Optimal source-sink matching in carbon capture and storage systems under uncertainty
This study addresses the robust optimal source-sink matching in carbon capture and storage (CCS) supply chains under uncertainty. A continuous-time uncertain mixed-integer linear programming (MILP) model with physical and temporal constraints is developed, where uncertainties are described as interv...
Saved in:
| Main Authors: | , , , , , |
|---|---|
| 格式: | text |
| 出版: |
Animo Repository
2014
|
| 主題: | |
| 在線閱讀: | https://animorepository.dlsu.edu.ph/faculty_research/3644 https://animorepository.dlsu.edu.ph/context/faculty_research/article/4646/type/native/viewcontent/ie402866d.html |
| 標簽: |
添加標簽
沒有標簽, 成為第一個標記此記錄!
|
| 機構: | De La Salle University |
| 總結: | This study addresses the robust optimal source-sink matching in carbon capture and storage (CCS) supply chains under uncertainty. A continuous-time uncertain mixed-integer linear programming (MILP) model with physical and temporal constraints is developed, where uncertainties are described as interval and uniform distributed stochastic parameters. A worst-case MILP formulation and a robust stochastic two-stage MILP formation are proposed to handle interval and stochastic uncertainties, respectively. Then, two illustrative case studies are solved to demonstrate the effectiveness of the proposed models for planning CCS deployment under uncertainty. © 2013 American Chemical Society. |
|---|