Robust Decarbonization Planning of Multi-regional Energy Sector with Flexible Carbon Capture and Storage Systems
Marquez, Ronald Tristan C.
Tapia, John Frederick D.
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How to Cite

Marquez R.T.C., Tapia J.F.D., 2025, Robust Decarbonization Planning of Multi-regional Energy Sector with Flexible Carbon Capture and Storage Systems, Chemical Engineering Transactions, 120, 133-138.
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Abstract

Carbon capture and storage (CCS) plays a vital role in the global transition to a low-carbon energy society, enabling the continued use of fossil fuels until low-carbon energy sources become viable and widely accessible. However, one of the drawbacks is the energy penalty associated with the capture process, requiring compensatory power from renewables to make up for power losses. A potential solution involves bypassing the capture unit during increased electricity demands to recover the generation capacity lost due to capture. This flexible "on/off" mechanism eliminates the requirement of additional generation capacity to compromise the power loss and be economically beneficial by selling more electricity during periods of peak demand. A mixed integer linear program (MILP) model is developed to systematically plan robust CCS retrofit systems of multiple regions with fossil fuel-fired power plant fleets subject to operational adjustments for numerous periods and scenarios. The model considers energy transfer between regions due to insufficient resources to compensate for parasitic power losses in retrofitting capture technologies. The decision for retrofit includes options for flexible and non-flexible capture. Operational adjustments relate to decisions to switch off the flexible capture plants to compensate for the power losses due to capture. A case study is presented to illustrate the model. Results of the case study indicates that up to 70 % reduction in CO2 emissions can be achieved through retrofitting of power plants with CO2 capture option. A reduction of 24 % can still be achieved even if the available compensatory power is reduced by 70 %. In all scenarios, the maximum 30 % increase in energy production costs are all met.
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