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Optimising European supply chains for carbon capture, transport and sequestration, including uncertainty on geological storage availability

机译:优化欧洲供应链用于碳捕获,运输和封存,包括地质储存可用性的不确定性

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Carbon capture and storage is considered a key option for decarbonising the energy sector.However, both the necessity of deploying large-scale infrastructures between the nodes of production and sequestration of CO2, and the uncertainty related to the effective storage availability of sequestration basins still represent major challenges.Here, a mixed integer linear programming approach is proposed for the optimisation of a European supply chain model for carbon capture, transport, and storage.A quantitative assessment of storage uncertainty is incorporated to represent the volumetric capacity of basins to date considered capable of efficiently trapping the anthropogenic CO2 emissions (i.e., deep saline aquifers, hydrocarbon fields and coal fields).The objective is to minimise the total expected cost required to install and operate, over a 10 years' time horizon, the overall network for carbon capture, transport and storage, while also taking into account the financial risk that is generated by uncertainty in geological capacity.The model defines economically optimal European supply chains, whilst simultaneously minimising the financial risk generated by uncertainty in local sequestration availability to ensure a robust design.
机译:碳捕获和存储被认为是低碳化能源sector.However的密钥选项,生产和二氧化碳封存的节点之间部署大型基础设施的必要性,以及与封存盆地的有效存储可用性的不确定性仍然代表主要challenges.Here,线性规划方法的混合整数提出了一种用于欧洲的供应链模型碳捕获,运输和存储的不确定性storage.A定量评估的最优化结合来表示盆地迄今为止容积考虑能够有效地俘获人为的CO2排放(即,深盐水层,烃字段和煤田)。该目标是总的安装和操作成本预期需要,过了10年的时间范围,碳捕获整个网络最小化,运输和储存,同时还考虑到金融风险,其根在地质capacity.The模型定义了经济上最佳的欧洲供应链的不确定性erated,而同时最小化由当地封存的可用性不确定性所产生的金融风险,确保稳健设计。

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