(62a) Supply Network Optimization of Carbon Capture, Sequestration and Utilization from Point Sources

Kegl, T., University of Maribor
?u?ek, L., University of Maribor
Kova? Kralj, A., Faculty of Chemistry and Chemical Engineering
Kravanja, Z., University of Maribor
Planet Earth contains different forms of energy sources such as fossil fuels, renewables, and nuclear energy sources. After the industrial revolution, fossil fuels became the main energy sources to meet the permanently increasing energy demand; at the same time they became the main concerns for global warming, as CO2 emissions are generated during their combustion. The concentration of CO2 increased from around 280 ppm in preindustrial times to more than 400 pm today mainly due to fossil fuels (Knutti et al., 2016).

In order to stabilize the global CO2 concentration significant efforts have been undertaken and are still on-going on CO2 capture, sequestration and utilization technologies (Cuellar-Franca and Azapagic, 2015). Various technologies for carbon capture and utilization and various opportunities for carbon sequestration are currently under research (Vooradi et al., 2018). However, technologies for reducing carbon emissions could significantly increase the cost of energy produced. The amount of money that would need to be invested in specific technology or environmental strategy to mitigate CO2 emissions is also so-called eco-cost (Hendriks et al., 2012).

This contribution deals with the development of the conceptual supply network model for minimization of the sum of CO2 emitted in the atmosphere by carbon capture sequestration technologies. Mathematical programming approach is applied for this purpose, and is based on the work by Egieya et al. (2018). A four-layer supply network is formulated as a mixed‑integer linear programming (MILP) model, where the first layer considers the locations of point sources of CO2; the second layer contains carbon capture technologies; the third considers the utilization possibilities and the fourth layer sequestration options. The proposed model and approach are applied on an illustrative case study to demonstrate their capabitilities for minimization of CO2 emissions.


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