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A multi-period optimisation model for planning carbon sequestration retrofits in the electricity sector

Lee, Jui-Yuan
Applied energy 2017 v.198 pp. 12-20
carbon, carbon dioxide, carbon sequestration, case studies, climate change, electricity, electricity costs, energy efficiency, greenhouse gas emissions, linear programming, models, planning, power generation, power plants
Carbon capture and storage (CCS) is a low-carbon technology aiming to prevent carbon dioxide (CO2) generated in large industrial facilities (e.g. power plants) from entering the atmosphere, thus mitigating human-caused climate change. CCS is deemed to be one of the most promising approaches to reduce industrial CO2 emissions on a global scale, in addition to energy efficiency enhancement and increased use of renewables. This paper presents a mathematical programming model for multi-period planning of power plant retrofits with carbon capture (CC) technologies. The model allows for energy penalties due to CC retrofits and the need for compensatory power generation, as well as variations in technological parameters (such as electricity costs) over time. Furthermore, the model is formulated as a mixed integer linear programme (MILP), for which global optimality is guaranteed if a solution exists. Two case studies on carbon-constrained energy sector planning are presented to illustrate the proposed approach. Further analysis is carried out to examine the effect of the cost limit on the total increase in power generation cost.