IDEAS home Printed from https://ideas.repec.org/r/eee/enepol/v30y2002i4p309-316.html
   My bibliography  Save this item

The economics of the combined cycle gas turbine--an experience curve analysis

Citations

Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
as


Cited by:

  1. Uyterlinde, Martine A. & Junginger, Martin & de Vries, Hage J. & Faaij, Andre P.C. & Turkenburg, Wim C., 2007. "Implications of technological learning on the prospects for renewable energy technologies in Europe," Energy Policy, Elsevier, vol. 35(8), pages 4072-4087, August.
  2. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
  3. Santhakumar, Srinivasan & Smart, Gavin & Noonan, Miriam & Meerman, Hans & Faaij, André, 2022. "Technological progress observed for fixed-bottom offshore wind in the EU and UK," Technological Forecasting and Social Change, Elsevier, vol. 182(C).
  4. Junginger, M. & Faaij, A. & Turkenburg, W. C., 2005. "Global experience curves for wind farms," Energy Policy, Elsevier, vol. 33(2), pages 133-150, January.
  5. Alessandro Fiorini & Antonio Sileo, 2013. "Infrastructural equip ment and regulati on. Key interv entions for sustaining security and development of the Italian natural gas market," ECONOMICS AND POLICY OF ENERGY AND THE ENVIRONMENT, FrancoAngeli Editore, vol. 2013(1), pages 23-40.
  6. Farmer, J. Doyne & Lafond, François, 2016. "How predictable is technological progress?," Research Policy, Elsevier, vol. 45(3), pages 647-665.
  7. Lafond, François & Bailey, Aimee Gotway & Bakker, Jan David & Rebois, Dylan & Zadourian, Rubina & McSharry, Patrick & Farmer, J. Doyne, 2018. "How well do experience curves predict technological progress? A method for making distributional forecasts," Technological Forecasting and Social Change, Elsevier, vol. 128(C), pages 104-117.
  8. Pettersson, Fredrik & Söderholm, Patrik, 2009. "The diffusion of renewable electricity in the presence of climate policy and technology learning: The case of Sweden," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(8), pages 2031-2040, October.
  9. Barreto, Leonardo & Kypreos, Socrates, 2004. "Emissions trading and technology deployment in an energy-systems "bottom-up" model with technology learning," European Journal of Operational Research, Elsevier, vol. 158(1), pages 243-261, October.
  10. Comello, Stephen & Reichelstein, Stefan, 2014. "Incentives for early adoption of carbon capture technology," Energy Policy, Elsevier, vol. 74(C), pages 579-588.
  11. Majidpour, Mehdi, 2012. "Heavy duty gas turbines in Iran, India and China: Do national energy policies drive the industries?," Energy Policy, Elsevier, vol. 41(C), pages 723-732.
  12. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
  13. Samadi, Sascha, 2018. "The experience curve theory and its application in the field of electricity generation technologies – A literature review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2346-2364.
  14. Phadke, Amol, 2009. "How many Enrons? Mark-ups in the stated capital cost of independent power producers' (IPPs') power projects in developing countries," Energy, Elsevier, vol. 34(11), pages 1917-1924.
  15. Chen, Youliang & Huang, Xiaoguang & Li, Wei & Fan, Rong & Zi, Pingyang & Wang, Xin, 2023. "Application of deep learning modelling of the optimal operation conditions of auxiliary equipment of combined cycle gas turbine power station," Energy, Elsevier, vol. 285(C).
  16. Li, Sheng & Zhang, Xiaosong & Gao, Lin & Jin, Hongguang, 2012. "Learning rates and future cost curves for fossil fuel energy systems with CO2 capture: Methodology and case studies," Applied Energy, Elsevier, vol. 93(C), pages 348-356.
  17. Wogrin, Sonja & Galbally, David & Ramos, Andrés, 2016. "CCGT unit commitment model with first-principle formulation of cycling costs due to fatigue damage," Energy, Elsevier, vol. 113(C), pages 227-247.
  18. Söderholm, Patrik & Sundqvist, Thomas, 2007. "Empirical challenges in the use of learning curves for assessing the economic prospects of renewable energy technologies," Renewable Energy, Elsevier, vol. 32(15), pages 2559-2578.
