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Use and limitations of learning curves for energy technology policy: A component-learning hypothesis

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  1. 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.
  2. van Velzen, Arjan & Annema, Jan Anne & van de Kaa, Geerten & van Wee, Bert, 2019. "Proposing a more comprehensive future total cost of ownership estimation framework for electric vehicles," Energy Policy, Elsevier, vol. 129(C), pages 1034-1046.
  3. Wang, Yongli & Gao, Mingchen & Wang, Jingyan & Wang, Shuo & Liu, Yang & Zhu, Jinrong & Tan, Zhongfu, 2021. "Measurement and key influencing factors of the economic benefits for China’s photovoltaic power generation: A LCOE-based hybrid model," Renewable Energy, Elsevier, vol. 169(C), pages 935-952.
  4. Wilson, Charlie, 2012. "Up-scaling, formative phases, and learning in the historical diffusion of energy technologies," Energy Policy, Elsevier, vol. 50(C), pages 81-94.
  5. Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
  6. Lindman, Åsa & Söderholm, Patrik, 2012. "Wind power learning rates: A conceptual review and meta-analysis," Energy Economics, Elsevier, vol. 34(3), pages 754-761.
  7. 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).
  8. Narbel, Patrick André & Hansen, Jan Petter, 2014. "Estimating the cost of future global energy supply," Renewable and Sustainable Energy Reviews, Elsevier, vol. 34(C), pages 91-97.
  9. Arnaud de La Tour & Matthieu Glachant & Yann Ménière, 2013. "What cost for photovoltaic modules in 2020? Lessons from experience curve models," Working Papers hal-00805668, HAL.
  10. Heuberger, Clara F. & Rubin, Edward S. & Staffell, Iain & Shah, Nilay & Mac Dowell, Niall, 2017. "Power capacity expansion planning considering endogenous technology cost learning," Applied Energy, Elsevier, vol. 204(C), pages 831-845.
  11. Beliën, Jeroen & De Boeck, Liesje & Colpaert, Jan & Cooman, Gert, 2013. "The best time to invest in photovoltaic panels in Flanders," Renewable Energy, Elsevier, vol. 50(C), pages 348-358.
  12. Marc Baudry & Clément Bonnet, 2016. "Demand pull isntruments and the development of wind power in Europe: A counter-factual analysis," Working Papers 1607, Chaire Economie du climat.
  13. Osorio, Andrés F. & Arias-Gaviria, Jessica & Devis-Morales, Andrea & Acevedo, Diego & Velasquez, Héctor Iván & Arango-Aramburo, Santiago, 2016. "Beyond electricity: The potential of ocean thermal energy and ocean technology ecoparks in small tropical islands," Energy Policy, Elsevier, vol. 98(C), pages 713-724.
  14. Ang Yang & Xiangyu Meng & He He & Liang Wang & Jing Gao, 2022. "Towards Optimized ARMGs’ Low-Carbon Transition Investment Decision Based on Real Options," Energies, MDPI, vol. 15(14), pages 1-16, July.
  15. Mainali, Brijesh & Silveira, Semida, 2013. "Alternative pathways for providing access to electricity in developing countries," Renewable Energy, Elsevier, vol. 57(C), pages 299-310.
  16. Arias-Gaviria, Jessica & Carvajal-Quintero, Sandra Ximena & Arango-Aramburo, Santiago, 2019. "Understanding dynamics and policy for renewable energy diffusion in Colombia," Renewable Energy, Elsevier, vol. 139(C), pages 1111-1119.
  17. Giraudet, Louis-Gaëtan & Guivarch, Céline & Quirion, Philippe, 2012. "Exploring the potential for energy conservation in French households through hybrid modeling," Energy Economics, Elsevier, vol. 34(2), pages 426-445.
  18. Tadeusz Skoczkowski & Sławomir Bielecki & Joanna Wojtyńska, 2019. "Long-Term Projection of Renewable Energy Technology Diffusion," Energies, MDPI, vol. 12(22), pages 1-24, November.
