Establishing an inter-cluster batchwise carbon capture and storage network in the UK
Establishing an inter-cluster batchwise carbon capture and storage network in the UK
The UK government's ambitious GHG abatement aims to achieve 90 to 170 Mtpa CO2 capture by 2050 with at least 50 Mtpa by 2035. This vision also states the importance of non-pipeline-transport (NPT) options. This paper integrates batchwise CO2 transportation options (i.e. ship, rails, and lorries) with planned pipeline-based carbon capture and storage (CCS) systems, enhancing the decarbonisation of industrial clusters. A Multi-period, Multi-mode, and Multi objective Mixed integer linear programming (MoMilp) framework is adopted to perform deterministic, stochastic, and multio bjective optimisations for the transport value chain of captured CO2 and regional infrastructure. Bottom-up process modelling data serves as input to design the infrastructure required for establishing efficient batchwise CCS networks. Publicly available point source emissions were used to devise emission profiles for the 30-year time horizon. Disperse CO2 sources are clustered by CO2 emission mass and distance using a machine learning algorithm (i.e. K-means). Two clustering concepts were analysed: a cluster hub only option, comprising 6 stationary emitters with 104 Mt CO2 over 30 years, and the cluster expanded option, comprising the 6 stationary and a further 38 satellite emitters with 209 Mt CO2 over 30 years. The optimisation results predict that the unit cost ranges from 16.4 to 29.2 £ t-1CO2, depending on the concept. The levelised cost (i.e. at 10%) ranges from 29.3 to 33.8 £ t-1CO2. Stochasticity in the emission profile increased the total cost by more than 20%. In the multi objective optimisation, the main opportunity for reducing GHG emissions from the network was to replace ship transportation with rail; however,this option would impose significant pressure on an already saturated rail network.
Martins Fraga, Denis
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Korre, Anna
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Nie, Zhenggang
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Durucan, Şevket
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Radcliffe, Jonathan
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Fender, Tom
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Teagle, Damon
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Armstrong, Lindsay-Marie
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Turnock, Stephen
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Vakili, Seyedvahid
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3 January 2025
Martins Fraga, Denis
fabced41-fbd1-4551-8f03-6010bcc47873
Korre, Anna
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Nie, Zhenggang
39870480-d555-48aa-919d-b81ef84444c2
Durucan, Şevket
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Radcliffe, Jonathan
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Fender, Tom
cf08ad19-7342-44c3-acf6-81b6a76758f8
Teagle, Damon
396539c5-acbe-4dfa-bb9b-94af878fe286
Armstrong, Lindsay-Marie
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Turnock, Stephen
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Vakili, Seyedvahid
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Martins Fraga, Denis, Korre, Anna, Nie, Zhenggang, Durucan, Şevket, Radcliffe, Jonathan, Fender, Tom, Teagle, Damon, Armstrong, Lindsay-Marie, Turnock, Stephen and Vakili, Seyedvahid
(2025)
Establishing an inter-cluster batchwise carbon capture and storage network in the UK.
In Proceedings of the 17th Greenhouse Gas Control Technologies Conference (GHGT-17) 20-24 October 2024.
9 pp
.
(doi:10.2139/ssrn.5070429).
Record type:
Conference or Workshop Item
(Paper)
Abstract
The UK government's ambitious GHG abatement aims to achieve 90 to 170 Mtpa CO2 capture by 2050 with at least 50 Mtpa by 2035. This vision also states the importance of non-pipeline-transport (NPT) options. This paper integrates batchwise CO2 transportation options (i.e. ship, rails, and lorries) with planned pipeline-based carbon capture and storage (CCS) systems, enhancing the decarbonisation of industrial clusters. A Multi-period, Multi-mode, and Multi objective Mixed integer linear programming (MoMilp) framework is adopted to perform deterministic, stochastic, and multio bjective optimisations for the transport value chain of captured CO2 and regional infrastructure. Bottom-up process modelling data serves as input to design the infrastructure required for establishing efficient batchwise CCS networks. Publicly available point source emissions were used to devise emission profiles for the 30-year time horizon. Disperse CO2 sources are clustered by CO2 emission mass and distance using a machine learning algorithm (i.e. K-means). Two clustering concepts were analysed: a cluster hub only option, comprising 6 stationary emitters with 104 Mt CO2 over 30 years, and the cluster expanded option, comprising the 6 stationary and a further 38 satellite emitters with 209 Mt CO2 over 30 years. The optimisation results predict that the unit cost ranges from 16.4 to 29.2 £ t-1CO2, depending on the concept. The levelised cost (i.e. at 10%) ranges from 29.3 to 33.8 £ t-1CO2. Stochasticity in the emission profile increased the total cost by more than 20%. In the multi objective optimisation, the main opportunity for reducing GHG emissions from the network was to replace ship transportation with rail; however,this option would impose significant pressure on an already saturated rail network.
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Published date: 3 January 2025
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URI: http://eprints.soton.ac.uk/id/eprint/502340
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Date deposited: 24 Jun 2025 16:30
Last modified: 25 Jun 2025 02:08
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Author:
Denis Martins Fraga
Author:
Anna Korre
Author:
Zhenggang Nie
Author:
Şevket Durucan
Author:
Jonathan Radcliffe
Author:
Tom Fender
Author:
Seyedvahid Vakili
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