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Ethylene cracking furnace TOPSIS energy efficiency evaluation method based on dynamic energy efficiency baselines

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  • Meng, Di
  • Shao, Cheng
  • Zhu, Li

Abstract

It is significant to evaluate accurately energy efficiency of ethylene cracking furnace as the highest energy consumption device in ethylene production. However, previous energy efficiency evaluation methods mainly concentrate on system-level evaluation of ethylene production and fail to consider effects of production load on operation conditions, which are unsuitable for detailed evaluation online. Considering single energy efficiency content and impractical improvement scheme of DEA and unreasonable static baselines in TOPSIS, a modified TOPSIS energy efficiency evaluation method is proposed. A set of new energy efficiency indicators is designed through matter conversion and energy transformation together with matter and energy interaction. To acquire real-time energy efficiency a simulation model of cracking furnace is established by employing radial basis function neural network. To improve evaluation accuracy, the relations among energy efficiency and operation conditions and production load are quantified by calculation formulas of energy efficiency indicators and functions extracted from simulation model. The sequential quadratic programming algorithm is suggested to solve dynamic baselines according to real-time production load by adjusting operation conditions within constraints. Furthermore, optimal operation conditions are provided by searching for maximum comprehensive energy efficiency. Finally, validity of proposed evaluation method is illustrated by applying in a practical cracking furnace.

Suggested Citation

  • 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.
    • Handle: RePEc:eee:energy:v:156:y:2018:i:c:p:620-634
    DOI: 10.1016/j.energy.2018.05.088
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    Cited by:

    1. Milani, M. & Montorsi, L. & Venturelli, M. & Tiscar, J.M. & García-Ten, J., 2019. "A numerical approach for the combined analysis of the dynamic thermal behaviour of an entire ceramic roller kiln and the stress formation in the tiles," Energy, Elsevier, vol. 177(C), pages 543-553.
    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. 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. Elissaios Sarmas & Vangelis Marinakis & Haris Doukas, 2022. "A data-driven multicriteria decision making tool for assessing investments in energy efficiency," Operational Research, Springer, vol. 22(5), pages 5597-5616, November.
    5. 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).
    6. 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).
    7. Zhao, Lu-Tao & Liu, Zhao-Ting & Cheng, Lei, 2021. "How will China's coal industry develop in the future? A quantitative analysis with policy implications," Energy, Elsevier, vol. 235(C).
    8. 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).
    9. 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.
    10. Sheng Zhong & Shuwen Niu & Yipeng Wang, 2018. "Research on Potential Evaluation and Sustainable Development of Rural Biomass Energy in Gansu Province of China," Sustainability, MDPI, vol. 10(10), pages 1-20, October.

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