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Analysis of CO 2 Emissions in the Whole Production Process of Coal-Fired Power Plant

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  • Han Wang

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Atmospheric Environment Institute, Chinese Research Academy of Environmental Sciences, Ministry of Ecology and Environment (MEE), Beijing 100012, China
    College of Environmental Science and Engineering, North China Electric Power University, Beijing 102206, China)

  • Zhenghui Fu

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China)

  • Shulan Wang

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Operation Management Department, National Joint Research Center for Tacking Key Problems in Air Pollution Control, Beijing 100012, China)

  • Wenjie Zhang

    (State Key Laboratory of Environmental Criteria and Risk Assessment, Chinese Research Academy of Environmental Sciences, Beijing 100012, China
    Atmospheric Environment Institute, Chinese Research Academy of Environmental Sciences, Ministry of Ecology and Environment (MEE), Beijing 100012, China)

Abstract

The linear programming (LP) model has been used to identify a cost-effective strategy for reducing CO 2 emissions in power plants considering coal washing, pollutant removal, and carbon capture processes, thus CO 2 emissions in different production processes can be obtained. The direct emissions (combustion emissions and desulfurization emissions) and indirect emissions (pollutant removal, coal washing, and carbon capture) of CO 2 were all considered in the LP model. Three planning periods were set with different CO 2 emission control desirability to simulate CO 2 emissions of the different reduction requirements. The results can reflect the CO 2 emissions across the whole production process of a coal-fired power plant overall. The simulation results showed that for a coal-fired power plant containing two 1000 MW ultra super-critical sets, when the desirability was 0.9, the CO 2 total emissions were 2.15, 1.84, and 1.59 million tons for the three planning periods. The research results suggest that the methodology of LP combined with fuzzy desirability function is applicable to represent the whole production process of industry sectors such as coal-fired power plants. The government policy makers could predict CO 2 emissions by this method and use the results as a reference to conduct effective industrial and energy structure adjustment.

Suggested Citation

  • Han Wang & Zhenghui Fu & Shulan Wang & Wenjie Zhang, 2021. "Analysis of CO 2 Emissions in the Whole Production Process of Coal-Fired Power Plant," Sustainability, MDPI, vol. 13(19), pages 1-13, October.
  • Handle: RePEc:gam:jsusta:v:13:y:2021:i:19:p:11084-:d:651286
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    References listed on IDEAS

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    1. Long, Xingle & Naminse, Eric Yaw & Du, Jianguo & Zhuang, Jincai, 2015. "Nonrenewable energy, renewable energy, carbon dioxide emissions and economic growth in China from 1952 to 2012," Renewable and Sustainable Energy Reviews, Elsevier, vol. 52(C), pages 680-688.
    2. Wang, Hongye & Su, Bin & Mu, Hailin & Li, Nan & Gui, Shusen & Duan, Ye & Jiang, Bo & Kong, Xue, 2020. "Optimal way to achieve renewable portfolio standard policy goals from the electricity generation, transmission, and trading perspectives in southern China," Energy Policy, Elsevier, vol. 139(C).
    3. Moret, Stefano & Babonneau, Frédéric & Bierlaire, Michel & Maréchal, François, 2020. "Decision support for strategic energy planning: A robust optimization framework," European Journal of Operational Research, Elsevier, vol. 280(2), pages 539-554.
    4. Wang, Hongye & Su, Bin & Mu, Hailin & Li, Nan & Jiang, Bo & Kong, Xue, 2019. "Optimization of electricity generation and interprovincial trading strategies in Southern China," Energy, Elsevier, vol. 174(C), pages 696-707.
    5. Kang, Jidong & Ng, Tsan Sheng & Su, Bin, 2020. "Optimizing electricity mix for CO2 emissions reduction: A robust input-output linear programming model," European Journal of Operational Research, Elsevier, vol. 287(1), pages 280-292.
    6. Lara, Cristiana L. & Mallapragada, Dharik S. & Papageorgiou, Dimitri J. & Venkatesh, Aranya & Grossmann, Ignacio E., 2018. "Deterministic electric power infrastructure planning: Mixed-integer programming model and nested decomposition algorithm," European Journal of Operational Research, Elsevier, vol. 271(3), pages 1037-1054.
    7. Bhadbhade, Navdeep & Zuberi, M. Jibran S. & Patel, Martin K., 2019. "A bottom-up analysis of energy efficiency improvement and CO2 emission reduction potentials for the swiss metals sector," Energy, Elsevier, vol. 181(C), pages 173-186.
    8. Zhao, Xin & Shang, Yuping & Song, Malin, 2020. "Industrial structure distortion and urban ecological efficiency from the perspective of green entrepreneurial ecosystems," Socio-Economic Planning Sciences, Elsevier, vol. 72(C).
    9. Lin, Boqiang & Ouyang, Xiaoling, 2014. "Analysis of energy-related CO2 (carbon dioxide) emissions and reduction potential in the Chinese non-metallic mineral products industry," Energy, Elsevier, vol. 68(C), pages 688-697.
    10. Boffino, Luigi & Conejo, Antonio J. & Sioshansi, Ramteen & Oggioni, Giorgia, 2019. "A two-stage stochastic optimization planning framework to decarbonize deeply electric power systems," Energy Economics, Elsevier, vol. 84(C).
    11. Ruiz, C. & Conejo, A.J., 2015. "Robust transmission expansion planning," European Journal of Operational Research, Elsevier, vol. 242(2), pages 390-401.
    12. Munoz, F.D. & Hobbs, B.F. & Watson, J.-P., 2016. "New bounding and decomposition approaches for MILP investment problems: Multi-area transmission and generation planning under policy constraints," European Journal of Operational Research, Elsevier, vol. 248(3), pages 888-898.
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