IDEAS home Printed from https://ideas.repec.org/a/eee/eneeco/v141y2025ics0140988324008442.html
   My bibliography  Save this article

Assessing uncertain technological progress in the decarbonization pathway of China's hydrogen energy system

Author

Listed:
  • Zhou, Wenji
  • Ren, Hongtao
  • Zhang, Xiao-Bing
  • Shao, Shuai

Abstract

Hydrogen energy is regarded as a promising solution for decarbonizing hard-to-abate sectors, while its role in the energy transition remains debatable. One of the key reasons is that uncertainty in technological progress has significant impacts on investment decision-making. To assess these effects, this study employs the MESSAGEix framework to develop a hydrogen energy system optimization model in China's context and integrates it with a stochastic scenario-tree generation method to assess the effects of uncertain technological progress on decarbonizing China's hydrogen energy system. The modeled system covers a full range of hydrogen production and consumption associated with different technical options for decarbonization, i.e., renewable energy-based water electrolysis (green hydrogen) and fossil-derived hydrogen coupled with carbon capture and storage. The model simulates a wide range of stochastic crucial cost metrics under the carbon-neutral constraint and compares it to a baseline without an emission constraint. Results show that disruptive technological breakthroughs in renewable electricity generation are essential to decarbonizing the hydrogen production system. The proposed hybrid modeling approach proves that computing is effective and could be applied to many other stochastic programming problems in long-term energy system planning.

Suggested Citation

  • Zhou, Wenji & Ren, Hongtao & Zhang, Xiao-Bing & Shao, Shuai, 2025. "Assessing uncertain technological progress in the decarbonization pathway of China's hydrogen energy system," Energy Economics, Elsevier, vol. 141(C).
    • Handle: RePEc:eee:eneeco:v:141:y:2025:i:c:s0140988324008442
    DOI: 10.1016/j.eneco.2024.108135
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0140988324008442
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.eneco.2024.108135?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. Rishee K. Jain & Junjie Qin & Ram Rajagopal, 2017. "Data-driven planning of distributed energy resources amidst socio-technical complexities," Nature Energy, Nature, vol. 2(8), pages 1-11, August.
    2. Biying Yu & Zihao Zhao & Yi-Ming Wei & Lan-Cui Liu & Qingyu Zhao & Shuo Xu & Jia-Ning Kang & Hua Liao, 2023. "Approaching national climate targets in China considering the challenge of regional inequality," Nature Communications, Nature, vol. 14(1), pages 1-12, December.
    3. Megy, Camille & Massol, Olivier, 2023. "Is Power-to-Gas always beneficial? The implications of ownership structure," Energy Economics, Elsevier, vol. 128(C).
    4. Shu Zhang & Wenying Chen, 2022. "Assessing the energy transition in China towards carbon neutrality with a probabilistic framework," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    5. Lei, Yang & Wang, Dan & Jia, Hongjie & Li, Jiaxi & Chen, Jingcheng & Li, Jingru & Yang, Zhihong, 2021. "Multi-stage stochastic planning of regional integrated energy system based on scenario tree path optimization under long-term multiple uncertainties," Applied Energy, Elsevier, vol. 300(C).
    6. Kim, Hansung & Cheon, Hyungkyu & Ahn, Young-Hwan & Choi, Dong Gu, 2019. "Uncertainty quantification and scenario generation of future solar photovoltaic price for use in energy system models," Energy, Elsevier, vol. 168(C), pages 370-379.
    7. Oshiro, Ken & Fujimori, Shinichiro, 2022. "Role of hydrogen-based energy carriers as an alternative option to reduce residual emissions associated with mid-century decarbonization goals," Applied Energy, Elsevier, vol. 313(C).
    8. vom Scheidt, Frederik & Qu, Jingyi & Staudt, Philipp & Mallapragada, Dharik S. & Weinhardt, Christof, 2022. "Integrating hydrogen in single-price electricity systems: The effects of spatial economic signals," Energy Policy, Elsevier, vol. 161(C).
    9. Tieju Ma, 2010. "Coping with Uncertainties in Technological Learning," Management Science, INFORMS, vol. 56(1), pages 192-201, January.
    10. Kjetil Høyland & Stein W. Wallace, 2001. "Generating Scenario Trees for Multistage Decision Problems," Management Science, INFORMS, vol. 47(2), pages 295-307, February.
    11. Ren, Lei & Zhou, Sheng & Peng, Tianduo & Ou, Xunmin, 2021. "A review of CO2 emissions reduction technologies and low-carbon development in the iron and steel industry focusing on China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    12. Bae, Jeong Hwan & Cho, Gyeong-Lyeob, 2010. "A dynamic general equilibrium analysis on fostering a hydrogen economy in Korea," Energy Economics, Elsevier, vol. 32(Supplemen), pages 57-66, September.
    Full references (including those not matched with items on IDEAS)

