IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v267y2023ics0360544222033643.html
   My bibliography  Save this article

Multi-scale energy efficiency recognition and diagnosis scheme for ethylene production based on a hierarchical multi-indicator system

Author

Listed:
  • Gong, Shixin

Abstract

It is essential to monitor and diagnose the energy efficiency level of ethylene production process to detect any abnormities in the production and adjust production parameters appropriately to ensure the energy efficiency. However, few studies have been carried out concerning the diagnosis of abnormal energy efficiency in the ethylene production with appropriate energy efficiency indicator system from multiple dimensions due to the incompatibility of the diagnosis algorithm and the complexity of this petrochemical production. Therefore, to achieve a comprehensive energy efficiency diagnosis and anomaly analysis for the ethylene production, a multi-scale energy efficiency recognition and diagnosis scheme based on a hierarchical multi-indicator system is proposed. Firstly, a novel recognition scheme for abnormal energy efficiency is conducted from a single-indicator scale to a multi-indicator scale based on a three-level indicator system with respect to the energy and materials flows in the system, process, and equipment level of the ethylene production, so that the energy efficiency of the ethylene production can be monitored in different levels and granularities. Secondly, an integration-decomposition diagnosis method to analyze the energy efficiency is proposed based on the Malmquist production index, where the overall efficiency is decomposed into production efficiency, pure production technical efficiency, and scale efficiency to form a multi-perspective in-depth diagnosis and exploration. Thirdly, a principal component analysis is converted into a preliminary abnormal cause diagnosis algorithm based on statistics so that the multi-scale and multi-level energy efficiency recognition and diagnosis for the ethylene production is achieved. Finally, the effectiveness of the diagnosis scheme is verified by applying it to a Chinese ethylene plant, and the results show that the abnormal energy efficiency can be identified effectively and the consistency of the diagnosis results with the actual situation is approximately 0.818 at least.

