Techno-economic-based dynamic network design for optimum large-scale carbon dioxide utilisation in process industries

Carbon capture and utilisation programs strive to efficiently utilise the captured carbon dioxide to produce value-added products. In view of this, the authors present a novel methodology to enable responsive carbon capture and utilisation through a fixed network design. This is based on optimal decision-making for planning the supply and consumption of carbon dioxide via a pipeline network to produce chemical additives and liquid fuel products, with the added benefit of enhancing the revenue streams of the consumers. The methodology was demonstrated through the identification, optimisation and techno-economic assessment of the linkages between carbon dioxide sources (emitters) and sinks (consumers) on a national scale for a case study in Qatar. The techno-economic indicators, such as net present value (NPV), internal rate of return (IRR) and profit-to-investment ratio (PIR), are implemented to evaluate the allocation solutions obtained by solving a multi-period optimisation problem considering different capital and operating expenditure scenarios in the network. For this purpose, historical datasets for market prices of urea, methanol, and liquid fuels, such as gasoline, diesel, and wax between the years 2005–2018 are also utilised. The outcomes of the scenarios considered, demonstrate that the optimal output for carbon dioxide utilisation ranges from 1.62 Mt/y to 6 Mt/y, which corresponds to a potential annual revenue ranging from 0.48 to 4.35 billion US dollars. Based on the solutions obtained in the Qatar case study, the maximum carbon dioxide utilisation occurs at the Pearl gas-to-liquids plant (up to 16%), whereas the major revenue is generated from the Methanol-Hydrogen plant, contributing as much as 59% of the total revenue in the proposed fixed network design.

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Published in: Journal of Cleaner Production
License: http://creativecommons.org/licenses/by/4.0/
See article on publisher's website: https://dx.doi.org/10.1016/j.jclepro.2020.122974