A review on learning effects in prospective technology assessment
Author
Abstract
Suggested Citation
DOI: 10.1016/j.rser.2020.109937
Download full text from publisher
As the access to this document is restricted, you may want to search for a different version of it.
References listed on IDEAS
- Atse Louwen & Wilfried G. J. H. M. van Sark & André P. C. Faaij & Ruud E. I. Schropp, 2016. "Re-assessment of net energy production and greenhouse gas emissions avoidance after 40 years of photovoltaics development," Nature Communications, Nature, vol. 7(1), pages 1-9, December.
- Esmaieli, M. & Ahmadian, M., 2018. "The effect of research and development incentive on wind power investment, a system dynamics approach," Renewable Energy, Elsevier, vol. 126(C), pages 765-773.
- Glock, C. H. & Grosse, E. H. & Jaber, M. Y. & Smunt, T. L., 2019. "Applications of learning curves in production and operations management: A systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 115512, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Shih, Yi-Hsuan & Tseng, Chao-Heng, 2014. "Cost-benefit analysis of sustainable energy development using life-cycle co-benefits assessment and the system dynamics approach," Applied Energy, Elsevier, vol. 119(C), pages 57-66.
- Hayashi, Daisuke & Huenteler, Joern & Lewis, Joanna I., 2018. "Gone with the wind: A learning curve analysis of China's wind power industry," Energy Policy, Elsevier, vol. 120(C), pages 38-51.
- Ruffini, Eleonora & Wei, Max, 2018. "Future costs of fuel cell electric vehicles in California using a learning rate approach," Energy, Elsevier, vol. 150(C), pages 329-341.
- Matteson, Schuyler & Williams, Eric, 2015. "Residual learning rates in lead-acid batteries: Effects on emerging technologies," Energy Policy, Elsevier, vol. 85(C), pages 71-79.
- Gert Jan Kramer & Martin Haigh, 2009. "No quick switch to low-carbon energy," Nature, Nature, vol. 462(7273), pages 568-569, December.
- 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.
- 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.
- Amela Ajanovic, 2015. "The future of electric vehicles: prospects and impediments," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 4(6), pages 521-536, November.
- Williams, Eric & Hittinger, Eric & Carvalho, Rexon & Williams, Ryan, 2017. "Wind power costs expected to decrease due to technological progress," Energy Policy, Elsevier, vol. 106(C), pages 427-435.
- Kavlak, Goksin & McNerney, James & Trancik, Jessika E., 2018. "Evaluating the causes of cost reduction in photovoltaic modules," Energy Policy, Elsevier, vol. 123(C), pages 700-710.
- Shanjun Li & Junji Xiao & Yimin Liu, 2015. "The Price Evolution in China's Automobile Market," Journal of Economics & Management Strategy, Wiley Blackwell, vol. 24(4), pages 786-810, October.
- 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.
- Franc{c}ois Lafond & Aimee Gotway Bailey & Jan David Bakker & Dylan Rebois & Rubina Zadourian & Patrick McSharry & J. Doyne Farmer, 2017. "How well do experience curves predict technological progress? A method for making distributional forecasts," Papers 1703.05979, arXiv.org, revised Sep 2017.
- 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.
- Wei, Max & Smith, Sarah J. & Sohn, Michael D., 2017. "Experience curve development and cost reduction disaggregation for fuel cell markets in Japan and the US," Applied Energy, Elsevier, vol. 191(C), pages 346-357.
- Gazheli, Ardjan & van den Bergh, Jeroen, 2018. "Real options analysis of investment in solar vs. wind energy: Diversification strategies under uncertain prices and costs," Renewable and Sustainable Energy Reviews, Elsevier, vol. 82(P3), pages 2693-2704.
- Mo, Jianlei & Schleich, Joachim & Fan, Ying, 2018.
"Getting ready for future carbon abatement under uncertainty – Key factors driving investment with policy implications,"
Energy Economics, Elsevier, vol. 70(C), pages 453-464.
- Mo, Jianlei & Schleich, Joachim & Fan, Ying, 2018. "Getting ready for future carbon abatement under uncertainty – key factors driving investment with policy implications," LSE Research Online Documents on Economics 87193, London School of Economics and Political Science, LSE Library.
