IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v278y2023ics0360544223010332.html
   My bibliography  Save this article

Three-stage coordinated operation of steel plant-based multi-energy microgrids considering carbon reduction

Author

Listed:
  • Gan, Lei
  • Yang, Tianyu
  • Wang, Bo
  • Chen, Xingying
  • Hua, Haochen
  • Dong, Zhao Yang

Abstract

Steel production is one of the most energy-intensive industries on demand side. Highly distributed energy resource-penetrated multi-energy microgrids (MEMGs) with combined heat and power (CHP) units can supply both electricity and heat while the by-product coal gases during manufacturing can be reused for onsite power supply. However, there is a lack of coordination between steel production and MEMG operation, and the steelmaking process is not fully modelled. Thus, this paper proposes a three-stage coordinated operation method for steel plant-based MEMGs, aiming to minimize the total operating cost. In this method, the steel production is scheduled weekly-ahead to meet the production demand considering carbon emission reduction. Then, the CHP commitment and day-ahead energy transaction are optimized in a day-ahead stage, while the dispatchable device output and intraday energy transaction are determined hourly-ahead based on uncertainty realizations. Accordingly, the steel production is modelled as continuous and discontinuous processes in parallel or series. To tackle the uncertainty of renewable generation, a scenario-based stochastic optimization method is utilized. Moreover, different carbon prices are applied to investigate their effects on steel production. The results show that the proposed method can decrease the operating cost by 14.33% and 1.45% compared with the other two conventional methods.

Suggested Citation

  • Gan, Lei & Yang, Tianyu & Wang, Bo & Chen, Xingying & Hua, Haochen & Dong, Zhao Yang, 2023. "Three-stage coordinated operation of steel plant-based multi-energy microgrids considering carbon reduction," Energy, Elsevier, vol. 278(C).
    • Handle: RePEc:eee:energy:v:278:y:2023:i:c:s0360544223010332
    DOI: 10.1016/j.energy.2023.127639
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223010332
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.127639?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. Sun, Wenqiang & Wang, Qiang & Zhou, Yue & Wu, Jianzhong, 2020. "Material and energy flows of the iron and steel industry: Status quo, challenges and perspectives," Applied Energy, Elsevier, vol. 268(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. Wang, Tonghe & Hua, Haochen & Shi, Tianying & Wang, Rui & Sun, Yizhong & Naidoo, Pathmanathan, 2024. "A bi-level dispatch optimization of multi-microgrid considering green electricity consumption willingness under renewable portfolio standard policy," Applied Energy, Elsevier, vol. 356(C).
    2. Wu, Chun & Chen, Xingying & Hua, Haochen & Yu, Kun & Gan, Lei & Shen, Jun & Ding, Yi, 2024. "Peer-to-peer energy trading optimization for community prosumers considering carbon cap-and-trade," Applied Energy, Elsevier, vol. 358(C).
    3. Kasper, Lukas & Schwarzmayr, Paul & Birkelbach, Felix & Javernik, Florian & Schwaiger, Michael & Hofmann, René, 2024. "A digital twin-based adaptive optimization approach applied to waste heat recovery in green steel production: Development and experimental investigation," Applied Energy, Elsevier, vol. 353(PB).

