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Funded by
© IDRIC 2022 | Website: Tangent & Duncan Weddell & Co
Principal Investigator
Department of Earth Sciences, Imperial College London
Team:
Department of Earth Sciences, Imperial College London:
Prof Sevket Durucan
Dr Ji Quan Shi
Dr Zhenggang Nie
Building onto earlier work by PI Korre and Co-I Durucan, we will address how dynamic, time dependent and uncertain storage constraints, unexpected changes in supply rate and uncertain carbon tax and credit policies affect short-term operability, long-term flexibility and total costs at CCUS cluster level. We aim to clarify the relationship between network design choices (system flexibility, short term and long-term security of storage capacity, supply and total cost) and constraints (geological uncertainty, operational risk and economic factors’ variability). This project will combine these elements into an integrated model for optimisation of transport and storage networks to support stakeholders in large scale CCUS deployment for the industrial decarbonisation clusters.
A key measure of success for the project will be the development of a model that enables industry partners/cluster stakeholders to evaluate the performance of different CCUS network options in terms of techno-economics and decarbonisation potential, as well as to establish their role within the design of alternative/optimal industrial decarbonisation infrastructure options at cluster level.
The uncertainties of CCS system development are represented by a set of scenarios assigned with probabilities. The here and-now decisions for the current deterministic stage and wait-and-see decisions for the future stochastic stages. The optimal capital investments include: which pipeline routes are selected; the size of the selected pipelines; which storage sites are used. The optimal investment decisions satisfy that the expectation of the total costs of all scenarios is minimised. The problem of CCS optimisation under uncertainty is modelled using two stage mixed integer linear programming. For the future work, appropriate proxy models will be developed, which would incorporate the results and understanding of the injection well pressure response modelling (WP1), to provide the aquifer storage building blocks for the integrated model (WP2)