- Zhou, Li & Duan, Maosheng & Yu, Yadong & Zhang, Xiliang, 2018. "Learning rates and cost reduction potential of indirect coal-to-liquid technology coupled with CO2 capture," Energy, Elsevier, vol. 165(PB), pages 21-32.
- Millinger, M. & Ponitka, J. & Arendt, O. & Thrän, D., 2017. "Competitiveness of advanced and conventional biofuels: Results from least-cost modelling of biofuel competition in Germany," Energy Policy, Elsevier, vol. 107(C), pages 394-402.
- Köberle, Alexandre C. & Gernaat, David E.H.J. & van Vuuren, Detlef P., 2015. "Assessing current and future techno-economic potential of concentrated solar power and photovoltaic electricity generation," Energy, Elsevier, vol. 89(C), pages 739-756.
- Björn Nykvist & Måns Nilsson, 2015. "Rapidly falling costs of battery packs for electric vehicles," Nature Climate Change, Nature, vol. 5(4), pages 329-332, April.
- 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.
- Andrew Sudmant & Joel Millward-Hopkins & Sarah Colenbrander & Andy Gouldson, 2016. "Low carbon cities: is ambitious action affordable?," Climatic Change, Springer, vol. 138(3), pages 681-688, October.
- Lim, Jin Han & Dally, Bassam B. & Chinnici, Alfonso & Nathan, Graham J., 2017. "Techno-economic evaluation of modular hybrid concentrating solar power systems," Energy, Elsevier, vol. 129(C), pages 158-170.
- O. Schmidt & A. Hawkes & A. Gambhir & I. Staffell, 2017. "The future cost of electrical energy storage based on experience rates," Nature Energy, Nature, vol. 2(8), pages 1-8, August.
- Pillai, Unni, 2015. "Drivers of cost reduction in solar photovoltaics," Energy Economics, Elsevier, vol. 50(C), pages 286-293.
- Matteson, Schuyler & Williams, Eric, 2015. "Learning dependent subsidies for lithium-ion electric vehicle batteries," Technological Forecasting and Social Change, Elsevier, vol. 92(C), pages 322-331.
- Murphy, Helen T. & O’Connell, Deborah A. & Raison, R. John & Warden, Andrew C. & Booth, Trevor H. & Herr, Alexander & Braid, Andrew L. & Crawford, Debbie F. & Hayward, Jennifer A. & Jovanovic, Tom & M, 2015. "Biomass production for sustainable aviation fuels: A regional case study in Queensland," Renewable and Sustainable Energy Reviews, Elsevier, vol. 44(C), pages 738-750.
- Tooraj Jamasb, 2007.
"Technical Change Theory and Learning Curves: Patterns of Progress in Electricity Generation Technologies,"
The Energy Journal, , vol. 28(3), pages 51-72, July.
- Tooraj Jamasb, 2007. "Technical Change Theory and Learning Curves: Patterns of Progress in Electricity Generation Technologies," The Energy Journal, International Association for Energy Economics, vol. 0(Number 3), pages 51-72.
- Leibowicz, Benjamin D., 2015. "Growth and competition in renewable energy industries: Insights from an integrated assessment model with strategic firms," Energy Economics, Elsevier, vol. 52(PA), pages 13-25.
- Jong-Hyun Kim & Yong-Gil Lee, 2017. "Analyzing the Learning Path of US Shale Players by Using the Learning Curve Method," Sustainability, MDPI, vol. 9(12), pages 1-8, December.
- Ryan Wiser & Karen Jenni & Joachim Seel & Erin Baker & Maureen Hand & Eric Lantz & Aaron Smith, 2016. "Expert elicitation survey on future wind energy costs," Nature Energy, Nature, vol. 1(10), pages 1-8, October.
- 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.
- Chen, Yuche & Zhang, Yunteng & Fan, Yueyue & Hu, Kejia & Zhao, Jianyou, 2017. "A dynamic programming approach for modeling low-carbon fuel technology adoption considering learning-by-doing effect," Applied Energy, Elsevier, vol. 185(P1), pages 825-835.
- Maria Rosario Garzón Sampedro & Carlos Sanchez Gonzalez, 2016. "Spanish photovoltaic learning curve," International Journal of Low-Carbon Technologies, Oxford University Press, vol. 11(2), pages 177-183.
- 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.
