IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i23p5983-d1531735.html
   My bibliography  Save this article

A Study on CO₂ Emission Reduction Strategies of Coal-Fired Power Plants Based on CCUS-ECBM Source-Sink Matching

Author

Listed:
  • Huawei Yang

    (School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Pan Zhang

    (School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Chenxing Zhang

    (School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Peiwen Zhang

    (School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China)

  • Xiaoyan Jia

    (School of Management Science and Engineering, Shanxi University of Finance and Economics, Taiyuan 030006, China)

Abstract

In order to reduce CO₂ emissions from industrial processes, countries have commenced the vigorous development of CCUS (carbon capture, utilization and storage) technology. The high geographical overlap between China’s extensive coal mining regions and CO 2 -emitting industrial parks provides an opportunity for the more efficient reduction in CO 2 emissions through the development of Enhanced Coal Bed Methane (ECBM) Recovery for use with CCUS technology. Furthermore, the high geographical overlap and proximity of these regions allows for a shift in the transportation mode from pipelines to tanker trucks, which are more cost-effective and logistically advantageous. The issue of transportation must also be considered in order to more accurately assess the constructed cost function and CCUS source–sink matching model for the implementation of ECBM. The constructed model, when considered in conjunction with the actual situation in Shanxi Province, enables the matching of emission sources and sequestration sinks in the province to be realized through the use of ArcGIS 10.8 software, and the actual transport routes are derived as a result. After analyzing the matching results, it is found that the transportation cost accounts for a relatively small proportion of the total cost. In fact, the CH 4 price has a larger impact on the total cost, and a high replacement ratio is not conducive to profitability. When the proportion of CO 2 replacing CH 4 increases from 1 to 3, the price of CH 4 needs to increase from $214.41/t to $643.23/t for sales to be profitable. In addition, electric vehicle transportation costs are lower compared to those of fuel and LNG vehicles, especially for high-mileage and frequent-use scenarios. In order to reduce the total cost, it is recommended to set aside the limitation of transportation distance when matching sources and sinks.

Suggested Citation

  • Huawei Yang & Pan Zhang & Chenxing Zhang & Peiwen Zhang & Xiaoyan Jia, 2024. "A Study on CO₂ Emission Reduction Strategies of Coal-Fired Power Plants Based on CCUS-ECBM Source-Sink Matching," Energies, MDPI, vol. 17(23), pages 1-14, November.
  • Handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:5983-:d:1531735
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/23/5983/pdf
    Download Restriction: no

    File URL: https://www.mdpi.com/1996-1073/17/23/5983/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Wang, Xueyang & Sun, Xiumei & Ahmad, Mahmood & Chen, Jiawei, 2024. "Energy transition, ecological governance, globalization, and environmental sustainability: Insights from the top ten emitting countries," Energy, Elsevier, vol. 292(C).
    2. Li, Ziwen & Yu, Hongjin & Bai, Yansong & Wang, Yinji & Hu, Hongqing & Gao, Yabin & Yan, Fazhi, 2024. "Analysis of reservoir permeability evolution and influencing factors during CO2-Enhanced coalbed methane recovery," Energy, Elsevier, vol. 304(C).
    3. Osamah Alghazwat & Melyse Laud & Yi Liao, 2024. "Thermally Enhanced Acidity for Regeneration of Carbon Dioxide Sorbent," Energies, MDPI, vol. 17(17), pages 1-9, August.
    4. Alessia Di Giuseppe & Alberto Maria Gambelli, 2024. "CO 2 Storage in Deep Oceanic Sediments in the form of Hydrates: Energy Evaluation and Advantages Related to the Use of N 2 -Containing Mixtures," Energies, MDPI, vol. 17(16), pages 1-17, August.
    5. Weilong Wang & Jianlong Wang & Haitao Wu, 2024. "Assessing the potential of energy transition policy in driving renewable energy technology innovation: evidence from new energy demonstration city pilots in China," Economic Change and Restructuring, Springer, vol. 57(5), pages 1-37, October.
    6. Demir, Emrah & Bektaş, Tolga & Laporte, Gilbert, 2012. "An adaptive large neighborhood search heuristic for the Pollution-Routing Problem," European Journal of Operational Research, Elsevier, vol. 223(2), pages 346-359.
    7. Wang, Yihan & Wen, Zongguo & Xu, Mao & Kosajan, Vorada, 2024. "The carbon-energy-water nexus of the carbon capture, utilization, and storage technology deployment schemes: A case study in China's cement industry," Applied Energy, Elsevier, vol. 362(C).
    8. Pohl, Erik & Geldermann, Jutta, 2024. "Selection of multi-criteria energy efficiency and emission abatement portfolios in container terminals," European Journal of Operational Research, Elsevier, vol. 316(1), pages 386-395.
    9. Chenxu Yang & Jintao Wu & Haojun Wu & Yong Jiang & Xinfei Song & Ping Guo & Qixuan Zhang & Hao Tian, 2024. "Research on Gas Injection Limits and Development Methods of CH 4 /CO 2 Synergistic Displacement in Offshore Fractured Condensate Gas Reservoirs," Energies, MDPI, vol. 17(13), pages 1-12, July.
    10. Zhou, Wei & Zhuang, Yan & Chen, Yan, 2024. "How does artificial intelligence affect pollutant emissions by improving energy efficiency and developing green technology," Energy Economics, Elsevier, vol. 131(C).
    Full references (including those not matched with items on IDEAS)