    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. Yang, Honghua & Ma, Linwei & Li, Zheng, 2023. "Tracing China's steel use from steel flows in the production system to steel footprints in the consumption system," Renewable and Sustainable Energy Reviews, Elsevier, vol. 172(C).
    2. Che, Gelegen & Zhang, Yanyan & Tang, Lixin & Zhao, Shengnan, 2023. "A deep reinforcement learning based multi-objective optimization for the scheduling of oxygen production system in integrated iron and steel plants," Applied Energy, Elsevier, vol. 345(C).
    3. Ma, Shuaiyin & Ding, Wei & Liu, Yang & Ren, Shan & Yang, Haidong, 2022. "Digital twin and big data-driven sustainable smart manufacturing based on information management systems for energy-intensive industries," Applied Energy, Elsevier, vol. 326(C).
    4. Jiang, Sheng-Long & Wang, Meihong & Bogle, I. David L., 2023. "Plant-wide byproduct gas distribution under uncertainty in iron and steel industry via quantile forecasting and robust optimization," Applied Energy, Elsevier, vol. 350(C).
    5. Xiao, Dongliang & Lin, Zhenjia & Chen, Haoyong & Hua, Weiqi & Yan, Jinyue, 2024. "Windfall profit-aware stochastic scheduling strategy for industrial virtual power plant with integrated risk-seeking/averse preferences," Applied Energy, Elsevier, vol. 357(C).
    6. Liu, Shuhan & Sun, Wenqiang, 2023. "Attention mechanism-aided data- and knowledge-driven soft sensors for predicting blast furnace gas generation," Energy, Elsevier, vol. 262(PA).
    7. Yang, Jiaojiao & Sun, Zeyi & Hu, Wenqing & Steinmeister, Louis, 2022. "Joint control of manufacturing and onsite microgrid system via novel neural-network integrated reinforcement learning algorithms," Applied Energy, Elsevier, vol. 315(C).
    8. Barbara Wyrzykowska & Hubert Szczepaniuk & Edyta Karolina Szczepaniuk & Anna Rytko & Marzena Kacprzak, 2024. "Intelligent Energy Management Systems in Industry 5.0: Cybersecurity Applications in Examples," Energies, MDPI, vol. 17(23), pages 1-22, November.
    9. Liu, Weipeng & Zhao, Chunhui & Peng, Tao & Zhang, Zhongwei & Wan, Anping, 2023. "Simulation-assisted multi-process integrated optimization for greentelligent aluminum casting," Applied Energy, Elsevier, vol. 336(C).
    10. Zhang, Liu & Zheng, Zhong & Chai, Yi & Xu, Zhaojun & Zhang, Kaitian & Liu, Yu & Chen, Sujun & Zhao, Liuqiang, 2023. "ASU model with multiple adjustment types for oxygen scheduling concerning pipe pressure safety in steel enterprises," Applied Energy, Elsevier, vol. 343(C).
    11. Zhang, Hanxin & Sun, Wenqiang & Li, Weidong & Ma, Guangyu, 2022. "A carbon flow tracing and carbon accounting method for exploring CO2 emissions of the iron and steel industry: An integrated material–energy–carbon hub," Applied Energy, Elsevier, vol. 309(C).
    12. Chen, Liudong & Liu, Nian & Li, Chenchen & Wu, Lei & Chen, Yubing, 2021. "Multi-party stochastic energy scheduling for industrial integrated energy systems considering thermal delay and thermoelectric coupling," Applied Energy, Elsevier, vol. 304(C).
    13. Sun, Jingchao & Na, Hongming & Yan, Tianyi & Qiu, Ziyang & Yuan, Yuxing & He, Jianfei & Li, Yingnan & Wang, Yisong & Du, Tao, 2021. "A comprehensive assessment on material, exergy and emission networks for the integrated iron and steel industry," Energy, Elsevier, vol. 235(C).
    14. José Edmundo de Almeida Pais & Hugo D. N. Raposo & José Torres Farinha & Antonio J. Marques Cardoso & Pedro Alexandre Marques, 2021. "Optimizing the Life Cycle of Physical Assets through an Integrated Life Cycle Assessment Method," Energies, MDPI, vol. 14(19), pages 1-24, September.
    15. Ma, Shuaiyin & Huang, Yuming & Liu, Yang & Liu, Haizhou & Chen, Yanping & Wang, Jin & Xu, Jun, 2023. "Big data-driven correlation analysis based on clustering for energy-intensive manufacturing industries," Applied Energy, Elsevier, vol. 349(C).
    16. Shuangping Wu & Anjun Xu, 2021. "Calculation Method of Energy Saving in Process Engineering: A Case Study of Iron and Steel Production Process," Energies, MDPI, vol. 14(18), pages 1-15, September.
    17. Tom Savage & Antonio del Rio Chanona & Gbemi Oluleye, 2023. "Robust Market Potential Assessment: Designing optimal policies for low-carbon technology adoption in an increasingly uncertain world," Papers 2304.10203, arXiv.org.
    18. Xu, Tingting & Huo, Zhaoyi & Wang, Wenjing & Xie, Ning & Li, Lili & Liu, Yingjie & Mu, Lin, 2024. "Evaluation of by-product-gas utilization options for carbon reduction at an integrated iron and steel mill," Energy, Elsevier, vol. 294(C).
    19. Na, Hongming & Sun, Jingchao & Qiu, Ziyang & Yuan, Yuxing & Du, Tao, 2022. "Optimization of energy efficiency, energy consumption and CO2 emission in typical iron and steel manufacturing process," Energy, Elsevier, vol. 257(C).
    20. Na, Hongming & Sun, Jingchao & Qiu, Ziyang & He, Jianfei & Yuan, Yuxing & Yan, Tianyi & Du, Tao, 2021. "A novel evaluation method for energy efficiency of process industry — A case study of typical iron and steel manufacturing process," Energy, Elsevier, vol. 233(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:278:y:2023:i:c:s0360544223010332. 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.