Learning rates and future cost curves for fossil fuel energy systems with CO2 capture: Methodology and case studies

Citations

Cited by:

1. Yao, Xing & Zhong, Ping & Zhang, Xian & Zhu, Lei, 2018. "Business model design for the carbon capture utilization and storage (CCUS) project in China," Energy Policy, Elsevier, vol. 121(C), pages 519-533.
2. 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.
3. 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.
4. Liu, Bingsheng & Liu, Song & Xue, Bin & Lu, Shijian & Yang, Yang, 2021. "Formalizing an integrated decision-making model for the risk assessment of carbon capture, utilization, and storage projects: From a sustainability perspective," Applied Energy, Elsevier, vol. 303(C).
5. Huang, Weilong & Chen, Wenying & Anandarajah, Gabrial, 2017. "The role of technology diffusion in a decarbonizing world to limit global warming to well below 2 °C: An assessment with application of Global TIMES model," Applied Energy, Elsevier, vol. 208(C), pages 291-301.
6. George, Jan Frederick & Müller, Viktor Paul & Winkler, Jenny & Ragwitz, Mario, 2022. "Is blue hydrogen a bridging technology? - The limits of a CO2 price and the role of state-induced price components for green hydrogen production in Germany," Energy Policy, Elsevier, vol. 167(C).
7. 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.
8. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Kraslawski, Andrzej & Irabien, Angel, 2013. "Stochastic MILP model for optimal timing of investments in CO2 capture technologies under uncertainty in prices," Energy, Elsevier, vol. 54(C), pages 343-351.
9. 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.
10. 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.
11. Lee, Jui-Yuan & Tan, Raymond R. & Chen, Cheng-Liang, 2014. "A unified model for the deployment of carbon capture and storage," Applied Energy, Elsevier, vol. 121(C), pages 140-148.
12. Jiang, Kai & Ashworth, Peta, 2021. "The development of Carbon Capture Utilization and Storage (CCUS) research in China: A bibliometric perspective," Renewable and Sustainable Energy Reviews, Elsevier, vol. 138(C).
13. Hesel, Philipp & Braun, Sebastian & Zimmermann, Florian & Fichtner, Wolf, 2022. "Integrated modelling of European electricity and hydrogen markets," Applied Energy, Elsevier, vol. 328(C).
14. Gregory Nemet & Erin Baker & Bob Barron & Samuel Harms, 2015. "Characterizing the effects of policy instruments on the future costs of carbon capture for coal power plants," Climatic Change, Springer, vol. 133(2), pages 155-168, November.
15. Wu, Jung-Hua & Huang, Yun-Hsun, 2014. "Electricity portfolio planning model incorporating renewable energy characteristics," Applied Energy, Elsevier, vol. 119(C), pages 278-287.
16. Plaza, M.G. & González, A.S. & Pis, J.J. & Rubiera, F. & Pevida, C., 2014. "Production of microporous biochars by single-step oxidation: Effect of activation conditions on CO2 capture," Applied Energy, Elsevier, vol. 114(C), pages 551-562.
17. Amigues, Jean-Pierre & Lafforgue, Gilles & Moreaux, Michel, 2016. "Optimal timing of carbon capture policies under learning-by-doing," Journal of Environmental Economics and Management, Elsevier, vol. 78(C), pages 20-37.
    • Jean-Pierre Amigues & Gilles Lafforgue & Michel Moreaux, 2015. "Optimal Timing of Carbon Capture Policies under Learning-by-doing," Working Papers 2015.20, FAERE - French Association of Environmental and Resource Economists.
18. Marisa Beck, Randall Wigle, 2014. "Carbon Revenue: Recycling versus Technological Incentives," LCERPA Working Papers 0079, Laurier Centre for Economic Research and Policy Analysis, revised 13 Jan 2014.
19. van Os, Herman W.A. & Herber, Rien & Scholtens, Bert, 2014. "Not Under Our Back Yards? A case study of social acceptance of the Northern Netherlands CCS initiative," Renewable and Sustainable Energy Reviews, Elsevier, vol. 30(C), pages 923-942.
