European supply chains for carbon capture, transport and sequestration, with uncertainties in geological storage capacity: Insights from economic optimisation
File(s)dAmore_et_al_CACE_SecondRevision.docx (3.56 MB)
Accepted version
Author(s)
d'Amore, Federico
Sunny, Nixon
Iruretagoyena, Diana
Bezzo, Fabrizio
Shah, Nilay
Type
Journal Article
Abstract
Carbon capture and storage is widely recognised as a promising technology for decarbonising the energy and industrial sector. An integrated assessment of technological options is required for effective deployment of large-scale infrastructures between the nodes of production and sequestration of CO2. Additionally, design challenges due to uncertainties in the effective storage availability of sequestration basins must be tackled for the optimal planning of long-lived infrastructure. The objective of this study is to quantify the financial risks arising from geological uncertainties in European supply chain networks, whilst also providing a tool for minimising storage risk exposure. For this purpose, a methodological approach utilising mixed integer linear optimisation is developed and subsequent analysis demonstrates that risks arising from geological volumes are negligible compared to the overall network costs (always <1% of total cost) although they may be significant locally. The model shows that a slight increase in transport (+11%) and sequestration (+5%) costs is required to obtain a resilient supply chain, but the overall investment is substantially unchanged (max. +0.2%) with respect to a risk-neutral network. It is shown that risks in storage capacities can be minimised via careful design of the network, through distributing the investment for storage across Europe, and incorporating operational flexibility.
Date Issued
2019-10-04
Date Acceptance
2019-07-20
Citation
Computers and Chemical Engineering, 2019, 129, pp.1-18
ISSN
0098-1354
Publisher
Elsevier
Start Page
1
End Page
18
Journal / Book Title
Computers and Chemical Engineering
Volume
129
Copyright Statement
© 2019 Elsevier Ltd. All rights reserved. This manuscript is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International Licence http://creativecommons.org/licenses/by-nc-nd/4.0/
Sponsor
BEIS - Department for Business, Energy and Industrial Strategy
Identifier
http://gateway.webofknowledge.com/gateway/Gateway.cgi?GWVersion=2&SrcApp=PARTNER_APP&SrcAuth=LinksAMR&KeyUT=WOS:000482588500006&DestLinkType=FullRecord&DestApp=ALL_WOS&UsrCustomerID=1ba7043ffcc86c417c072aa74d649202
Grant Number
415000025679
Subjects
Science & Technology
Technology
Computer Science, Interdisciplinary Applications
Engineering, Chemical
Computer Science
Engineering
Carbon capture transport and storage
European supply chain optimisation
Mixed integer linear programming
Uncertainty in storage capacity and risk
CO2 CAPTURE
POWER-SYSTEMS
DESIGN
RISK
INFRASTRUCTURE
TECHNOLOGY
IMPACT
MODEL
Publication Status
Published online
Article Number
UNSP 106521
Date Publish Online
2019-07-22