IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v263y2023ipbs0360544222026147.html
   My bibliography  Save this article

Techno-economic optimization of novel energy-efficient solvent deasphalting process using CO2 as a stripping agent

Author

Listed:
  • Park, Jun Woo
  • Im, Soo Ik
  • Lee, Ki Bong

Abstract

The solvent deasphalting (SDA) process is specifically designed to selectively remove asphaltene from heavy oil feedstocks. However, high energy consumption resulting from the separation processes used to recover the extraction solvent from the mixture of oil products and solvent is a challenge in the SDA process. In this study, a novel SDA process in which the solvent recovery steps were modified by employing carbon dioxide instead of steam as the stripping agent was developed. In addition, the operating and heat integration parameters of the novel CO2-assisted SDA process were optimized using bilevel optimization to minimize the total annualized cost. A genetic algorithm was applied to optimize the process operating variables in the upper-level problem, including the temperature and pressure of solvent recovery units. In the lower-level problem, heat integration parameters—the minimum temperature difference (ΔTmin) and the heat load distribution of hot and cold utilities—were optimized. The optimization results demonstrated that the novel SDA process is more energy-efficient and economical than the conventional SDA process.

Suggested Citation

  • Park, Jun Woo & Im, Soo Ik & Lee, Ki Bong, 2023. "Techno-economic optimization of novel energy-efficient solvent deasphalting process using CO2 as a stripping agent," Energy, Elsevier, vol. 263(PB).
    • Handle: RePEc:eee:energy:v:263:y:2023:i:pb:s0360544222026147
    DOI: 10.1016/j.energy.2022.125728
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222026147
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.125728?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Subramanian, Avinash S.R. & Gundersen, Truls & Adams, Thomas A., 2021. "Optimal design and operation of a waste tire feedstock polygeneration system," Energy, Elsevier, vol. 223(C).
    2. Flórez-Orrego, Daniel & de Oliveira Junior, Silvio, 2016. "On the efficiency, exergy costs and CO2 emission cost allocation for an integrated syngas and ammonia production plant," Energy, Elsevier, vol. 117(P2), pages 341-360.
    3. Zakaria, A. & Ismail, Firas B. & Lipu, M.S. Hossain & Hannan, M.A., 2020. "Uncertainty models for stochastic optimization in renewable energy applications," Renewable Energy, Elsevier, vol. 145(C), pages 1543-1571.
    4. Lai, Yee Qing & Wan Alwi, Sharifah Rafidah & Manan, Zainuddin Abdul, 2019. "Customised retrofit of heat exchanger network combining area distribution and targeted investment," Energy, Elsevier, vol. 179(C), pages 1054-1066.
    5. Ghorbani, Bahram & Shirmohammadi, Reza & Mehrpooya, Mehdi & Hamedi, Mohammad-Hossein, 2018. "Structural, operational and economic optimization of cryogenic natural gas plant using NSGAII two-objective genetic algorithm," Energy, Elsevier, vol. 159(C), pages 410-428.
    6. Stijepovic, Mirko Z. & Papadopoulos, Athanasios I. & Linke, Patrick & Grujic, Aleksandar S. & Seferlis, Panos, 2014. "An exergy composite curves approach for the design of optimum multi-pressure organic Rankine cycle processes," Energy, Elsevier, vol. 69(C), pages 285-298.
    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. Silva, Ana R. & Pousinho, H.M.I. & Estanqueiro, Ana, 2022. "A multistage stochastic approach for the optimal bidding of variable renewable energy in the day-ahead, intraday and balancing markets," Energy, Elsevier, vol. 258(C).
    2. Lim, Juin Yau & Teng, Sin Yong & How, Bing Shen & Nam, KiJeon & Heo, SungKu & Máša, Vítězslav & Stehlík, Petr & Yoo, Chang Kyoo, 2022. "From microalgae to bioenergy: Identifying optimally integrated biorefinery pathways and harvest scheduling under uncertainties in predicted climate," Renewable and Sustainable Energy Reviews, Elsevier, vol. 168(C).
    3. Liu, Jiejie & Li, Yao & Ma, Yanan & Qin, Ruomu & Meng, Xianyang & Wu, Jiangtao, 2023. "Two-layer multiple scenario optimization framework for integrated energy system based on optimal energy contribution ratio strategy," Energy, Elsevier, vol. 285(C).
    4. Ali Dargahi & Khezr Sanjani & Morteza Nazari-Heris & Behnam Mohammadi-Ivatloo & Sajjad Tohidi & Mousa Marzband, 2020. "Scheduling of Air Conditioning and Thermal Energy Storage Systems Considering Demand Response Programs," Sustainability, MDPI, vol. 12(18), pages 1-13, September.
