IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v259y2020ics0306261919317994.html
   My bibliography  Save this article

Feasible roadmap for CCS retrofit of coal-based power plants to reduce Chinese carbon emissions by 2050

Author

Listed:
  • Guo, Jian-Xin
  • Huang, Chen

Abstract

In the medium to long term, China must conduct deep emission reduction actions to transform the country’s economy and meet the conditions of the Paris Agreement. As an advanced emission reduction technology, carbon capture and storage (CCS) is undoubtedly an important means of achieving this goal. China must consider how to retrofit existing thermal power plants to install CCS technology. Thus, the expected future roadmap for power plants with CO2 capture is of significant interest. To achieve this aim, we propose a new CCS project investment model, which helps design the CCS development roadmap for achieving the emission targets for 2050. Reductions in the cost of technologies as a result of learning-by-doing is considered to enrich the model to describe the reality more sensibly. Through some mathematical skills, we transform the original continuous problem into a nonlinear integer programming problem. By solving the model, we are trying to answer questions about when to adopt CCS technology and the cost. The results reveal that early large-scale CCS demonstrations are not necessary. The peak investment period of CCS is around 2035. Operating costs account for 80% of the overall cost of CCS, and thus, policymakers must fully motivate the development and investment of operating technologies, especially capture technologies. The results also show that when the scale of CCS technology is promoted, flexible installation levels can be considered to improve efficiency and reduce costs.

Suggested Citation

  • 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).
  • Handle: RePEc:eee:appene:v:259:y:2020:i:c:s0306261919317994
    DOI: 10.1016/j.apenergy.2019.114112
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261919317994
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.apenergy.2019.114112?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Rozenberg, Julie & Vogt-Schilb, Adrien & Hallegatte, Stephane, 2020. "Instrument choice and stranded assets in the transition to clean capital," Journal of Environmental Economics and Management, Elsevier, vol. 100(C).
    2. Guo, Jian-Xin & Zhu, Lei & Fan, Ying, 2016. "Emission path planning based on dynamic abatement cost curve," European Journal of Operational Research, Elsevier, vol. 255(3), pages 996-1013.
    3. 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.
    4. 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.
    5. Duan Li & Xiaoling Sun, 2006. "Nonlinear Integer Programming," International Series in Operations Research and Management Science, Springer, number 978-0-387-32995-6, December.
    6. Fuss, Sabine & Szolgayova, Jana & Obersteiner, Michael & Gusti, Mykola, 2008. "Investment under market and climate policy uncertainty," Applied Energy, Elsevier, vol. 85(8), pages 708-721, August.
    7. 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.
    8. 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.
    9. K. J. Arrow, 1971. "The Economic Implications of Learning by Doing," Palgrave Macmillan Books, in: F. H. Hahn (ed.), Readings in the Theory of Growth, chapter 11, pages 131-149, Palgrave Macmillan.
    10. Walsh, D.M. & O'Sullivan, K. & Lee, W.T. & Devine, M.T., 2014. "When to invest in carbon capture and storage technology: A mathematical model," Energy Economics, Elsevier, vol. 42(C), pages 219-225.
    11. Krysiak, Frank C., 2011. "Environmental regulation, technological diversity, and the dynamics of technological change," Journal of Economic Dynamics and Control, Elsevier, vol. 35(4), pages 528-544, April.
    12. Bramoulle, Yann & Olson, Lars J., 2005. "Allocation of pollution abatement under learning by doing," Journal of Public Economics, Elsevier, vol. 89(9-10), pages 1935-1960, September.
    13. Chakravorty, Ujjayant & Leach, Andrew & Moreaux, Michel, 2012. "Cycles in nonrenewable resource prices with pollution and learning-by-doing," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1448-1461.
    14. Moreaux, Michel & Withagen, Cees, 2015. "Optimal abatement of carbon emission flows," Journal of Environmental Economics and Management, Elsevier, vol. 74(C), pages 55-70.
    15. Somayeh Heydari & Nick Ovenden & Afzal Siddiqui, 2012. "Real options analysis of investment in carbon capture and sequestration technology," Computational Management Science, Springer, vol. 9(1), pages 109-138, February.
    16. Sharifzadeh, Mahdi & Hien, Raymond Khoo Teck & Shah, Nilay, 2019. "China’s roadmap to low-carbon electricity and water: Disentangling greenhouse gas (GHG) emissions from electricity-water nexus via renewable wind and solar power generation, and carbon capture and sto," Applied Energy, Elsevier, vol. 235(C), pages 31-42.
    17. Goulder, Lawrence H. & Mathai, Koshy, 2000. "Optimal CO2 Abatement in the Presence of Induced Technological Change," Journal of Environmental Economics and Management, Elsevier, vol. 39(1), pages 1-38, January.
    18. Della Seta, Marco & Gryglewicz, Sebastian & Kort, Peter M., 2012. "Optimal investment in learning-curve technologies," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1462-1476.
    Full references (including those not matched with items on IDEAS)