- Beck, Marisa & Rivers, Nicholas & Wigle, Randall, 2018. "How do learning externalities influence the evaluation of Ontario's renewables support policies?," Energy Policy, Elsevier, vol. 117(C), pages 86-99.
- 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.
- Xiping Wang & Shaoyuan Qie, 2018. "Study on the investment timing of carbon capture and storage under different business modes," Greenhouse Gases: Science and Technology, Blackwell Publishing, vol. 8(4), pages 639-649, August.
- Lecca, Patrizio & McGregor, Peter G. & Swales, Kim J. & Tamba, Marie, 2017. "The Importance of Learning for Achieving the UK's Targets for Offshore Wind," Ecological Economics, Elsevier, vol. 135(C), pages 259-268.
- Anelí Bongers, 2017.
"Learning and forgetting in the jet fighter aircraft industry,"
PLOS ONE, Public Library of Science, vol. 12(9), pages 1-19, September.
- Anelí Bongers, 2017. "Learning and Forgetting in the Jet Fighter Aircraft Industry," Working Papers 2017-02, Universidad de Málaga, Department of Economic Theory, Málaga Economic Theory Research Center.
- Rickard Arvidsson & Anne‐Marie Tillman & Björn A. Sandén & Matty Janssen & Anders Nordelöf & Duncan Kushnir & Sverker Molander, 2018. "Environmental Assessment of Emerging Technologies: Recommendations for Prospective LCA," Journal of Industrial Ecology, Yale University, vol. 22(6), pages 1286-1294, December.
- Vinca, Adriano & Rottoli, Marianna & Marangoni, Giacomo & Tavoni, Massimo, 2017.
"The Role of Carbon Capture and Storage Electricity in Attaining 1.5 and 2°C,"
MITP: Mitigation, Innovation and Transformation Pathways
266285, Fondazione Eni Enrico Mattei (FEEM).
- Adriano Vinca & Marianna Rottoli & Giacomo Marangoni & Massimo Tavoni, 2017. "The Role of Carbon Capture and Storage Electricity in Attaining 1.5 and 2°C," Working Papers 2017.54, Fondazione Eni Enrico Mattei.
- 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.
- Zou, Hongyang & Du, Huibin & Brown, Marilyn A. & Mao, Guozhu, 2017. "Large-scale PV power generation in China: A grid parity and techno-economic analysis," Energy, Elsevier, vol. 134(C), pages 256-268.
- Palmer, J. & Sorda, G. & Madlener, R., 2015.
"Modeling the diffusion of residential photovoltaic systems in Italy: An agent-based simulation,"
Technological Forecasting and Social Change, Elsevier, vol. 99(C), pages 106-131.
- Palmer, Johannes & Sorda, Giovanni & Madlener, Reinhard, 2013. "Modeling the Diffusion of Residential Photovoltaic Systems in Italy: An Agent-based Simulation," FCN Working Papers 9/2013, E.ON Energy Research Center, Future Energy Consumer Needs and Behavior (FCN).
- Grafström, Jonas & Lindman, Åsa, 2017. "Invention, innovation and diffusion in the European wind power sector," Technological Forecasting and Social Change, Elsevier, vol. 114(C), pages 179-191.
- Trappey, Amy J.C. & Trappey, Charles V. & Liu, Penny H.Y. & Lin, Lee-Cheng & Ou, Jerry J.R., 2013. "A hierarchical cost learning model for developing wind energy infrastructures," International Journal of Production Economics, Elsevier, vol. 146(2), pages 386-391.
- Jong-Hyun Kim & Yong-Gil Lee, 2018. "Learning Curve, Change in Industrial Environment, and Dynamics of Production Activities in Unconventional Energy Resources," Sustainability, MDPI, vol. 10(9), pages 1-11, September.
- 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.
- Yuan, Rong & Behrens, Paul & Tukker, Arnold & Rodrigues, João F.D., 2018. "Carbon overhead: The impact of the expansion in low-carbon electricity in China 2015–2040," Energy Policy, Elsevier, vol. 119(C), pages 97-104.
- Zhengshan J. Yu & Joe V. Carpenter & Zachary C. Holman, 2018. "Techno-economic viability of silicon-based tandem photovoltaic modules in the United States," Nature Energy, Nature, vol. 3(9), pages 747-753, September.
