Cost-optimal CO2 transport systems for carbon capture and storage deployment

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Examensarbete för masterexamen
Master's Thesis

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This thesis investigates the cost and composition of a Swedish system with large scale implementation of CCS and how the implementation is affected by condition standards, route-flexible vehicle deployment and volume of CO2 captured. A mixed integer linear programming model that considers the cost of emitted CO2 and each step in the CCS chain. The CCS chain in the model contains the capture and liquefaction processes, intermediate storage at sites and transportation hubs, transportation of captured CO2, and the storage sites. The transportation modes considered in the model are ships, trains, trucks and pipelines. There are 3 condi tions considered in the model, which are combinations of pressure and temperature during transportation. This model is applied to a case study where Swedish indus trial plants with more than 100 kt annual CO2 emissions are included. The model adds flexible deployment of vehicles . The system and how it is affected are investi gated by constructing and comparing scenarios. The modeling result shows that transportation is a relatively small part of the CCS cost, but this part can increase if there are limited transportation options. The model also shows that there are multiple ways to set up the system for similar specific chain costs when the base case and scenarios are compared. Systems with one condition are likely better than systems with multiple conditions. That a system with only pipelines is not viable in Sweden. The only difference between route-flexible and route-specific vehicles is the system composition. Higher volume of captured CO2 have a small decrease in the specific cost. The preferred transportation mode in the model is ships with large capacity for long distances and trains for shorter distances. Trucks are also used for shorter distances due to locations missing the required infrastructure for trains.

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Ämne/nyckelord

CCS, BECCS, CO2 transportation, Cost minimization, Mixed integer linear programming

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