Designing a cost-effective CO2 storage infrastructure using a GIS based linear optimization energy model

Publication date

2010

Authors

van den Broek, M.A.ORCID 0000-0003-1028-1742ISNI 0000000396870440
Brederode, E.
Ramirez-Ramirez, C.A.ISNI 0000000388171084
Kramers, L.
van der Kuip, M.
Wildenborg, T.
Turkenburg, W.C.ISNI 0000000023313975
Faaij, A.P.C.ISNI 0000000397196996

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Document Type

Article
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Abstract

Large-scale deployment of carbon capture and storage needs a dedicated infrastructure. Planning and designing of this infrastructure require incorporation of both temporal and spatial aspects. In this study, a toolbox has been developed that integrates ArcGIS, a geographical information system with spatial and routing functions, and MARKAL, an energy bottom-up model based on linear optimization. Application of this toolbox led to blueprints of a CO2 infrastructure in the Netherlands. The results show that in a scenario with 20% and 50% CO2 emissions reduction targets compared to their 1990 level in respectively 2020 and 2050, an infrastructure of around 600 km of CO2 trunklines may need to be built before 2020. Investment costs for the pipeline construction and the storage site development amount to around 720 m€ and 340 m€, respectively. The results also show the implication of policy choices such as allowing or prohibiting CO2 storage onshore on CO2 Capture and Storage (CCS) and infrastructure development. This paper illustrates how the ArcGIS/MARKAL-based toolbox can provide insights into a CCS infrastructure development, and support policy makers by giving concrete blueprints over time with respect to scale, pipeline trajectories, and deployment of individual storage sites.

Keywords

CO2 capture transport and storage, Linear optimization, GIS, MARKAL, Energy systems model, Taverne

Citation

van den Broek, M A, Brederode, E, Ramírez-Ramírez, A, Kramers, L, van der Kuip, M, Wildenborg, T, Turkenburg, W C & Faaij, A P C 2010, 'Designing a cost-effective CO2 storage infrastructure using a GIS based linear optimization energy model', Environmental Modelling and Software, vol. 25, no. 12, pp. 1754-1768. https://doi.org/10.1016/j.envsoft.2010.06.015