- Béla Nagy & J Doyne Farmer & Quan M Bui & Jessika E Trancik, 2013.
"Statistical Basis for Predicting Technological Progress,"
PLOS ONE, Public Library of Science, vol. 8(2), pages 1-7, February.
- Bela Nagy & J. Doyne Farmer & Quan M. Bui & Jessika E. Trancik, 2012. "Statistical Basis for Predicting Technological Progress," Papers 1207.1463, arXiv.org.
- Liu, Xi & Du, Huibin & Brown, Marilyn A. & Zuo, Jian & Zhang, Ning & Rong, Qian & Mao, Guozhu, 2018. "Low-carbon technology diffusion in the decarbonization of the power sector: Policy implications," Energy Policy, Elsevier, vol. 116(C), pages 344-356.
- 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.
- 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.
- Cong, Rong-Gang & Shen, Shaochuan, 2014. "How to Develop Renewable Power in China? A Cost-Effective Perspective," MPRA Paper 112209, University Library of Munich, Germany.
- Nadeau, Marie-Claude & Kar, Ashish & Roth, Richard & Kirchain, Randolph, 2010. "A dynamic process-based cost modeling approach to understand learning effects in manufacturing," International Journal of Production Economics, Elsevier, vol. 128(1), pages 223-234, November.
- Glock, C. H. & Grosse, E. H. & Jaber, M. Y. & Smunt, T. L., 2019. "Applications of learning curves in production and operations management: A systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 115511, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Few, Sheridan & Schmidt, Oliver & Offer, Gregory J. & Brandon, Nigel & Nelson, Jenny & Gambhir, Ajay, 2018. "Prospective improvements in cost and cycle life of off-grid lithium-ion battery packs: An analysis informed by expert elicitations," Energy Policy, Elsevier, vol. 114(C), pages 578-590.
- Hong, Sungjun & Chung, Yanghon & Woo, Chungwon, 2015. "Scenario analysis for estimating the learning rate of photovoltaic power generation based on learning curve theory in South Korea," Energy, Elsevier, vol. 79(C), pages 80-89.
- Stefan Reichelstein & Anshuman Sahoo, 2018. "Relating Product Prices to Long‐Run Marginal Cost: Evidence from Solar Photovoltaic Modules," Contemporary Accounting Research, John Wiley & Sons, vol. 35(3), pages 1464-1498, September.
- Talavera, D.L. & Pérez-Higueras, P. & Ruíz-Arias, J.A. & Fernández, E.F., 2015. "Levelised cost of electricity in high concentrated photovoltaic grid connected systems: Spatial analysis of Spain," Applied Energy, Elsevier, vol. 151(C), pages 49-59.
- Gert Berckmans & Maarten Messagie & Jelle Smekens & Noshin Omar & Lieselot Vanhaverbeke & Joeri Van Mierlo, 2017. "Cost Projection of State of the Art Lithium-Ion Batteries for Electric Vehicles Up to 2030," Energies, MDPI, vol. 10(9), pages 1-20, September.
- MacGillivray, Andrew & Jeffrey, Henry & Winskel, Mark & Bryden, Ian, 2014. "Innovation and cost reduction for marine renewable energy: A learning investment sensitivity analysis," Technological Forecasting and Social Change, Elsevier, vol. 87(C), pages 108-124.
- Lin, Boqiang & Li, Jianglong, 2015. "Analyzing cost of grid-connection of renewable energy development in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 1373-1382.
- Ye, Liang-Cheng & Rodrigues, João F.D. & Lin, Hai Xiang, 2017. "Analysis of feed-in tariff policies for solar photovoltaic in China 2011–2016," Applied Energy, Elsevier, vol. 203(C), pages 496-505.
- Nemet, Gregory F., 2006. "Beyond the learning curve: factors influencing cost reductions in photovoltaics," Energy Policy, Elsevier, vol. 34(17), pages 3218-3232, November.
- 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.
- 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.
- Lavidas, George, 2019. "Energy and socio-economic benefits from the development of wave energy in Greece," Renewable Energy, Elsevier, vol. 132(C), pages 1290-1300.
- Nikolaos Kouvaritakis & Antonio Soria & Stephane Isoard, 2000. "Modelling energy technology dynamics: methodology for adaptive expectations models with learning by doing and learning by searching," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 14(1/2/3/4), pages 104-115.