    Citations

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


    Cited by:

    1. Guo, Jian-Xin & Zhu, Kaiwei & Tan, Xianchun & Gu, Baihe, 2021. "Low-carbon technology development under multiple adoption risks," Technological Forecasting and Social Change, Elsevier, vol. 172(C).
    2. Wen, Shiyan & Jia, Zhijie, 2022. "The energy, environment and economy impact of coal resource tax, renewable investment, and total factor productivity growth," Resources Policy, Elsevier, vol. 77(C).
    3. Dongdong Song & Tong Jiang & Chuanping Rao, 2022. "Review of Policy Framework for the Development of Carbon Capture, Utilization and Storage in China," IJERPH, MDPI, vol. 19(24), pages 1-16, December.
    4. Sammarchi, Sergio & Li, Jia & Izikowitz, David & Yang, Qiang & Xu, Dong, 2022. "China’s coal power decarbonization via CO2 capture and storage and biomass co-firing: A LCA case study in Inner Mongolia," Energy, Elsevier, vol. 261(PA).
    5. Wu, Xiaomei & Fan, Huifeng & Mao, Yuanhao & Sharif, Maimoona & Yu, Yunsong & Zhang, Zaoxiao & Liu, Guangxin, 2022. "Systematic study of an energy efficient MEA-based electrochemical CO2 capture process: From mechanism to practical application," Applied Energy, Elsevier, vol. 327(C).
    6. Luo, Shihua & Hu, Weihao & Liu, Wen & Xu, Xiao & Huang, Qi & Chen, Zhe & Lund, Henrik, 2021. "Transition pathways towards a deep decarbonization energy system—A case study in Sichuan, China," Applied Energy, Elsevier, vol. 302(C).
    7. 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.
    8. Hu, Yingying & Wu, Wei, 2023. "Can fossil energy make a soft landing?— the carbon-neutral pathway in China accompanying CCS," Energy Policy, Elsevier, vol. 174(C).
    9. Yin, Linfei & Tao, Min, 2023. "Balanced broad learning prediction model for carbon emissions of integrated energy systems considering distributed ground source heat pump heat storage systems and carbon capture & storage," Applied Energy, Elsevier, vol. 329(C).
    10. Di, Zichen & Yilmaz, Duygu & Biswas, Arijit & Cheng, Fangqin & Leion, Henrik, 2022. "Spinel ferrite-contained industrial materials as oxygen carriers in chemical looping combustion," Applied Energy, Elsevier, vol. 307(C).
    11. Wang, Zhaohua & Zhang, Hongzhi & Li, Hao & Wang, Bo & Cui, Qi & Zhang, Bin, 2022. "Economic impact and energy transformation of different effort-sharing schemes to pursue 2 ℃ warming limit in China," Applied Energy, Elsevier, vol. 320(C).
    12. Liu, Zheng & Huang, Yu-Qing & Shang, Wen-Long & Zhao, Yuan-Jun & Yang, Zao-Li & Zhao, Zhao, 2022. "Precooling energy and carbon emission reduction technology investment model in a fresh food cold chain based on a differential game," Applied Energy, Elsevier, vol. 326(C).
    13. Shenghao Feng & Xiujian Peng & Philip Adams, 2021. "Energy and Economic Implications of Carbon Neutrality in China -- A Dynamic General Equilibrium Analysis," Centre of Policy Studies/IMPACT Centre Working Papers g-318, Victoria University, Centre of Policy Studies/IMPACT Centre.
    14. Wang, Peng-Tao & Wei, Yi-Ming & Yang, Bo & Li, Jia-Quan & Kang, Jia-Ning & Liu, Lan-Cui & Yu, Bi-Ying & Hou, Yun-Bing & Zhang, Xian, 2020. "Carbon capture and storage in China’s power sector: Optimal planning under the 2 °C constraint," Applied Energy, Elsevier, vol. 263(C).
    15. 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.

