IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v217y2021ics0360544220325081.html
   My bibliography  Save this article

Energy efficiency enhancement of energy and materials for ethylene production based on two-stage coordinated optimization scheme

Author

Listed:
  • Gong, Shixin
  • Shao, Cheng
  • Zhu, Li

Abstract

Nowadays with the growing requirements of sustainable development, energy efficiency enhancement plays a crucial role in the petrochemical industries. In fact, the energy efficiency level depends on the coordination management of energy and materials. Therefore, a two-stage optimization scheme with respect to coordination of energy and materials from the entire process to the key sub-process is proposed for improving energy efficiency level of ethylene production. Firstly, a data-driven model for feedstock and plant-level economic indicators and is established by extreme learning machine (ELM) integrated domain adaptive manifold regularization (DAMR) and particle swarm optimization (PSO), called DAMR-PSO-ELM. Secondly, a multi-objective optimization model for feedstock proportions is established and a cascading-priority weight strategy is made for obtaining the optimal feedstock proportions under the different market demands. Finally, fuel–feedstock ratio optimization models for cracking furnaces are built with respect to the obtained optimal proportions, and an improved elitist teaching–learning-based optimization algorithm is proposed to acquire the optimal fuel. The effectiveness and feasibility of the proposed coordinated optimization scheme are validated from a practical ethylene plant, results show that energy consumption of cracking production is reduced by 4.89% and energy efficiency of the entire ethylene process is increased by 6.82% on average.

Suggested Citation

  • Gong, Shixin & Shao, Cheng & Zhu, Li, 2021. "Energy efficiency enhancement of energy and materials for ethylene production based on two-stage coordinated optimization scheme," Energy, Elsevier, vol. 217(C).
    • Handle: RePEc:eee:energy:v:217:y:2021:i:c:s0360544220325081
    DOI: 10.1016/j.energy.2020.119401
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544220325081
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2020.119401?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. E, Jiaqiang & Zhao, Xiaohuan & Liu, Guanlin & Zhang, Bin & Zuo, Qingsong & Wei, Kexiang & Li, Hongmei & Han, Dandan & Gong, Jinke, 2019. "Effects analysis on optimal microwave energy consumption in the heating process of composite regeneration for the diesel particulate filter," Applied Energy, Elsevier, vol. 254(C).
    2. Yu, Kunjie & While, Lyndon & Reynolds, Mark & Wang, Xin & Liang, J.J. & Zhao, Liang & Wang, Zhenlei, 2018. "Multiobjective optimization of ethylene cracking furnace system using self-adaptive multiobjective teaching-learning-based optimization," Energy, Elsevier, vol. 148(C), pages 469-481.
    3. Gong, Shixin & Shao, Cheng & Zhu, Li, 2019. "Multi-level and multi-granularity energy efficiency diagnosis scheme for ethylene production process," Energy, Elsevier, vol. 170(C), pages 1151-1169.
    4. Meng, Di & Shao, Cheng & Zhu, Li, 2018. "Ethylene cracking furnace TOPSIS energy efficiency evaluation method based on dynamic energy efficiency baselines," Energy, Elsevier, vol. 156(C), pages 620-634.
    5. Ren, Tao & Patel, Martin & Blok, Kornelis, 2006. "Olefins from conventional and heavy feedstocks: Energy use in steam cracking and alternative processes," Energy, Elsevier, vol. 31(4), pages 425-451.
    6. Gong, Shixin & Shao, Cheng & Zhu, Li, 2019. "An energy efficiency integration optimization scheme for ethylene production with respect to multiple working conditions," Energy, Elsevier, vol. 182(C), pages 280-295.
    7. Zhang, Bin & E, Jiaqiang & Gong, Jinke & Yuan, Wenhua & Zuo, Wei & Li, Yu & Fu, Jun, 2016. "Multidisciplinary design optimization of the diesel particulate filter in the composite regeneration process," Applied Energy, Elsevier, vol. 181(C), pages 14-28.
    8. Yoram Wind & Thomas L. Saaty, 1980. "Marketing Applications of the Analytic Hierarchy Process," Management Science, INFORMS, vol. 26(7), pages 641-658, July.
    9. Geng, Zhiqiang & Zhang, Yanhui & Li, Chengfei & Han, Yongming & Cui, Yunfei & Yu, Bin, 2020. "Energy optimization and prediction modeling of petrochemical industries: An improved convolutional neural network based on cross-feature," Energy, Elsevier, vol. 194(C).
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    Cited by:

    1. Li, Xiuquan & Yang, Zhongqing & Zhang, Li & He, Ziqiang & Fang, Ruiming & Wang, Ziqi & Yan, Yunfei & Ran, Jingyu, 2021. "Effect of Pd doping in (Fe/Ni)/CeO2 catalyst for the reaction path in CO2 oxidative ethane dehydrogenation/reforming," Energy, Elsevier, vol. 234(C).
    2. Gong, Shixin, 2023. "Multi-scale energy efficiency recognition and diagnosis scheme for ethylene production based on a hierarchical multi-indicator system," Energy, Elsevier, vol. 267(C).