  19. Blanco, María Isabel, 2009. "The economics of wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 13(6-7), pages 1372-1382, August.
  20. Lee, Shun-Chung & Shih, Li-Hsing, 2010. "Renewable energy policy evaluation using real option model -- The case of Taiwan," Energy Economics, Elsevier, vol. 32(Supplemen), pages 67-78, September.
  21. Kypreos, Socrates, 2005. "Modeling experience curves in MERGE (model for evaluating regional and global effects)," Energy, Elsevier, vol. 30(14), pages 2721-2737.
  22. Santhakumar, Srinivasan & Meerman, Hans & Faaij, André, 2021. "Improving the analytical framework for quantifying technological progress in energy technologies," Renewable and Sustainable Energy Reviews, Elsevier, vol. 145(C).
  23. 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.
  24. Guittet, Mélanie & Capezzali, Massimiliano & Gaudard, Ludovic & Romerio, Franco & Vuille, François & Avellan, François, 2016. "Study of the drivers and asset management of pumped-storage power plants historical and geographical perspective," Energy, Elsevier, vol. 111(C), pages 560-579.
  25. 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.
  26. Roques, Fabien A., 2008. "Technology choices for new entrants in liberalized markets: The value of operating flexibility and contractual arrangements," Utilities Policy, Elsevier, vol. 16(4), pages 245-253, December.
  27. van den Broek, Machteld & Berghout, Niels & Rubin, Edward S., 2015. "The potential of renewables versus natural gas with CO2 capture and storage for power generation under CO2 constraints," Renewable and Sustainable Energy Reviews, Elsevier, vol. 49(C), pages 1296-1322.
  28. Pettersson, Fredrik, 2007. "Carbon pricing and the diffusion of renewable power generation in Eastern Europe: A linear programming approach," Energy Policy, Elsevier, vol. 35(4), pages 2412-2425, April.
  29. Nelson, Sarah & Allwood, Julian M., 2021. "The technological and social timelines of climate mitigation: Lessons from 12 past transitions," Energy Policy, Elsevier, vol. 152(C).
  30. Rubin, Edward S. & Azevedo, Inês M.L. & Jaramillo, Paulina & Yeh, Sonia, 2015. "A review of learning rates for electricity supply technologies," Energy Policy, Elsevier, vol. 86(C), pages 198-218.
  31. Chade Ricosti, Juliana F. & Sauer, Ildo L., 2013. "An assessment of wind power prospects in the Brazilian hydrothermal system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 742-753.
  32. Watson, Jim & Kern, Florian & Markusson, Nils, 2014. "Resolving or managing uncertainties for carbon capture and storage: Lessons from historical analogues," Technological Forecasting and Social Change, Elsevier, vol. 81(C), pages 192-204.
  33. Junginger, Martin & de Visser, Erika & Hjort-Gregersen, Kurt & Koornneef, Joris & Raven, Rob & Faaij, Andre & Turkenburg, Wim, 2006. "Technological learning in bioenergy systems," Energy Policy, Elsevier, vol. 34(18), pages 4024-4041, December.
  34. Nandini Das & Shyamasree Dasgupta & Joyashree Roy & Oluf Langhelle & Mohsen Assadi, 2021. "Emission Mitigation and Energy Security Trade-Off: Role of Natural Gas in the Indian Power Sector," Energies, MDPI, vol. 14(13), pages 1-17, June.
  35. Olsina, Fernando & Garces, Francisco & Haubrich, H.-J., 2006. "Modeling long-term dynamics of electricity markets," Energy Policy, Elsevier, vol. 34(12), pages 1411-1433, August.
  36. 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.
  37. Martin Junginger & Wilfried van Sark & André Faaij (ed.), 2010. "Technological Learning in the Energy Sector," Books, Edward Elgar Publishing, number 13741.
  38. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
  39. Rubin, Edward S & Taylor, Margaret R & Yeh, Sonia & Hounshell, David A, 2004. "Learning curves for environmental technology and their importance for climate policy analysis," Energy, Elsevier, vol. 29(9), pages 1551-1559.
  40. Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng, 2022. "Effects of learning curve models on onshore wind and solar PV cost developments in the USA," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.