  19. Karali, Nihan & Park, Won Young & McNeil, Michael, 2017. "Modeling technological change and its impact on energy savings in the U.S. iron and steel sector," Applied Energy, Elsevier, vol. 202(C), pages 447-458.
  20. de La Tour, Arnaud & Glachant, Matthieu & Ménière, Yann, 2013. "Predicting the costs of photovoltaic solar modules in 2020 using experience curve models," Energy, Elsevier, vol. 62(C), pages 341-348.
  21. Hernandez-Negron, Christian G. & Baker, Erin & Goldstein, Anna P., 2023. "A hypothesis for experience curves of related technologies with an application to wind energy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 184(C).
  22. Lane, Blake & Kinnon, Michael Mac & Shaffer, Brendan & Samuelsen, Scott, 2022. "Deployment planning tool for environmentally sensitive heavy-duty vehicles and fueling infrastructure," Energy Policy, Elsevier, vol. 171(C).
  23. Kim, Seunghyok & Koo, Jamin & Lee, Chang Jun & Yoon, En Sup, 2012. "Optimization of Korean energy planning for sustainability considering uncertainties in learning rates and external factors," Energy, Elsevier, vol. 44(1), pages 126-134.
  24. Svetlana Revinova & Inna Lazanyuk & Svetlana Ratner & Konstantin Gomonov, 2023. "Forecasting Development of Green Hydrogen Production Technologies Using Component-Based Learning Curves," Energies, MDPI, vol. 16(11), pages 1-19, May.
  25. Nicodemus, Julia Haltiwanger, 2018. "Technological learning and the future of solar H2: A component learning comparison of solar thermochemical cycles and electrolysis with solar PV," Energy Policy, Elsevier, vol. 120(C), pages 100-109.
  26. Smith, Sarah Josephine & Wei, Max & Sohn, Michael D., 2016. "A retrospective analysis of compact fluorescent lamp experience curves and their correlations to deployment programs," Energy Policy, Elsevier, vol. 98(C), pages 505-512.
  27. Clas‐Otto Wene, 2016. "Future energy system development depends on past learning opportunities," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 5(1), pages 16-32, January.
  28. Alemzero, David & Acheampong, Theophilus & Huaping, Sun, 2021. "Prospects of wind energy deployment in Africa: Technical and economic analysis," Renewable Energy, Elsevier, vol. 179(C), pages 652-666.
  29. Thomassen, Gwenny & Van Passel, Steven & Dewulf, Jo, 2020. "A review on learning effects in prospective technology assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
  30. Kërçi, Taulant & Tzounas, Georgios & Milano, Federico, 2022. "A dynamic behavioral model of the long-term development of solar photovoltaic generation driven by feed-in tariffs," Energy, Elsevier, vol. 256(C).
  31. Desroches, Louis-Benoit & Garbesi, Karina & Kantner, Colleen & Van Buskirk, Robert & Yang, Hung-Chia, 2013. "Incorporating experience curves in appliance standards analysis," Energy Policy, Elsevier, vol. 52(C), pages 402-416.
  32. Yu, C.F. & van Sark, W.G.J.H.M. & Alsema, E.A., 2011. "Unraveling the photovoltaic technology learning curve by incorporation of input price changes and scale effects," Renewable and Sustainable Energy Reviews, Elsevier, vol. 15(1), pages 324-337, January.
  33. van der Zwaan, B.C.C. & Schoots, K. & Rivera-Tinoco, R. & Verbong, G.P.J., 2011. "The cost of pipelining climate change mitigation: An overview of the economics of CH4, CO2 and H2 transportation," Applied Energy, Elsevier, vol. 88(11), pages 3821-3831.
  34. Ayompe, L.M. & Duffy, A. & McCormack, S.J. & Conlon, M., 2010. "Projected costs of a grid-connected domestic PV system under different scenarios in Ireland, using measured data from a trial installation," Energy Policy, Elsevier, vol. 38(7), pages 3731-3743, July.
  35. Candelise, Chiara & Winskel, Mark & Gross, Robert J.K., 2013. "The dynamics of solar PV costs and prices as a challenge for technology forecasting," Renewable and Sustainable Energy Reviews, Elsevier, vol. 26(C), pages 96-107.
