(658g) Optimal Design and Operation of CO2 Transportation and Storage Infrastructure for Industrial Clusters

In almost all sectors in most countries, there is still a need for rapid decarbonisation. Currently, over 60 countries have passed laws or made political pledges to achieve net-zero, with targets from 2030 (Energy & Climate Intelligence Unit, 2022). Amongst the available decarbonisation routes, Carbon Capture, Utilisation and Storage (CCUS) is the most promising particularly for power generation and other carbon-intensive sectors (Bui et al., 2018). One of the main challenges of CCUS implementation in industrial clusters, however, is associated with planning and investing in large-scale infrastructure for CO₂ transport. Although industrial clusters benefit from economies of scale and the shared transport infrastructure (Mechleri et al., 2017), the size and capacity of such transport networks need to be optimised to avoid underestimating the transported amounts that could lead to stranded emitters or overestimating the capacity that would translate to financial losses due to unjustified capital costs. Given that the demand and cost of CO₂ transport in industrial clusters depend on many factors: the number and size of CO₂ emitters, available potential CO₂ transport and storage/utilisation options, etc. (d’Amore et al., 2021), finding the optimal solution for CO₂ transport requires a whole-system approach that involves cost-benefit analysis, while also accounting for a range of evolving scenarios given differing projected pathways to net-zero targets. Scenarios such as those that account for the electrification of industrial processes, the deployment of renewable energy, amongst others, will directly impact the amount of CO₂ emitted, captured and transported in the long run (Mechleri et al., 2017).

As such, we propose a comprehensive approach for optimal CO₂ transport infrastructure design and operation for industrial clusters under different net-zero pathway scenarios. For the infrastructure design, a mixed-integer non-linear programming (MINLP) optimisation model is proposed with an overall (capital and operating) cost minimisation objective. Given a set of CO₂ emitters within an industrial cluster, their projected emissions, and pre-specified storage locations, the optimal size of the transport infrastructure is obtained. Its dynamic operation is further evaluated using an agent-based model which simulates emissions from each cluster member and fluid properties via the transport medium under projected scenarios of carbon reduction targets.

Acknowledgement

This work has received funding from the European Union’s Horizon 2020 research and innovation programme under grant agreement no. 884418. The work reflects only the authors’ views and the European Union is not liable for any use that may be made of the information contained therein.

References

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d’Amore, F., Romano, M. C., & Bezzo, F. (2021). Optimal design of European supply chains for carbon capture and storage from industrial emission sources including pipe and ship transport. International Journal of Greenhouse Gas Control, 109(May), 103372. https://doi.org/10.1016/j.ijggc.2021.103372

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