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

• Published in: Applied energy 2017-03, Vol.189, p.725-738
• Main Authors: Lee, Suh-Young, Lee, Jae-Uk, Lee, In-Beum, Han, Jeehoon
• Format: Article
• Language: English
• Subjects: CCS; Downside risk; Life Cycle Assessment; Optimization; Stochastic model
• ISSN: 0306-2619; 1872-9118
• DOI: 10.1016/j.apenergy.2016.12.066

•A stochastic decision-making algorithm for CCS networks incorporating tolerance on risk is provided.•Optimization and modeling of CCS networks is performed.•Economic and Life Cycle Assessment of CCS networks is conducted.•A case study based on power-plant CO2 emission in Korea is presented in this study. 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.