  36. Marc Baudry & Clément Bonnet, 2019. "Demand-Pull Instruments and the Development of Wind Power in Europe: A Counterfactual Analysis," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 73(2), pages 385-429, June.
  37. Audrey Laude & Christian Jonen, 2011. "Biomass and CCS: The influence of the learning effect," Working Papers halshs-00829779, HAL.
  38. Bolinger, Mark & Wiser, Ryan, 2012. "Understanding wind turbine price trends in the U.S. over the past decade," Energy Policy, Elsevier, vol. 42(C), pages 628-641.
  39. Zheng, Cheng & Kammen, Daniel M., 2014. "An innovation-focused roadmap for a sustainable global photovoltaic industry," Energy Policy, Elsevier, vol. 67(C), pages 159-169.
  40. Tavoni, Massimo & van der Zwaan, Bob, 2009. "Nuclear versus Coal plus CCS: A Comparison of Two Competitive Base-load Climate Control Options," Sustainable Development Papers 55327, Fondazione Eni Enrico Mattei (FEEM).
  41. Hsu, Chiung-Wen, 2012. "Using a system dynamics model to assess the effects of capital subsidies and feed-in tariffs on solar PV installations," Applied Energy, Elsevier, vol. 100(C), pages 205-217.
  42. 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.
  43. Christian JONEN & Audrey LAUDE, 2011. "Biomasse and CCS: The Influence of the Learning Effect," LEO Working Papers / DR LEO 273, Orleans Economics Laboratory / Laboratoire d'Economie d'Orleans (LEO), University of Orleans.
  44. Hayward, Jennifer A. & Graham, Paul W., 2013. "A global and local endogenous experience curve model for projecting future uptake and cost of electricity generation technologies," Energy Economics, Elsevier, vol. 40(C), pages 537-548.
  45. Li, Jin & Hu, Shanying, 2017. "History and future of the coal and coal chemical industry in China," Resources, Conservation & Recycling, Elsevier, vol. 124(C), pages 13-24.
  46. Bergesen, Joseph D. & Suh, Sangwon, 2016. "A framework for technological learning in the supply chain: A case study on CdTe photovoltaics," Applied Energy, Elsevier, vol. 169(C), pages 721-728.
  47. Vasilakou, Konstantina & Nimmegeers, Philippe & Thomassen, Gwenny & Billen, Pieter & Van Passel, Steven, 2023. "Assessing the future of second-generation bioethanol by 2030 – A techno-economic assessment integrating technology learning curves," Applied Energy, Elsevier, vol. 344(C).
  48. Criqui, P. & Mima, S. & Menanteau, P. & Kitous, A., 2015. "Mitigation strategies and energy technology learning: An assessment with the POLES model," Technological Forecasting and Social Change, Elsevier, vol. 90(PA), pages 119-136.
  49. Olatayo, Kunle Ibukun & Wichers, J. Harry & Stoker, Piet W., 2020. "The advanced and moderate-growth development paths for the viability and future growth of small wind energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 117(C).
  50. de Wit, Marc & Junginger, Martin & Faaij, André, 2013. "Learning in dedicated wood production systems: Past trends, future outlook and implications for bioenergy," Renewable and Sustainable Energy Reviews, Elsevier, vol. 19(C), pages 417-432.
  51. Upstill, Garrett & Hall, Peter, 2018. "Estimating the learning rate of a technology with multiple variants: The case of carbon storage," Energy Policy, Elsevier, vol. 121(C), pages 498-505.
  52. Laude, Audrey & Jonen, Christian, 2013. "Biomass and CCS: The influence of technical change," Energy Policy, Elsevier, vol. 60(C), pages 916-924.
  53. Strupeit, Lars, 2017. "An innovation system perspective on the drivers of soft cost reduction for photovoltaic deployment: The case of Germany," Renewable and Sustainable Energy Reviews, Elsevier, vol. 77(C), pages 273-286.
  54. Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
  55. 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.
  56. Arias-Gaviria, Jessica & Larsen, Erik R. & Arango-Aramburo, Santiago, 2018. "Understanding the future of Seawater Air Conditioning in the Caribbean: A simulation approach," Utilities Policy, Elsevier, vol. 53(C), pages 73-83.