- Jridi, Omar & Jridi, Maher & Barguaoui, Saoussen Aguir & Nouri, Fethi Zouheir, 2016. "Energy paradox and political intervention: A stochastic model for the case of electrical equipments," Energy Policy, Elsevier, vol. 93(C), pages 59-69.
- Yan Xu & Jiahai Yuan & Jianxiu Wang, 2017. "Learning of Power Technologies in China: Staged Dynamic Two-Factor Modeling and Empirical Evidence," Sustainability, MDPI, vol. 9(5), pages 1-14, May.
- Ajanovic, Amela & Haas, Reinhard, 2018. "Economic prospects and policy framework for hydrogen as fuel in the transport sector," Energy Policy, Elsevier, vol. 123(C), pages 280-288.
- Pehnt, Martin, 2006. "Dynamic life cycle assessment (LCA) of renewable energy technologies," Renewable Energy, Elsevier, vol. 31(1), pages 55-71.
- Victor, Nadejda & Nichols, Christopher & Zelek, Charles, 2018. "The U.S. power sector decarbonization: Investigating technology options with MARKAL nine-region model," Energy Economics, Elsevier, vol. 73(C), pages 410-425.
- Lin, Boqiang & He, Jiaxin, 2016. "Learning curves for harnessing biomass power: What could explain the reduction of its cost during the expansion of China?," Renewable Energy, Elsevier, vol. 99(C), pages 280-288.
- 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.
- Glock, C. H. & Grosse, E. H. & Jaber, M. Y. & Smunt, T. L., 2019. "Applications of learning curves in production and operations management: A systematic literature review," Publications of Darmstadt Technical University, Institute for Business Studies (BWL) 107692, Darmstadt Technical University, Department of Business Administration, Economics and Law, Institute for Business Studies (BWL).
- Anton Finenko & Kamal Soundararajan, 2016. "Flexible solar photovoltaic deployments for Singapore: an economic assessment," International Journal of Global Energy Issues, Inderscience Enterprises Ltd, vol. 39(3/4), pages 157-180.
Citations
Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
Cited by:
- Huang, Rui & Lv, Guonian, 2021. "The climate economic effect of technology spillover," Energy Policy, Elsevier, vol. 159(C).
- Anissa Nurdiawati & Frauke Urban, 2021. "Towards Deep Decarbonisation of Energy-Intensive Industries: A Review of Current Status, Technologies and Policies," Energies, MDPI, vol. 14(9), pages 1-33, April.
- Klimenko, V.V. & Ratner, S.V. & Tereshin, A.G., 2021. "Constraints imposed by key-material resources on renewable energy development," Renewable and Sustainable Energy Reviews, Elsevier, vol. 144(C).
- Andrew William Ruttinger & Miyuru Kannangara & Jalil Shadbahr & Phil De Luna & Farid Bensebaa, 2021. "How CO 2 -to-Diesel Technology Could Help Reach Net-Zero Emissions Targets: A Canadian Case Study," Energies, MDPI, vol. 14(21), pages 1-21, October.
- Castrejon-Campos, Omar & Aye, Lu & Hui, Felix Kin Peng & Vaz-Serra, Paulo, 2022. "Economic and environmental impacts of public investment in clean energy RD&D," Energy Policy, Elsevier, vol. 168(C).
- 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).
- Sacchi, R. & Terlouw, T. & Siala, K. & Dirnaichner, A. & Bauer, C. & Cox, B. & Mutel, C. & Daioglou, V. & Luderer, G., 2022. "PRospective EnvironMental Impact asSEment (premise): A streamlined approach to producing databases for prospective life cycle assessment using integrated assessment models," Renewable and Sustainable Energy Reviews, Elsevier, vol. 160(C).
- Lim, Dongjun & Lee, Boreum & Lee, Hyunjun & Byun, Manhee & Lim, Hankwon, 2022. "Projected cost analysis of hybrid methanol production from tri-reforming of methane integrated with various water electrolysis systems: Technical and economic assessment," Renewable and Sustainable Energy Reviews, Elsevier, vol. 155(C).
- Neij, Lena & Nemet, Gregory, 2022. "Accelerating the low-carbon transition will require policy to enhance local learning," Energy Policy, Elsevier, vol. 167(C).
- 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).