    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.
    1. Guo, Jian-Xin & Tan, Xianchun & Gu, Baihe & Zhu, Kaiwei, 2022. "Integration of supply chain management of hybrid biomass power plant with carbon capture and storage operation," Renewable Energy, Elsevier, vol. 190(C), pages 1055-1065.
    2. Chakravorty, Ujjayant & Leach, Andrew & Moreaux, Michel, 2009. ""Twin Peaks" in Energy Prices: A Hotelling Model with Pollution Learning," Working Papers 2009-10, University of Alberta, Department of Economics.
    3. Durmaz, Tunç, 2018. "The economics of CCS: Why have CCS technologies not had an international breakthrough?," Renewable and Sustainable Energy Reviews, Elsevier, vol. 95(C), pages 328-340.
    4. 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.
    5. Baldwin, Elizabeth & Cai, Yongyang & Kuralbayeva, Karlygash, 2020. "To build or not to build? Capital stocks and climate policy∗," Journal of Environmental Economics and Management, Elsevier, vol. 100(C).
    6. Vogt-Schilb, Adrien & Meunier, Guy & Hallegatte, Stéphane, 2018. "When starting with the most expensive option makes sense: Optimal timing, cost and sectoral allocation of abatement investment," Journal of Environmental Economics and Management, Elsevier, vol. 88(C), pages 210-233.
    7. Guo, Jian-Xin & Zhu, Lei & Fan, Ying, 2016. "Emission path planning based on dynamic abatement cost curve," European Journal of Operational Research, Elsevier, vol. 255(3), pages 996-1013.
    8. Yang, Lin & Xu, Mao & Fan, Jingli & Liang, Xi & Zhang, Xian & Lv, Haodong & Wang, Dong, 2021. "Financing coal-fired power plant to demonstrate CCS (carbon capture and storage) through an innovative policy incentive in China," Energy Policy, Elsevier, vol. 158(C).
    9. Enrica Cian & Samuel Carrara & Massimo Tavoni, 2014. "Innovation benefits from nuclear phase-out: can they compensate the costs?," Climatic Change, Springer, vol. 123(3), pages 637-650, April.
    10. Chakravorty, Ujjayant & Leach, Andrew & Moreaux, Michel, 2012. "Cycles in nonrenewable resource prices with pollution and learning-by-doing," Journal of Economic Dynamics and Control, Elsevier, vol. 36(10), pages 1448-1461.
    11. 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).
    12. 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.
    13. Elofsson, Katarina, 2014. "International knowledge diffusion and its impact on the cost-effective clean-up of the Baltic Sea," Working Paper Series 2014:06, Swedish University of Agricultural Sciences, Department Economics.
    14. Popp, David & Newell, Richard G. & Jaffe, Adam B., 2010. "Energy, the Environment, and Technological Change," Handbook of the Economics of Innovation, in: Bronwyn H. Hall & Nathan Rosenberg (ed.), Handbook of the Economics of Innovation, edition 1, volume 2, chapter 0, pages 873-937, Elsevier.
    15. CHAKRAVORTY Ujjayant & LEACH Andrew & MOREAUX Michel, 2008. ""Twin Peaks" in Energy Prices: A Polluting Fossil Fuel with Learning in the Clean Substitute," LERNA Working Papers 08.15.259, LERNA, University of Toulouse.
    16. 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.
    17. Elofsson, Katarina & Gren, Ing-Marie, 2014. "Cost-efficient climate policies for interdependent and uncertain carbon pools," Working Paper Series 2014:7, Swedish University of Agricultural Sciences, Department Economics.
    18. Fan, Jing-Li & Xu, Mao & Yang, Lin & Zhang, Xian, 2019. "Benefit evaluation of investment in CCS retrofitting of coal-fired power plants and PV power plants in China based on real options," Renewable and Sustainable Energy Reviews, Elsevier, vol. 115(C).
    19. Gerlagh, Reyer & Kverndokk, Snorre & Rosendahl, Knut Einar, 2014. "The optimal time path of clean energy R&D policy when patents have finite lifetime," Journal of Environmental Economics and Management, Elsevier, vol. 67(1), pages 2-19.
    20. Tiruwork B. Tibebu & Eric Hittinger & Qing Miao & Eric Williams, 2024. "Adoption Model Choice Affects the Optimal Subsidy for Residential Solar," Energies, MDPI, vol. 17(3), pages 1-19, February.

    Corrections

    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:appene:v:259:y:2020:i:c:s0306261919317994. 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/405891/description#description .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.