  57. Reed, Jeffrey & Dailey, Emily & Shaffer, Brendan & Lane, Blake & Flores, Robert & Fong, Amber & Samuelsen, Scott, 2023. "Potential evolution of the renewable hydrogen sector using California as a reference market," Applied Energy, Elsevier, vol. 331(C).
  58. Elia, A. & Taylor, M. & Ó Gallachóir, B. & Rogan, F., 2020. "Wind turbine cost reduction: A detailed bottom-up analysis of innovation drivers," Energy Policy, Elsevier, vol. 147(C).
  59. Gan, Peck Yean & Li, ZhiDong, 2015. "Quantitative study on long term global solar photovoltaic market," Renewable and Sustainable Energy Reviews, Elsevier, vol. 46(C), pages 88-99.
  60. Chen, Siyuan & Liu, Jiangfeng & Zhang, Qi & Teng, Fei & McLellan, Benjamin C., 2022. "A critical review on deployment planning and risk analysis of carbon capture, utilization, and storage (CCUS) toward carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
  61. Schoots, K. & Kramer, G.J. & van der Zwaan, B.C.C., 2010. "Technology learning for fuel cells: An assessment of past and potential cost reductions," Energy Policy, Elsevier, vol. 38(6), pages 2887-2897, June.
  62. Matthias Buyle & Amaryllis Audenaert & Pieter Billen & Katrien Boonen & Steven Van Passel, 2019. "The Future of Ex-Ante LCA? Lessons Learned and Practical Recommendations," Sustainability, MDPI, vol. 11(19), pages 1-24, October.
  63. Ioannis E. Kosmadakis & Costas Elmasides & Dimitrios Eleftheriou & Konstantinos P. Tsagarakis, 2019. "A Techno-Economic Analysis of a PV-Battery System in Greece," Energies, MDPI, vol. 12(7), pages 1-14, April.
  64. Shayegh, Soheil & Sanchez, Daniel L. & Caldeira, Ken, 2017. "Evaluating relative benefits of different types of R&D for clean energy technologies," Energy Policy, Elsevier, vol. 107(C), pages 532-538.
  65. Aldersey-Williams, John & Broadbent, Ian D. & Strachan, Peter A., 2019. "Better estimates of LCOE from audited accounts – A new methodology with examples from United Kingdom offshore wind and CCGT," Energy Policy, Elsevier, vol. 128(C), pages 25-35.
  66. Narbel, Patrick A. & Hansen, Jan Petter, 2014. "Estimating the cost of future global energy supply," Discussion Papers 2014/14, Norwegian School of Economics, Department of Business and Management Science.
  67. Bossink, Bart, 2020. "Learning strategies in sustainable energy demonstration projects: What organizations learn from sustainable energy demonstrations," Renewable and Sustainable Energy Reviews, Elsevier, vol. 131(C).
  68. van der Zwaan, Bob & Rivera-Tinoco, Rodrigo & Lensink, Sander & van den Oosterkamp, Paul, 2012. "Cost reductions for offshore wind power: Exploring the balance between scaling, learning and R&D," Renewable Energy, Elsevier, vol. 41(C), pages 389-393.
  69. Miao, Huiying & Yu, Yadong & Kharrazi, Ali & Ma, Tieju, 2023. "Multi-criteria decision analysis for the planning of island microgrid system: A case study of Yongxing island, China," Energy, Elsevier, vol. 284(C).
  70. Siderius, Hans-Paul, 2013. "The role of experience curves for setting MEPS for appliances," Energy Policy, Elsevier, vol. 59(C), pages 762-772.
  71. Zakerinia, Saleh, 2018. "Understanding the Role of Transportation in Meeting California’s Greenhouse Gas Emissions Reduction Target: A Focus on Technology Forcing Policies, Interactions with the Electric Sector and Mitigation," Institute of Transportation Studies, Working Paper Series qt0r69m651, Institute of Transportation Studies, UC Davis.