Suggested Citation

  • 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).
    • Handle: RePEc:eee:energy:v:267:y:2023:i:c:s0360544222033643
    DOI: 10.1016/j.energy.2022.126478
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544222033643
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2022.126478?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. Yang, Dan & Peng, Xin & Ye, Zhencheng & Lu, Yusheng & Zhong, Weimin, 2021. "Domain adaptation network with uncertainty modeling and its application to the online energy consumption prediction of ethylene distillation processes," Applied Energy, Elsevier, vol. 303(C).
    2. 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.
    3. 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.
    4. Wade D. Cook & Joe Zhu, 2015. "DEA Cross Efficiency," International Series in Operations Research & Management Science, in: Joe Zhu (ed.), Data Envelopment Analysis, edition 127, chapter 2, pages 23-43, Springer.
    5. Han, Yongming & Geng, Zhiqiang & Zhu, Qunxiong & Qu, Yixin, 2015. "Energy efficiency analysis method based on fuzzy DEA cross-model for ethylene production systems in chemical industry," Energy, Elsevier, vol. 83(C), pages 685-695.
    6. 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).
    7. Patterson, Murray G, 1996. "What is energy efficiency? : Concepts, indicators and methodological issues," Energy Policy, Elsevier, vol. 24(5), pages 377-390, May.
    8. Zhu, Li & Li, Zhe & Chen, Junghui, 2021. "Evaluating and predicting energy efficiency using slow feature partial least squares method for large-scale chemical plants," Energy, Elsevier, vol. 230(C).
    9. 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.
    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. Gong, Shixin & Shao, Cheng & Zhu, Li, 2017. "Energy efficiency evaluation in ethylene production process with respect to operation classification," Energy, Elsevier, vol. 118(C), pages 1370-1379.
    12. Han, Yongming & Wu, Hao & Geng, Zhiqiang & Zhu, Qunxiong & Gu, Xiangbai & Yu, Bin, 2020. "Review: Energy efficiency evaluation of complex petrochemical industries," Energy, Elsevier, vol. 203(C).
    13. Shen, Feifei & Zhao, Liang & Wang, Meihong & Du, Wenli & Qian, Feng, 2022. "Data-driven adaptive robust optimization for energy systems in ethylene plant under demand uncertainty," Applied Energy, Elsevier, vol. 307(C).
    14. 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).
    15. Panjapornpon, Chanin & Bardeeniz, Santi & Hussain, Mohamed Azlan, 2023. "Improving energy efficiency prediction under aberrant measurement using deep compensation networks: A case study of petrochemical process," Energy, Elsevier, vol. 263(PC).
    16. Wen, Xuanhao & Cao, Huajun & Hon, Bernard & Chen, Erheng & Li, Hongcheng, 2021. "Energy value mapping: A novel lean method to integrate energy efficiency into production management," Energy, Elsevier, vol. 217(C).
    17. Wang, Lili & Zhao, Jun & Teng, Junfeng & Dong, Shilong & Wang, Yinglong & Xiang, Shuguang & Sun, Xiaoyan, 2022. "Study on an energy-saving process for separation ethylene elycol mixture through heat-pump, heat-integration and ORC driven by waste-heat," Energy, Elsevier, vol. 243(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. Xuan, Di & Jiang, Xiaoyan & Fang, Yan, 2023. "Can globalization and the green economy hedge natural resources? Functions of population growth and financial development in BRICS countries," Resources Policy, Elsevier, vol. 82(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. Ding, Li-Li & Lei, Liang & Zhao, Xin & Calin, Adrian Cantemir, 2020. "Modelling energy and carbon emission performance: A constrained performance index measure," Energy, Elsevier, vol. 197(C).
    2. Abbas Mardani & Dalia Streimikiene & Tomas Balezentis & Muhamad Zameri Mat Saman & Khalil Md Nor & Seyed Meysam Khoshnava, 2018. "Data Envelopment Analysis in Energy and Environmental Economics: An Overview of the State-of-the-Art and Recent Development Trends," Energies, MDPI, vol. 11(8), pages 1-21, August.
    3. Bian, Yiwen & Hu, Miao & Wang, Yousen & Xu, Hao, 2016. "Energy efficiency analysis of the economic system in China during 1986–2012: A parallel slacks-based measure approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 990-998.
    4. 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).
    5. 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.
    6. Tao Xu & Jianxin You & Hui Li & Luning Shao, 2020. "Energy Efficiency Evaluation Based on Data Envelopment Analysis: A Literature Review," Energies, MDPI, vol. 13(14), pages 1-20, July.
    7. 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).
    8. Geng, ZhiQiang & Dong, JunGen & Han, YongMing & Zhu, QunXiong, 2017. "Energy and environment efficiency analysis based on an improved environment DEA cross-model: Case study of complex chemical processes," Applied Energy, Elsevier, vol. 205(C), pages 465-476.
    9. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    10. Ge Huang & Wei Pan & Cheng Hu & Wu-Lin Pan & Wan-Qiang Dai, 2021. "Energy Utilization Efficiency of China Considering Carbon Emissions—Based on Provincial Panel Data," Sustainability, MDPI, vol. 13(2), pages 1-14, January.
    11. Deng, Yuanwang & Liu, Huawei & Zhao, Xiaohuan & E, Jiaqiang & Chen, Jianmei, 2018. "Effects of cold start control strategy on cold start performance of the diesel engine based on a comprehensive preheat diesel engine model," Applied Energy, Elsevier, vol. 210(C), pages 279-287.
    12. He, Yan-Lin & Wang, Ping-Jiang & Zhang, Ming-Qing & Zhu, Qun-Xiong & Xu, Yuan, 2018. "A novel and effective nonlinear interpolation virtual sample generation method for enhancing energy prediction and analysis on small data problem: A case study of Ethylene industry," Energy, Elsevier, vol. 147(C), pages 418-427.
    13. Jafari, Hamed & Safarzadeh, Soroush & Azad-Farsani, Ehsan, 2022. "Effects of governmental policies on energy-efficiency improvement of hydrogen fuel cell cars: A game-theoretic approach," Energy, Elsevier, vol. 254(PC).
    14. Arabi, Behrouz & Munisamy, Susila & Emrouznejad, Ali & Toloo, Mehdi & Ghazizadeh, Mohammad Sadegh, 2016. "Eco-efficiency considering the issue of heterogeneity among power plants," Energy, Elsevier, vol. 111(C), pages 722-735.
    15. Yue Xu & Zebin Wang & Yung-Ho Chiu & Fangrong Ren, 2020. "Research on energy-saving and emissions reduction efficiency in Chinese thermal power companies," Energy & Environment, , vol. 31(5), pages 903-919, August.
    16. Roychaudhuri, Pritam Sankar & Kazantzi, Vasiliki & Foo, Dominic C.Y. & Tan, Raymond R. & Bandyopadhyay, Santanu, 2017. "Selection of energy conservation projects through Financial Pinch Analysis," Energy, Elsevier, vol. 138(C), pages 602-615.
    17. Shermeh, H. Ebrahimzadeh & Najafi, S.E. & Alavidoost, M.H., 2016. "A novel fuzzy network SBM model for data envelopment analysis: A case study in Iran regional power companies," Energy, Elsevier, vol. 112(C), pages 686-697.
    18. Davoudabadi, Reza & Mousavi, Seyed Meysam & Mohagheghi, Vahid, 2021. "A new decision model based on DEA and simulation to evaluate renewable energy projects under interval-valued intuitionistic fuzzy uncertainty," Renewable Energy, Elsevier, vol. 164(C), pages 1588-1601.
    19. Panjapornpon, Chanin & Bardeeniz, Santi & Hussain, Mohamed Azlan, 2023. "Improving energy efficiency prediction under aberrant measurement using deep compensation networks: A case study of petrochemical process," Energy, Elsevier, vol. 263(PC).
    20. Han, Yongming & Liu, Shuang & Geng, Zhiqiang & Gu, Hengchang & Qu, Yixin, 2021. "Energy analysis and resources optimization of complex chemical processes: Evidence based on novel DEA cross-model," Energy, Elsevier, vol. 218(C).

    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:267:y:2023:i:c:s0360544222033643. 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.