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This study investigates the optimal design of carbon capture, transport and storage (CCTS) supply chains for decarbonizing industrial emitters. It builds upon previous analyses, which determine the cost-optimal design of CCTS supply chains while complying with specified emissions reduction scenarios, and determines optimal designs in terms of minimum cost and maximum resilience. The resilience of a supply chain is defined as its ability to permanently store the captured CO2 during the time horizon of interest, and it is quantified in terms of expected amount of carbon not stored under a fixed number of possible simultaneous failures. A mixed-integer linear program is developed to design CCTS supply chains that ensure a specified level of resilience while minimizing total system costs and CO2 emissions. The model is illustrated by determining the optimal decarbonization strategy in terms of costs and level of resilience for the Swiss waste-to-energy sector from 2025 to 2050. Overall, resilience is achieved with a cost increase with respect to the cost-optimal solution ranging from about 5% (backup truck connections to minimize the cost of the supply chain) to about 70% (backup pipeline connections to minimize the emissions of the supply chain) when the storage site is in the North Sea. When the storage site is available in Switzerland, the cost increase is much reduced and ranges from about 1% to 10% with respect to the cost-optimal solution.
Gabrielli et al. (Thu,) studied this question.