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The improved ChinaCCS decision support system: A case study for Beijing–Tianjin–Hebei Region of China

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  • Sun, Liang
  • Chen, Wenying

Abstract

Wide employment of CO2 capture and storage (CCS) technology is of great importance to the sustainable development of China thanks to its contributions to climate change mitigation. Considering the fact that coal accounts for over 65% in the primary energy consumption mix of China, commensurate infrastructure should be built up to transport CO2 to storage sinks from emission sources. The paper presents the improved ChinaCCS Decision Support System (DSS), a tool developed by the General Algebraic Modeling System (GAMS) for optimizing CO2 transportation network given a set of sources and sinks by generating a fully integrated, cost-minimizing CCS system. The improved ChinaCCS DSS assists in determining the sources, sinks and amounts for CO2 capture and sequestration, as well as the paths and sizes of pipelines, while minimizing the net present value for sequestrating a given amount of CO2. Pipeline construction costs take into account topographic conditions such as slopes, heavily populated areas, rivers, railway, highway, etc. A case study for Beijing–Tianjin–Hebei Region of China was demonstrated in the paper. The results highlighted the importance of systematic planning for CCS infrastructure.

Suggested Citation

  • Sun, Liang & Chen, Wenying, 2013. "The improved ChinaCCS decision support system: A case study for Beijing–Tianjin–Hebei Region of China," Applied Energy, Elsevier, vol. 112(C), pages 793-799.
    • Handle: RePEc:eee:appene:v:112:y:2013:i:c:p:793-799
    DOI: 10.1016/j.apenergy.2013.05.016
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    References listed on IDEAS

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    1. repec:diw:diwwpp:dp1052 is not listed on IDEAS
    2. Middleton, Richard S. & Bielicki, Jeffrey M., 2009. "A scalable infrastructure model for carbon capture and storage: SimCCS," Energy Policy, Elsevier, vol. 37(3), pages 1052-1060, March.
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    Cited by:

    1. 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).
    2. 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.
    3. Zhang, Shuai & Liu, Linlin & Zhang, Lei & Zhuang, Yu & Du, Jian, 2018. "An optimization model for carbon capture utilization and storage supply chain: A case study in Northeastern China," Applied Energy, Elsevier, vol. 231(C), pages 194-206.
    4. Tapia, John Frederick D. & Lee, Jui-Yuan & Ooi, Raymond E.H. & Foo, Dominic C.Y. & Tan, Raymond R., 2016. "Optimal CO2 allocation and scheduling in enhanced oil recovery (EOR) operations," Applied Energy, Elsevier, vol. 184(C), pages 337-345.
    5. Viebahn, Peter & Vallentin, Daniel & Höller, Samuel, 2015. "Prospects of carbon capture and storage (CCS) in China’s power sector – An integrated assessment," Applied Energy, Elsevier, vol. 157(C), pages 229-244.
    6. Herui Cui & Tian Zhao & Ruirui Wu, 2018. "An Investment Feasibility Analysis of CCS Retrofit Based on a Two-Stage Compound Real Options Model," Energies, MDPI, vol. 11(7), pages 1-19, July.
    7. Xu, Xiaoyi & Li, Qi & Cai, Bofeng & Liu, Guizhen & Pang, Lingyun & Jing, Meng & Guo, Jing, 2024. "Cost assessment and potential evaluation of geologic carbon storage in China based on least-cost path analysis," Applied Energy, Elsevier, vol. 371(C).
    8. Lee, Suh-Young & Lee, Jae-Uk & Lee, In-Beum & Han, Jeehoon, 2017. "Design under uncertainty of carbon capture and storage infrastructure considering cost, environmental impact, and preference on risk," Applied Energy, Elsevier, vol. 189(C), pages 725-738.
    9. Knoope, M.M.J. & Ramírez, A. & Faaij, A.P.C., 2015. "The influence of uncertainty in the development of a CO2 infrastructure network," Applied Energy, Elsevier, vol. 158(C), pages 332-347.
    10. Sun, Liang & Chen, Wenying, 2017. "Development and application of a multi-stage CCUS source–sink matching model," Applied Energy, Elsevier, vol. 185(P2), pages 1424-1432.

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