  72. Yao, Xilong & Liu, Yang & Qu, Shiyou, 2015. "When will wind energy achieve grid parity in China? – Connecting technological learning and climate finance," Applied Energy, Elsevier, vol. 160(C), pages 697-704.
  73. Paulo Henrique de Mello Santana, 2015. "Cost-effectiveness as Energy Policy Mechanisms: The Paradox of Technology-neutral and Technology-specific Policies in the Short and Long Term," Working Papers Working Paper 2015-02, Regional Research Institute, West Virginia University.
  74. Rochedo, Pedro R.R. & Szklo, Alexandre, 2013. "Designing learning curves for carbon capture based on chemical absorption according to the minimum work of separation," Applied Energy, Elsevier, vol. 108(C), pages 383-391.
  75. Strupeit, Lars & Neij, Lena, 2017. "Cost dynamics in the deployment of photovoltaics: Insights from the German market for building-sited systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 69(C), pages 948-960.
  76. Felix Groba & Barbara Breitschopf, 2013. "Impact of Renewable Energy Policy and Use on Innovation: A Literature Review," Discussion Papers of DIW Berlin 1318, DIW Berlin, German Institute for Economic Research.
  77. Liu, Jiangfeng & Zhang, Qi & Li, Hailong & Chen, Siyuan & Teng, Fei, 2022. "Investment decision on carbon capture and utilization (CCU) technologies—A real option model based on technology learning effect," Applied Energy, Elsevier, vol. 322(C).
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  80. Grafström, Jonas & Poudineh, Rahmat, 2021. "A review of problems associated with learning curves for solar and wind power technologies," Ratio Working Papers 347, The Ratio Institute.
  81. M. Jaber & Z. Givi, 2015. "Imperfect production process with learning and forgetting effects," Computational Management Science, Springer, vol. 12(1), pages 129-152, January.
  82. Yeh, Sonia & Rubin, Edward S., 2012. "A review of uncertainties in technology experience curves," Energy Economics, Elsevier, vol. 34(3), pages 762-771.
  83. Tsagarakis, Konstantinos P., 2020. "Shallow geothermal energy under the microscope: Social, economic, and institutional aspects," Renewable Energy, Elsevier, vol. 147(P2), pages 2801-2808.
  84. Hernández-Moro, J. & Martínez-Duart, J.M., 2013. "Analytical model for solar PV and CSP electricity costs: Present LCOE values and their future evolution," Renewable and Sustainable Energy Reviews, Elsevier, vol. 20(C), pages 119-132.
  85. de Mello Santana, Paulo Henrique, 2016. "Cost-effectiveness as energy policy mechanisms: The paradox of technology-neutral and technology-specific policies in the short and long term," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 1216-1222.
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  87. Fukui, Rokuhei & Greenfield, Carl & Pogue, Katie & van der Zwaan, Bob, 2017. "Experience curve for natural gas production by hydraulic fracturing," Energy Policy, Elsevier, vol. 105(C), pages 263-268.
  88. 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).
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  90. Wei, Max & Smith, Sarah Josephine & Sohn, Michael D., 2017. "Non-constant learning rates in retrospective experience curve analyses and their correlation to deployment programs," Energy Policy, Elsevier, vol. 107(C), pages 356-369.
  91. Benson, Christopher L. & Magee, Christopher L., 2014. "On improvement rates for renewable energy technologies: Solar PV, wind turbines, capacitors, and batteries," Renewable Energy, Elsevier, vol. 68(C), pages 745-751.
  92. Arias-Gaviria, Jessica & van der Zwaan, Bob & Kober, Tom & Arango-Aramburo, Santiago, 2017. "The prospects for Small Hydropower in Colombia," Renewable Energy, Elsevier, vol. 107(C), pages 204-214.
  93. Duffy, Aidan & Hand, Maureen & Wiser, Ryan & Lantz, Eric & Dalla Riva, Alberto & Berkhout, Volker & Stenkvist, Maria & Weir, David & Lacal-Arántegui, Roberto, 2020. "Land-based wind energy cost trends in Germany, Denmark, Ireland, Norway, Sweden and the United States," Applied Energy, Elsevier, vol. 277(C).
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