    5. Yan, Rujing & Wang, Jiangjiang & Wang, Jiahao & Tian, Lei & Tang, Saiqiu & Wang, Yuwei & Zhang, Jing & Cheng, Youliang & Li, Yuan, 2022. "A two-stage stochastic-robust optimization for a hybrid renewable energy CCHP system considering multiple scenario-interval uncertainties," Energy, Elsevier, vol. 247(C).
    6. Felipe Godoy Righetto & Carlos Eduardo Keutenedjian Mady, 2023. "Exergy Analysis of a Sugarcane Crop: A Planting-to-Harvest Approach," Sustainability, MDPI, vol. 15(20), pages 1-14, October.
    7. Xiong, Kang & Hu, Weihao & Cao, Di & Li, Sichen & Zhang, Guozhou & Liu, Wen & Huang, Qi & Chen, Zhe, 2023. "Coordinated energy management strategy for multi-energy hub with thermo-electrochemical effect based power-to-ammonia: A multi-agent deep reinforcement learning enabled approach," Renewable Energy, Elsevier, vol. 214(C), pages 216-232.
    8. Huang, Mengdi & Chang, Jianxia & Guo, Aijun & Zhao, Mingzhe & Ye, Xiangmin & Lei, Kaixuan & Peng, Zhiwen & Wang, Yimin, 2023. "Cascade hydropower stations optimal dispatch considering flexible margin in renewable energy power system," Energy, Elsevier, vol. 285(C).
    9. Niu, Jintao & Wang, Jiansheng & Liu, Xueling, 2023. "Thermodynamic and economic analysis of organic Rankine cycle combined with flash cycle and ejector," Energy, Elsevier, vol. 282(C).
    10. Lecompte, S. & Huisseune, H. & van den Broek, M. & De Paepe, M., 2015. "Methodical thermodynamic analysis and regression models of organic Rankine cycle architectures for waste heat recovery," Energy, Elsevier, vol. 87(C), pages 60-76.
    11. Imed Khabbouchi & Dhaou Said & Aziz Oukaira & Idir Mellal & Lyes Khoukhi, 2023. "Machine Learning and Game-Theoretic Model for Advanced Wind Energy Management Protocol (AWEMP)," Energies, MDPI, vol. 16(5), pages 1-15, February.
    12. Silva-Rodriguez, Lina & Sanjab, Anibal & Fumagalli, Elena & Gibescu, Madeleine, 2024. "Light robust co-optimization of energy and reserves in the day-ahead electricity market," Applied Energy, Elsevier, vol. 353(PA).
    13. Fan, Dongming & Ren, Yi & Feng, Qiang & Liu, Yiliu & Wang, Zili & Lin, Jing, 2021. "Restoration of smart grids: Current status, challenges, and opportunities," Renewable and Sustainable Energy Reviews, Elsevier, vol. 143(C).
    14. Li, Jian & Ge, Zhong & Duan, Yuanyuan & Yang, Zhen & Liu, Qiang, 2018. "Parametric optimization and thermodynamic performance comparison of single-pressure and dual-pressure evaporation organic Rankine cycles," Applied Energy, Elsevier, vol. 217(C), pages 409-421.
    15. Dadak, Ali & Mousavi, Seyed Ali & Mehrpooya, Mehdi & Kasaeian, Alibakhsh, 2022. "Techno-economic investigation and dual-objective optimization of a stand-alone combined configuration for the generation and storage of electricity and hydrogen applying hybrid renewable system," Renewable Energy, Elsevier, vol. 201(P1), pages 1-20.
    16. Rosato, Antonello & Panella, Massimo & Andreotti, Amedeo & Mohammed, Osama A. & Araneo, Rodolfo, 2021. "Two-stage dynamic management in energy communities using a decision system based on elastic net regularization," Applied Energy, Elsevier, vol. 291(C).
    17. Deveci, Kaan & Güler, Önder, 2020. "A CMOPSO based multi-objective optimization of renewable energy planning: Case of Turkey," Renewable Energy, Elsevier, vol. 155(C), pages 578-590.
    18. Kang, Lixia & Tang, Jianping & Liu, Yongzhong, 2020. "Optimal design of an organic Rankine cycle system considering the expected variations on heat sources," Energy, Elsevier, vol. 213(C).
    19. Jiao, Feixiang & Zou, Yuan & Zhou, Yi & Zhang, Yanyu & Zhang, Xibeng, 2023. "Energy management for regional microgrids considering energy transmission of electric vehicles between microgrids," Energy, Elsevier, vol. 283(C).
    20. Gonzalez Hernandez, Ana & Lupton, Richard C. & Williams, Chris & Cullen, Jonathan M., 2018. "Control data, Sankey diagrams, and exergy: Assessing the resource efficiency of industrial plants," Applied Energy, Elsevier, vol. 218(C), pages 232-245.

    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:eee:energy:v:263:y:2023:i:pb:s0360544222026147. 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: Catherine Liu (email available below). General contact details of provider: http://www.journals.elsevier.com/energy .

    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.