- Aui, Alvina & Wang, Yu, 2023. "Cellulosic ethanol production: Assessment of the impacts of learning and plant capacity," Technological Forecasting and Social Change, Elsevier, vol. 197(C).
- 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).
- Kosugi, Takanobu, 2023. "Learning rate matters: Reexamining optimal power expansion planning with endogenized technological experience curves," Energy, Elsevier, vol. 283(C).
- Vetters, Jade & Thomassen, Gwenny & Van Passel, Steven, 2024. "Sailing through end-of-life challenges: A comprehensive review for offshore wind," Renewable and Sustainable Energy Reviews, Elsevier, vol. 199(C).
Most related items
These are the items that most often cite the same works as this one and are cited by the same works as this one.- Elia, A. & Kamidelivand, M. & Rogan, F. & Ó Gallachóir, B., 2021. "Impacts of innovation on renewable energy technology cost reductions," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
- 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.
- 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).
- 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).
- Reinhard Haas & Marlene Sayer & Amela Ajanovic & Hans Auer, 2023. "Technological learning: Lessons learned on energy technologies," Wiley Interdisciplinary Reviews: Energy and Environment, Wiley Blackwell, vol. 12(2), March.
- 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).
- Schauf, Magnus & Schwenen, Sebastian, 2021. "Mills of progress grind slowly? Estimating learning rates for onshore wind energy," Energy Economics, Elsevier, vol. 104(C).
- 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.
- 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.
- Choi, Donghyun & Kim, Yeong Jae, 2023. "Local and global experience curves for lumpy and granular energy technologies," Energy Policy, Elsevier, vol. 174(C).
- Nemet, Gregory F. & Lu, Jiaqi & Rai, Varun & Rao, Rohan, 2020. "Knowledge spillovers between PV installers can reduce the cost of installing solar PV," Energy Policy, Elsevier, vol. 144(C).
- Mauleón, Ignacio, 2016. "Photovoltaic learning rate estimation: Issues and implications," Renewable and Sustainable Energy Reviews, Elsevier, vol. 65(C), pages 507-524.
- 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.
- Renaldi, Renaldi & Hall, Richard & Jamasb, Tooraj & Roskilly, Anthony P., 2021.
"Experience rates of low-carbon domestic heating technologies in the United Kingdom,"
Energy Policy, Elsevier, vol. 156(C).
- Renaldi, Renaldi & Hall, Richard & Jamasb, Tooraj & Roskilly, Anthony P., 2020. "Experience Rates of Low-Carbon Domestic Heating Technologies in the United Kingdom," Working Papers 16-2020, Copenhagen Business School, Department of Economics.
- 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.
- Odam, Neil & de Vries, Frans P., 2020. "Innovation modelling and multi-factor learning in wind energy technology," Energy Economics, Elsevier, vol. 85(C).
- Jabir Ali Ouassou & Julian Straus & Marte Fodstad & Gunhild Reigstad & Ove Wolfgang, 2021. "Applying Endogenous Learning Models in Energy System Optimization," Energies, MDPI, vol. 14(16), pages 1-21, August.
- Sascha Samadi, 2016. "A Review of Factors Influencing the Cost Development of Electricity Generation Technologies," Energies, MDPI, vol. 9(11), pages 1-25, November.
- Glenk, Gunther & Meier, Rebecca & Reichelstein, Stefan, 2021. "Cost dynamics of clean energy technologies," ZEW Discussion Papers 21-054, ZEW - Leibniz Centre for European Economic Research.
- Wei, Max & Smith, Sarah J. & Sohn, Michael D., 2017. "Experience curve development and cost reduction disaggregation for fuel cell markets in Japan and the US," Applied Energy, Elsevier, vol. 191(C), pages 346-357.
More about this item
Keywords
Learning effects; Life cycle assessment; Techno-economic assessment; Prospective technology assessment; Learning-by-doing; Learning curve; Progress rate; Experience curve;All these keywords.
Statistics
Access and download statisticsCorrections
All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:eee:rensus:v:130:y:2020:i:c:s1364032120302288. See general information about how to correct material in RePEc.
If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.
If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .
If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.
For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: Catherine Liu (email available below). General contact details of provider: http://www.elsevier.com/wps/find/journaldescription.cws_home/600126/description#description .
Please note that corrections may take a couple of weeks to filter through the various RePEc services.