Mathematical Optimization of Carbon Storage and Transport Problem for Carbon Capture, Use, and Storage Chain

Yiwei Wu, Hongyu Zhang, Shuaian Wang and Lu Zhen ()
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Yiwei Wu: Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong 999077, China
Hongyu Zhang: Division of Logistics and Transportation, Shenzhen International Graduate School, Tsinghua University, Shenzhen 518055, China
Shuaian Wang: Department of Logistics and Maritime Studies, Faculty of Business, The Hong Kong Polytechnic University, Hung Hom, Kowloon, Hong Kong 999077, China
Lu Zhen: School of Management, Shanghai University, Shanghai 200436, China

Mathematics, 2023, vol. 11, issue 12, 1-14

Abstract: The greenhouse effect caused by carbon dioxide ( C O 2 ) emissions has forced the shipping industry to actively reduce the amount of C O 2 emissions emitted directly into the atmosphere over the past few years. Carbon capture, utilization, and storage (CCUS) is one of the main technological methods for reducing the amount of C O 2 emissions emitted directly into the atmosphere. C O 2 transport, i.e., shipping C O 2 to permanent or temporary storage sites, is a critical intermediate step in the CCUS chain. This study formulates a mixed-integer programming model for a carbon storage and transport problem in the CCUS chain to optimally determine ship allocation, ship departure scheduling, and C O 2 storage and transport. Taking advantage of the structure of the problem, we transform the mixed-integer programming model into a simpler model that can be computed efficiently. To evaluate the performance of the simpler model, numerous computational experiments are conducted. The results show that all small-scale instances (each with 10 power plants) and medium-scale instances (each with 30 power plants) can be solved optimality by Gurobi within 14.33 s. For large-scale instances with 60 and 65 power plants, feasible solutions with average gap values of 0.06% and 6.93% can be obtained by Gurobi within one hour, which indicates that the proposed methodology can be efficiently applied to practical problems. In addition, important parameters, including the unit fuel price, the time-charter cost, and the ship sailing speed, are examined in sensitivity analyses to investigate the impacts of these factors on operations decisions. In summary, a lower fuel price, a lower charter cost, or a higher ship sailing speed can increase the profit of the CCUS chain.

Keywords: ship allocation and scheduling optimization; maritime decarbonization; carbon capture; utilization; storage (search for similar items in EconPapers)
JEL-codes: C (search for similar items in EconPapers)
Date: 2023
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