MINLP model for optimizing electricity production from coal-fired power plants considering carbon management

In order to achieve the reduction in greenhouse gases committed in the Kyoto Protocol, countries must establish control policies and encourage industries to reduce their emissions. Two main options arise in a cap and trade framework: (i) buying/selling emission allowances; and (ii) reducing emissions by investing in abatement technologies. In this context, each industry must choose the best strategy considering its particular features. This work proposes a systematic tool to assist decision-makers in the design of coal-fired energy production with carbon management in existing power plants. Our approach relies on a novel mixed integer non-linear program (MINLP) that minimizes the cost of electricity (COE) for a given price of CO2 allowance on the trade market. We demonstrate the capabilities of this MINLP through a case study that addresses the retrofitting of a coal-fired power plant. Results show that the price of the CO2 allowance on the market that effectively induce the investment in carbon capture falls in the range 22–30 $/tCO2eq depending on the quantity of allowances distributed for free. In this solution, carbon capture is accomplished by implementing the oxy-fuel combustion technology (which is preferred to the post-combustion capture using monoethanolamine as solvent).

Highlight
► We optimize electricity production from coal-fired power plants considering carbon management.
► Our approach relies on a novel mixed integer non-linear programming (MINLP) optimization model.
► We minimize the cost of electricity (COE) for a given price of CO2 allowance in the trade market.
► The allowance price that effectively induce the investment in CCS falls in the range 22–30 $/tCO2eq.
► Oxy-fuel is preferred to the post-combustion capture with MEA in a cap and trade framework.