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Lin, Boqiang & Xu, Chongchong, 2024. "The effects of industrial robots on firm energy intensity: From the perspective of technological innovation and electrification," Technological Forecasting and Social Change, Elsevier, vol. 203(C).
    2. Mo, Pengli & Yao, Yu & D’Ariano, Andrea & Liu, Zhiyuan, 2023. "The vehicle routing problem with underground logistics: Formulation and algorithm," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 179(C).
    3. Qianqian Meng & Ziying Jia & Huixue Yang, 2024. "Policy Simulation of the Coordinated Development of Environmental Governance and Urbanization in the Beijing–Tianjin-Hebei Region: A Study Using a Multi-Regional CGE Model," Sustainability, MDPI, vol. 16(23), pages 1-25, November.
    4. Yagcitekin, Bunyamin & Uzunoglu, Mehmet, 2016. "A double-layer smart charging strategy of electric vehicles taking routing and charge scheduling into account," Applied Energy, Elsevier, vol. 167(C), pages 407-419.
    5. Ren, Xuan & Froger, Aurélien & Jabali, Ola & Liang, Gongqian, 2024. "A competitive heuristic algorithm for vehicle routing problems with drones," European Journal of Operational Research, Elsevier, vol. 318(2), pages 469-485.
    6. Kallestad, Jakob & Hasibi, Ramin & Hemmati, Ahmad & Sörensen, Kenneth, 2023. "A general deep reinforcement learning hyperheuristic framework for solving combinatorial optimization problems," European Journal of Operational Research, Elsevier, vol. 309(1), pages 446-468.
    7. Vadlamani, Satish & Hosseini, Seyedmohsen, 2014. "A novel heuristic approach for solving aircraft landing problem with single runway," Journal of Air Transport Management, Elsevier, vol. 40(C), pages 144-148.
    8. Zhao, Lei & Bi, Xinhua & Li, Gendao & Dong, Zhaohui & Xiao, Ni & Zhao, Anni, 2022. "Robust traveling salesman problem with multiple drones: Parcel delivery under uncertain navigation environments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 168(C).
    9. Gläser, Sina, 2022. "A waste collection problem with service type option," European Journal of Operational Research, Elsevier, vol. 303(3), pages 1216-1230.
    10. Florence Blouin & Jean-François Audy & Amina Lamghari, 2022. "Circular Economy in Winter Road Maintenance: A Simulation Study," Sustainability, MDPI, vol. 14(23), pages 1-18, November.
    11. Suzuki, Yoshinori, 2016. "A dual-objective metaheuristic approach to solve practical pollution routing problem," International Journal of Production Economics, Elsevier, vol. 176(C), pages 143-153.
    12. Zandieh, Fatemeh & Ghannadpour, Seyed Farid, 2023. "A comprehensive risk assessment view on interval type-2 fuzzy controller for a time-dependent HazMat routing problem," European Journal of Operational Research, Elsevier, vol. 305(2), pages 685-707.
    13. Büşra Ağan, 2024. "Forecasting Green Technology Diffusion in OECD Economies Through Machine Learning Analysis," Journal of Research in Economics, Politics & Finance, Ersan ERSOY, vol. 9(3), pages 484-502.
    14. Alessia Giulianetti & Marco Gotelli & Anna Sciomachen, 2024. "Comparative Analysis of Train Departure Strategies in a Container Shipment," Logistics, MDPI, vol. 8(3), pages 1-16, September.
    15. Yossiri Adulyasak & Jean-François Cordeau & Raf Jans, 2014. "Optimization-Based Adaptive Large Neighborhood Search for the Production Routing Problem," Transportation Science, INFORMS, vol. 48(1), pages 20-45, February.
    16. Dumez, Dorian & Lehuédé, Fabien & Péton, Olivier, 2021. "A large neighborhood search approach to the vehicle routing problem with delivery options," Transportation Research Part B: Methodological, Elsevier, vol. 144(C), pages 103-132.
    17. Dukkanci, Okan & Karsu, Özlem & Kara, Bahar Y., 2022. "Planning sustainable routes: Economic, environmental and welfare concerns," European Journal of Operational Research, Elsevier, vol. 301(1), pages 110-123.
    18. Amine Masmoudi, M. & Mancini, Simona & Baldacci, Roberto & Kuo, Yong-Hong, 2022. "Vehicle routing problems with drones equipped with multi-package payload compartments," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 164(C).
    19. Singh, Nitish & Dang, Quang-Vinh & Akcay, Alp & Adan, Ivo & Martagan, Tugce, 2022. "A matheuristic for AGV scheduling with battery constraints," European Journal of Operational Research, Elsevier, vol. 298(3), pages 855-873.
    20. Li, Hongqi & Wang, Haotian & Chen, Jun & Bai, Ming, 2020. "Two-echelon vehicle routing problem with time windows and mobile satellites," Transportation Research Part B: Methodological, Elsevier, vol. 138(C), pages 179-201.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jeners:v:17:y:2024:i:23:p:5983-:d:1531735. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.