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

Author

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  • Cristóbal, Jorge
  • Guillén-Gosálbez, Gonzalo
  • Jiménez, Laureano
  • Irabien, Angel

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).

Suggested Citation

  • Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano & Irabien, Angel, 2012. "MINLP model for optimizing electricity production from coal-fired power plants considering carbon management," Energy Policy, Elsevier, vol. 51(C), pages 493-501.
    • Handle: RePEc:eee:enepol:v:51:y:2012:i:c:p:493-501
    DOI: 10.1016/j.enpol.2012.08.055
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    References listed on IDEAS

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    1. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Jiménez, Laureano & Irabien, Angel, 2012. "Multi-objective optimization of coal-fired electricity production with CO2 capture," Applied Energy, Elsevier, vol. 98(C), pages 266-272.
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    1. Cristóbal, Jorge & Guillén-Gosálbez, Gonzalo & Kraslawski, Andrzej & Irabien, Angel, 2013. "Stochastic MILP model for optimal timing of investments in CO2 capture technologies under uncertainty in prices," Energy, Elsevier, vol. 54(C), pages 343-351.
    2. Huang, Yi & Yi, Qun & Kang, Jing-Xian & Zhang, Ya-Gang & Li, Wen-Ying & Feng, Jie & Xie, Ke-Chang, 2019. "Investigation and optimization analysis on deployment of China coal chemical industry under carbon emission constraints," Applied Energy, Elsevier, vol. 254(C).
    3. Malladi, Krishna Teja & Sowlati, Taraneh, 2020. "Bi-objective optimization of biomass supply chains considering carbon pricing policies," Applied Energy, Elsevier, vol. 264(C).
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    5. Munguía-López, Aurora del Carmen & González-Bravo, Ramón & Ponce-Ortega, José María, 2019. "Evaluation of carbon and water policies in the optimization of water distribution networks involving power-desalination plants," Applied Energy, Elsevier, vol. 236(C), pages 927-936.
    6. Xiaohua Song & Xiao Jiang & Xubei Zhang & Jinpeng Liu, 2018. "Analysis, Evaluation and Optimization Strategy of China Thermal Power Enterprises’ Business Performance Considering Environmental Costs under the Background of Carbon Trading," Sustainability, MDPI, vol. 10(6), pages 1-27, June.

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