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

Abstract: 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).

Other publications of the same journal or congress with authors from the University of Cantabria

 Authorship: Cristóbal J., Guillén-Gosálbez G., Jiménez L., Irabien A.,

 Fuente: Energy Policy, 2012, 51, 493-501

Publisher: Elsevier

 Publication date: 01/12/2012

No. of pages: 9

Publication type: Article

 DOI: 10.1016/j.enpol.2012.08.055

ISSN: 0301-4215

 Spanish project: CTQ2009-14420-C02-01 ; DPI2012-37154-C02-02 ; CTQ2012-37039-C02-01 ; BFU2008-00196 ; ENE2010-14828

Publication Url: https://doi.org/10.1016/j.enpol.2012.08.055

Authorship

JORGE CRISTOBAL GARCIA

GONZALO GUILLEN GOSALBEZ

LAUREANO JIMENEZ ESTELLER