The experience curve theory and its application in the field of electricity generation technologies – A literature review

Citations

Cited by:

1. Wei, Yi-Ming & Qiao, Lu & Lv, Xin, 2020. "The impact of mergers and acquisitions on technology learning in the petroleum industry," Energy Economics, Elsevier, vol. 88(C).
2. Farrell, Niall, 2023. "Policy design for green hydrogen," Renewable and Sustainable Energy Reviews, Elsevier, vol. 178(C).
3. 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.
4. 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).
5. Hahn Menacho, A.J. & Rodrigues, J.F.D. & Behrens, P., 2022. "A triple bottom line assessment of concentrated solar power generation in China and Europe 2020–2050," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
6. 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).
7. Cesaro, Zac & Ives, Matthew & Nayak-Luke, Richard & Mason, Mike & Bañares-Alcántara, René, 2021. "Ammonia to power: Forecasting the levelized cost of electricity from green ammonia in large-scale power plants," Applied Energy, Elsevier, vol. 282(PA).
8. 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).
9. Jabir Ali Ouassou & Julian Straus & Marte Fodstad & Gunhild Reigstad & Ove Wolfgang, 2021. "Applying endogenous learning models in energy system optimization," Papers 2106.06373, arXiv.org.
10. Tu, Qiang & Mo, Jianlei & Betz, Regina & Cui, Lianbiao & Fan, Ying & Liu, Yu, 2020. "Achieving grid parity of solar PV power in China- The role of Tradable Green Certificate," Energy Policy, Elsevier, vol. 144(C).
11. Langer, Jannis & Quist, Jaco & Blok, Kornelis, 2020. "Recent progress in the economics of ocean thermal energy conversion: Critical review and research agenda," Renewable and Sustainable Energy Reviews, Elsevier, vol. 130(C).
12. Choi, Donghyun & Kim, Yeong Jae, 2023. "Local and global experience curves for lumpy and granular energy technologies," Energy Policy, Elsevier, vol. 174(C).
13. 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).
14. Odenweller, Adrian, 2022. "Climate mitigation under S-shaped energy technology diffusion: Leveraging synergies of optimisation and simulation models," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
15. Tadeusz Skoczkowski & Sławomir Bielecki & Joanna Wojtyńska, 2019. "Long-Term Projection of Renewable Energy Technology Diffusion," Energies, MDPI, vol. 12(22), pages 1-24, November.
16. Wiser, Ryan & Millstein, Dev, 2020. "Evaluating the economic return to public wind energy research and development in the United States," Applied Energy, Elsevier, vol. 261(C).
17. 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).
18. Mr. Tobias Adrian & Mr. Patrick Bolton & Alissa M. Kleinnijenhuis, 2022. "The Great Carbon Arbitrage," IMF Working Papers 2022/107, International Monetary Fund.
    • Kleinnijenhuis, Alissa & Adrian, Tobias & Bolton, Patrick, 2022. "The Great Carbon Arbitrage," INET Oxford Working Papers 2022-07, Institute for New Economic Thinking at the Oxford Martin School, University of Oxford.
19. 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).
20. Abdul Ghani Olabi & Tabbi Wilberforce & Khaled Elsaid & Enas Taha Sayed & Tareq Salameh & Mohammad Ali Abdelkareem & Ahmad Baroutaji, 2021. "A Review on Failure Modes of Wind Turbine Components," Energies, MDPI, vol. 14(17), pages 1-44, August.
21. 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.
22. Simonas Cerniauskas & Thomas Grube & Aaron Praktiknjo & Detlef Stolten & Martin Robinius, 2019. "Future Hydrogen Markets for Transportation and Industry: The Impact of CO 2 Taxes," Energies, MDPI, vol. 12(24), pages 1-26, December.
23. Mitavachan Hiremath & Peter Viebahn & Sascha Samadi, 2021. "An Integrated Comparative Assessment of Coal-Based Carbon Capture and Storage (CCS) Vis-à-Vis Renewable Energies in India’s Low Carbon Electricity Transition Scenarios," Energies, MDPI, vol. 14(2), pages 1-28, January.
24. 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).
25. Hu, Jing & Harmsen, Robert & Crijns-Graus, Wina & Worrell, Ernst, 2019. "Geographical optimization of variable renewable energy capacity in China using modern portfolio theory," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
26. Woo, C.K. & Zarnikau, J., 2019. "Renewable energy's vanishing premium in Texas's retail electricity pricing plans," Energy Policy, Elsevier, vol. 132(C), pages 764-770.
27. 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.
28. Wen, Xin & Jaxa-Rozen, Marc & Trutnevyte, Evelina, 2023. "Hindcasting to inform the development of bottom-up electricity system models: The cases of endogenous demand and technology learning," Applied Energy, Elsevier, vol. 340(C).
29. 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.
30. 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).
31. Peter Viebahn & Alexander Scholz & Ole Zelt, 2019. "The Potential Role of Direct Air Capture in the German Energy Research Program—Results of a Multi-Dimensional Analysis," Energies, MDPI, vol. 12(18), pages 1-27, September.
32. 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).
33. Odam, Neil & de Vries, Frans P., 2020. "Innovation modelling and multi-factor learning in wind energy technology," Energy Economics, Elsevier, vol. 85(C).