    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. Meng, Di & Shao, Cheng & Zhu, Li, 2022. "Two-level comprehensive energy-efficiency quantitative diagnosis scheme for ethylene-cracking furnace with multi-working-condition of fault and exception operation," Energy, Elsevier, vol. 239(PA).
    2. Gong, Shixin, 2023. "Multi-scale energy efficiency recognition and diagnosis scheme for ethylene production based on a hierarchical multi-indicator system," Energy, Elsevier, vol. 267(C).
    3. Zhao, Xiaohuan & E, Jiaqiang & Zhang, Zhiqing & Chen, Jingwei & Liao, Gaoliang & Zhang, Feng & Leng, Erwei & Han, Dandan & Hu, Wenyu, 2020. "A review on heat enhancement in thermal energy conversion and management using Field Synergy Principle," Applied Energy, Elsevier, vol. 257(C).
    4. Barbie, Eli & Rabinovici, Raul & Kuperman, Alon, 2020. "Analytic formulation and optimization of weighted total harmonic distortion in single-phase staircase modulated multilevel inverters," Energy, Elsevier, vol. 199(C).
    5. Ye, Jiahao & E, Jiaqiang & Peng, Qingguo, 2023. "Effects of porosity setting and multilayers of diesel particulate filter on the improvement of regeneration performance," Energy, Elsevier, vol. 263(PE).
    6. Gang Wu & Guoda Feng & Yuelin Li & Tao Ling & Xuejun Peng & Zhilai Su & Xiaohuan Zhao, 2024. "A Review of Thermal Energy Management of Diesel Exhaust after-Treatment Systems Technology and Efficiency Enhancement Approaches," Energies, MDPI, vol. 17(3), pages 1-32, January.
    7. Zuo, Qingsong & Xie, Yong & E, Jiaqiang & Zhu, Xinning & Zhang, Bin & Tang, Yuanyou & Zhu, Guohui & Wang, Zhiqi & Zhang, Jianping, 2020. "Effect of different exhaust parameters on NO conversion efficiency enhancement of a dual-carrier catalytic converter in the gasoline engine," Energy, Elsevier, vol. 191(C).
    8. Zhu, Xinning & Zuo, Qingsong & Tang, Yuanyou & Xie, Yong & Shen, Zhuang & Yang, Xiaomei, 2022. "Performance enhancement of equilibrium regeneration in a gasoline particulate filter based on field synergy theory," Energy, Elsevier, vol. 244(PA).
    9. Miroslav Variny & Kristián Hanus & Marek Blahušiak & Patrik Furda & Peter Illés & Ján Janošovský, 2021. "Energy and Environmental Assessment of Steam Management Optimization in an Ethylene Plant," IJERPH, MDPI, vol. 18(22), pages 1-17, November.
    10. Geng, Zhiqiang & Zeng, Rongfu & Han, Yongming & Zhong, Yanhua & Fu, Hua, 2019. "Energy efficiency evaluation and energy saving based on DEA integrated affinity propagation clustering: Case study of complex petrochemical industries," Energy, Elsevier, vol. 179(C), pages 863-875.
    11. Zuo, Hongyan & Zhang, Bin & Huang, Zhonghua & Wei, Kexiang & Zhu, Hong & Tan, Jiqiu, 2022. "Effect analysis on SOC values of the power lithium manganate battery during discharging process and its intelligent estimation," Energy, Elsevier, vol. 238(PB).
    12. Agarwal, Avinash Kumar & Mustafi, Nirendra Nath, 2021. "Real-world automotive emissions: Monitoring methodologies, and control measures," Renewable and Sustainable Energy Reviews, Elsevier, vol. 137(C).
    13. Zhao, Xiaohuan & Zuo, Hongyan & Jia, Guohai, 2022. "Effect analysis on pressure sensitivity performance of diesel particulate filter for heavy-duty truck diesel engine by the nonlinear soot regeneration combustion pressure model," Energy, Elsevier, vol. 257(C).
    14. Banai, Reza, 2010. "Evaluation of land use-transportation systems with the Analytic Network Process," The Journal of Transport and Land Use, Center for Transportation Studies, University of Minnesota, vol. 3(1), pages 85-112.
    15. Fatih Yiğit & Şakir Esnaf, 2021. "A new Fuzzy C-Means and AHP-based three-phased approach for multiple criteria ABC inventory classification," Journal of Intelligent Manufacturing, Springer, vol. 32(6), pages 1517-1528, August.
    16. Rachele Corticelli & Margherita Pazzini & Cecilia Mazzoli & Claudio Lantieri & Annarita Ferrante & Valeria Vignali, 2022. "Urban Regeneration and Soft Mobility: The Case Study of the Rimini Canal Port in Italy," Sustainability, MDPI, vol. 14(21), pages 1-27, November.
    17. Lin, Sheng-Hau & Zhao, Xiaofeng & Wu, Jiuxing & Liang, Fachao & Li, Jia-Hsuan & Lai, Ren-Ji & Hsieh, Jing-Chzi & Tzeng, Gwo-Hshiung, 2021. "An evaluation framework for developing green infrastructure by using a new hybrid multiple attribute decision-making model for promoting environmental sustainability," Socio-Economic Planning Sciences, Elsevier, vol. 75(C).
    18. Pishchulov, Grigory & Trautrims, Alexander & Chesney, Thomas & Gold, Stefan & Schwab, Leila, 2019. "The Voting Analytic Hierarchy Process revisited: A revised method with application to sustainable supplier selection," International Journal of Production Economics, Elsevier, vol. 211(C), pages 166-179.
    19. Seung-Jin Han & Won-Jae Lee & So-Hee Kim & Sang-Hoon Yoon & Hyunwoong Pyun, 2022. "Assessing Expected Long-term Benefits for the Olympic Games: Delphi-AHP Approach from Korean Olympic Experts," SAGE Open, , vol. 12(4), pages 21582440221, December.
    20. Denys Yemshanov & Frank H. Koch & Yakov Ben‐Haim & Marla Downing & Frank Sapio & Marty Siltanen, 2013. "A New Multicriteria Risk Mapping Approach Based on a Multiattribute Frontier Concept," Risk Analysis, John Wiley & Sons, vol. 33(9), pages 1694-1709, September.

    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:217:y:2021:i:c:s0360544220325081. 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.