.
  19. Lee, M. (2008), Global Trends and Implications for the PV Industry, Korea Development Bank Journal, 631, 65-98.
  20. Lee, M. (2009), Environmental Change and Eesponse of the Solar Cell Industry, Korea Energy Economics Institute, Energy Focus, 6(4), 35-62.
  21. Ministry of Knowledge Economy, Korea Energy Management Corporation New and Renewable Energy Center (2008), New and Renewable Energy White Paper 2008, Korea.
  22. Ministry of Knowledge Economy, Korea Energy Management Corporation New and Renewable Energy Center (2010), New and Renewable Energy White Paper, Korea.
  23. Neij, L. (1997), Use of Experience Curves to Analyse the Prospects for Diffusion and Adoption of Renewable Energy Technology, Energy Policy, 23(13), 1099- 1107.
  24. Neij, L. (1999), Cost Dynamics of Wind Power, Energy, 24(5), 375-389. https://doi.org/10.1016/S0360-5442(99)00010-9
  25. Nemet, G. F. (2005), Beyond the Learning Curve : factors influencing cost reductions in photovoltaics, Energy Policy, 34(17), 3218-3232.
  26. Papineau, M. (2006), An Economic Perspective on Experience Curves and Dynamic Economies in Renewable Energy Technologies, Energy Policy, 34(4), 422- 432. https://doi.org/10.1016/j.enpol.2004.06.008
  27. Park, M., Lee, J., Lee, Y., and Kim, J. (2007), A Learning Curve Model, Applied to Cost Analysis of Developing Renewable Energy in Korea, The Korea Socity for Energy Engineering Fall Conference, 169-174.
  28. Rout, U. K., Blesl, M., Fahl, U., Remme, U., and Voss. A. (2009) ,Uncertainty in the learning rates of energy technologies : An experiments in a global multi- regional energy system modes, Energy Policy, 37(11), 4927-4942. https://doi.org/10.1016/j.enpol.2009.06.056
  29. Schaeffer, G. J., Seebregts, A. J., Beurskens, L. W. M., de Moor, H. H. C., Alsema, E. A., Sark, W., Durstewicz, M., Perrin, M., Boulanger, P., Laukamp, H., and Zuccaro, C. (2004), Learning from the Sun; Analysis of the use of experience curves for energy policy purposes: the case of photovoltaic power, Final Report of the PHOTEX Project, ECN-C-04-035, Petten, The Netherlands, Energy Research Center of the Netherlands.
  30. Schmitz, J. (2008), Solar Photovoltaic Electricity to hit the Power Grid?, The Second Law of Life, http://secondlawoflife.wordpress.com/2008/02.
  31. Shin, Y., Jung, R., Ko, J., and Jeon, J. (2008), Present Situation and Utilization- rate of a Mass Solar-powerplant in Korea, The Korean Institute of Electical Engineer Fall Conference.
  32. van der Zwaan, B. and Rabl, A. (2004), The learning potential of photovoltaics : implications for energy policy, Energy Policy, 32(13), 1545-1554. https://doi.org/10.1016/S0301-4215(03)00126-5
  33. van der Zwaan, B. and Rabl, A. (2003), Prospects for PV : a learning curve analysis, Solar Energy, 74(1), 19-31. https://doi.org/10.1016/S0038-092X(03)00112-9
  34. Varian, H. (1992), Microeconomic Analysis, New York : W. W. Norton and Company.
  35. Wene, C. O. (2000), Experience Curves for Energy Technology Policy, IEA study book, Paris, France, 2000.
  36. Wright, T. P. (1936), Factors affection the cost of airplanes, Journal of the Aeronautical Science, 3.
  37. Yu, C. F., van Sark, W. G. J. H. M., and Alsema, E. A. (2011), Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects, Renewable and Sustainable Energy, 15(1), 324-337. https://doi.org/10.1016/j.rser.2010.09.001
  38. Yu, J. (2007), Analysis on the Competitiveness of New and Renewable Energy in Korea's Power Market under Uncertainty of Technical Change, Ph.D. diss., Ajou University.

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