20. 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.
21. 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.
22. 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.
23. Fan, Jing-Li & Xu, Mao & Li, Fengyu & Yang, Lin & Zhang, Xian, 2018. "Carbon capture and storage (CCS) retrofit potential of coal-fired power plants in China: The technology lock-in and cost optimization perspective," Applied Energy, Elsevier, vol. 229(C), pages 326-334.
24. 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).
25. Guo, Jian-Xin & Huang, Chen, 2020. "Feasible roadmap for CCS retrofit of coal-based power plants to reduce Chinese carbon emissions by 2050," Applied Energy, Elsevier, vol. 259(C).
26. Cocco, Daniele & Serra, Fabio & Tola, Vittorio, 2013. "Assessment of energy and economic benefits arising from syngas storage in IGCC power plants," Energy, Elsevier, vol. 58(C), pages 635-643.
27. Hetti, Ravihari Kotagoda & Karunathilake, Hirushie & Chhipi-Shrestha, Gyan & Sadiq, Rehan & Hewage, Kasun, 2020. "Prospects of integrating carbon capturing into community scale energy systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 133(C).
28. Yang, Lin & Lv, Haodong & Wei, Ning & Li, Yiming & Zhang, Xian, 2023. "Dynamic optimization of carbon capture technology deployment targeting carbon neutrality, cost efficiency and water stress: Evidence from China's electric power sector," Energy Economics, Elsevier, vol. 125(C).
29. Lan, Liuhan & Zhang, Youzhong & Zhang, Xingping & Zhang, Xinyue, 2024. "Price effect of multi-energy system with CCS and P2G and its impact on carbon-gas-electricity sectors," Applied Energy, Elsevier, vol. 359(C).
30. Plaza, M.G. & González, A.S. & Pevida, C. & Pis, J.J. & Rubiera, F., 2012. "Valorisation of spent coffee grounds as CO2 adsorbents for postcombustion capture applications," Applied Energy, Elsevier, vol. 99(C), pages 272-279.
31. Wenli Qiang & Shuwen Niu & Xiaojie Liu & Xiang Wang & Zhuo Jia & Runqi Dai, 2018. "Analysis of generation cost changes during China’s energy transition," Energy & Environment, , vol. 29(4), pages 456-472, June.
32. Igor Donskoy, 2023. "Techno-Economic Efficiency Estimation of Promising Integrated Oxyfuel Gasification Combined-Cycle Power Plants with Carbon Capture," Clean Technol., MDPI, vol. 5(1), pages 1-18, February.
33. Yu, Shiwei & Agbemabiese, Lawrence & Zhang, Junjie, 2016. "Estimating the carbon abatement potential of economic sectors in China," Applied Energy, Elsevier, vol. 165(C), pages 107-118.
34. Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2014. "Targeting for carbon sequestration retrofit planning in the power generation sector for multi-period problems," Applied Energy, Elsevier, vol. 113(C), pages 477-487.
35. Lei Zhu & Xing Yao & Xian Zhang, 2020. "Evaluation of cooperative mitigation: captured carbon dioxide for enhanced oil recovery," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 25(7), pages 1261-1285, October.
36. 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.
37. Yao, Xing & Fan, Ying & Zhu, Lei & Zhang, Xian, 2020. "Optimization of dynamic incentive for the deployment of carbon dioxide removal technology: A nonlinear dynamic approach combined with real options," Energy Economics, Elsevier, vol. 86(C).
38. Tola, Vittorio & Pettinau, Alberto, 2014. "Power generation plants with carbon capture and storage: A techno-economic comparison between coal combustion and gasification technologies," Applied Energy, Elsevier, vol. 113(C), pages 1461-1474.
39. 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.
40. Huang, Weijia & Zheng, Danxing & Xie, Hui & Li, Yun & Wu, Weize, 2019. "Hybrid physical-chemical absorption process for carbon capture with strategy of high-pressure absorption/medium-pressure desorption," Applied Energy, Elsevier, vol. 239(C), pages 928-937.