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Identification of management strategies for CO2 capture and sequestration under uncertainty through inexact modeling

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  • Zhang, Xiaodong
  • Duncan, Ian J.
  • Huang, Gordon
  • Li, Gongchen
Abstract
Geologic sequestration has been considered as an effective and critical means for significant reductions of CO2 amounts to the atmosphere among various mitigation approaches. A carbon capture and storage (CCS) management system must be a complex system to accommodate the relevant social, economic, environmental, and political factors. Effective management of such a complex system involves balancing tradeoffs among these key influencing factors. In addition, carbon-emission trading is increased attention as a mechanism for addressing emissions quota shortage problems. Emissions markets have potentials to mediate between various emission sources and CO2 capture and sequestration projects in a systematic manner. The objective of this study is to develop an inexact management model (ICSM) to identify optimal strategies for planning CO2 capture and sequestration with a CCS system involving multiple emission sources, multiple capture technologies and multiple project periods. Two mechanisms are considered including with and without carbon emission trading. The proposed model is based on the interval programming method, where uncertain information is directly incorporated and communicated into the optimization processes through the use of interval numbers. The ICSM model has been applied to a hypothetical case study in CCS management to demonstrate its applicability. The results indicated that total system costs under a trading mechanism would be less than those under a non-trading mechanism through more effective re-allocation of emission quota to different sources within the entire CCS system. The obtained solutions could provide more flexibility for the decision makers in generating appropriate management practices for carbon capture and sequestration.

Suggested Citation

  • Zhang, Xiaodong & Duncan, Ian J. & Huang, Gordon & Li, Gongchen, 2014. "Identification of management strategies for CO2 capture and sequestration under uncertainty through inexact modeling," Applied Energy, Elsevier, vol. 113(C), pages 310-317.
    • Handle: RePEc:eee:appene:v:113:y:2014:i:c:p:310-317
    DOI: 10.1016/j.apenergy.2013.07.055
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    4. Dai, C. & Cai, Y.P. & Li, Y.P. & Sun, W. & Wang, X.W. & Guo, H.C., 2014. "Optimal strategies for carbon capture, utilization and storage based on an inexact mλ-measure fuzzy chance-constrained programming," Energy, Elsevier, vol. 78(C), pages 465-478.
    5. Chatzizacharia, Kalliopi & Benekis, Vasilis & Hatziavramidis, Dimitris, 2016. "A blueprint for an energy policy in Greece with considerations of climate change," Applied Energy, Elsevier, vol. 162(C), pages 382-389.
    6. 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.
    7. Cai, Mengting & Huang, Guohe & Chen, Jiapei & Li, Yunhuan & Fan, Yurui, 2018. "A generalized fuzzy chance-constrained energy systems planning model for Guangzhou, China," Energy, Elsevier, vol. 165(PA), pages 191-204.
    8. Chen, Siyuan & Liu, Jiangfeng & Zhang, Qi & Teng, Fei & McLellan, Benjamin C., 2022. "A critical review on deployment planning and risk analysis of carbon capture, utilization, and storage (CCUS) toward carbon neutrality," Renewable and Sustainable Energy Reviews, Elsevier, vol. 167(C).
    9. Karjunen, Hannu & Tynjälä, Tero & Hyppänen, Timo, 2017. "A method for assessing infrastructure for CO2 utilization: A case study of Finland," Applied Energy, Elsevier, vol. 205(C), pages 33-43.
    10. Zhou, Y. & Li, Y.P. & Huang, G.H., 2015. "Planning sustainable electric-power system with carbon emission abatement through CDM under uncertainty," Applied Energy, Elsevier, vol. 140(C), pages 350-364.
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