    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. Xian, Yujiao & Hu, Zhihui & Wang, Ke, 2023. "The least-cost abatement measure of carbon emissions for China's glass manufacturing industry based on the marginal abatement costs," Energy, Elsevier, vol. 284(C).
    2. Shao, Tianming & Pan, Xunzhang & Li, Xiang & Zhou, Sheng & Zhang, Shu & Chen, Wenying, 2022. "China's industrial decarbonization in the context of carbon neutrality: A sub-sectoral analysis based on integrated modelling," Renewable and Sustainable Energy Reviews, Elsevier, vol. 170(C).
    3. Yu, Biying & Dai, Ying & Fu, Jiahao & Qi, Jiahong & Li, Xia, 2025. "Industrial risks assessment for the large-scale development of electric arc furnace steelmaking technology," Applied Energy, Elsevier, vol. 377(PC).
    4. Wang, Ke & Liu, Fangming & Liu, Junling, 2025. "Techno-economic assessment of different clean hydrogen development pathways across industries in China," Applied Energy, Elsevier, vol. 382(C).
    5. Owadally, Iqbal & Jang, Chul & Clare, Andrew, 2021. "Optimal investment for a retirement plan with deferred annuities," Insurance: Mathematics and Economics, Elsevier, vol. 98(C), pages 51-62.
    6. Liu, Pei-chen Barry & Hansen, Mark & Mukherjee, Avijit, 2008. "Scenario-based air traffic flow management: From theory to practice," Transportation Research Part B: Methodological, Elsevier, vol. 42(7-8), pages 685-702, August.
    7. Gulpinar, Nalan & Rustem, Berc & Settergren, Reuben, 2004. "Simulation and optimization approaches to scenario tree generation," Journal of Economic Dynamics and Control, Elsevier, vol. 28(7), pages 1291-1315, April.
    8. Yang, Honghua & Ma, Linwei & Li, Zheng, 2023. "Tracing China's steel use from steel flows in the production system to steel footprints in the consumption system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
    9. Igos, Elorri & Rugani, Benedetto & Rege, Sameer & Benetto, Enrico & Drouet, Laurent & Zachary, Daniel S., 2015. "Combination of equilibrium models and hybrid life cycle-input–output analysis to predict the environmental impacts of energy policy scenarios," Applied Energy, Elsevier, vol. 145(C), pages 234-245.
    10. Ning Zhang & Aziz Kemal Konyalıoğlu & Huabo Duan & Haibo Feng & Huanyu Li, 2024. "The impact of innovative technologies in construction activities on concrete debris recycling in China: a system dynamics-based analysis," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 26(6), pages 14039-14064, June.
    11. Tanaka, Ken'ichiro & Toda, Alexis Akira, 2015. "Discretizing Distributions with Exact Moments: Error Estimate and Convergence Analysis," University of California at San Diego, Economics Working Paper Series qt7g23r5kh, Department of Economics, UC San Diego.
    12. Zhang, Gaohang & Li, Fengting & Wang, Sen & Yin, Chunya, 2023. "Robust low-carbon energy and reserve scheduling considering operational risk and flexibility improvement," Energy, Elsevier, vol. 284(C).
    13. Wu, Dexiang & Wu, Desheng Dash, 2020. "A decision support approach for two-stage multi-objective index tracking using improved lagrangian decomposition," Omega, Elsevier, vol. 91(C).
    14. Murat Köksalan & Ceren Tuncer Şakar, 2016. "An interactive approach to stochastic programming-based portfolio optimization," Annals of Operations Research, Springer, vol. 245(1), pages 47-66, October.
    15. D. Kuhn, 2009. "Convergent Bounds for Stochastic Programs with Expected Value Constraints," Journal of Optimization Theory and Applications, Springer, vol. 141(3), pages 597-618, June.
    16. Yuancheng Lin & Honghua Yang & Linwei Ma & Zheng Li & Weidou Ni, 2021. "Low-Carbon Development for the Iron and Steel Industry in China and the World: Status Quo, Future Vision, and Key Actions," Sustainability, MDPI, vol. 13(22), pages 1-28, November.
    17. Yihan Wang & Zongguo Wen & Mao Xu & Christian Doh Dinga, 2025. "Long-term transformation in China’s steel sector for carbon capture and storage technology deployment," Nature Communications, Nature, vol. 16(1), pages 1-13, December.
    18. Zhao, Laijun & Wang, Ke & Yi, Hongru & Cheng, Youfeng & Zhen, Juntao & Hu, Haisheng, 2024. "Carbon emission drivers of China's power sector and its transformation for global decarbonization contribution," Applied Energy, Elsevier, vol. 376(PA).
    19. Wen Zhang & Yuting Yang & Huigang Liang, 2023. "A Bibliometric Analysis of Enterprise Social Media in Digital Economy: Research Hotspots and Trends," Sustainability, MDPI, vol. 15(16), pages 1-21, August.
    20. Bongsuk Sung & Hong Chen & Sang Do Park, 2024. "Who Drives Policy Discourse of China’s Energy Transition: Considering Time Series Perspective, Network and Core-Peripheral Analysis," SAGE Open, , vol. 14(2), pages 21582440241, May.

    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:eneeco:v:141:y:2025:i:c:s0140988324008442. 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/locate/eneco .

    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.