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Design under uncertainty of carbon capture and storage infrastructure considering cost, environmental impact, and preference on risk

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  • Lee, Suh-Young
  • Lee, Jae-Uk
  • Lee, In-Beum
  • Han, Jeehoon

Abstract

We present a stochastic decision-making algorithm for the design and operation of a carbon capture and storage (CCS) network; the algorithm incorporates the decision-maker’s tolerance of risk caused by uncertainties. Given a set of available resources to capture, store, and transport CO2, the algorithm provides an optimal plan of the CCS infrastructure and a CCS assessment method, while minimizing annual cost, environmental impact, and risk under uncertainties. The model uses the concept of downside risk to explicitly incorporate the trade-off between risk and either economic or environmental objectives at the decision-making level. A two-phase-two-stage stochastic multi-objective optimization problem (2P2SSMOOP) solving approach is implemented to consider uncertainty, and the ε-constraint method is used to evaluate the interaction between total annual cost with financial risk and an Eco-indicator 99 score with environmental risk. The environmental impact is measured by Life Cycle Assessment (LCA) considering all contributions made by operation and installation of a CCS infrastructure. A case study of power-plant CO2 emission in Korea is presented to illustrate the application of the proposed modeling and solution method.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:appene:v:189:y:2017:i:c:p:725-738
    DOI: 10.1016/j.apenergy.2016.12.066
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