IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v17y2024i11p2448-d1398667.html
   My bibliography  Save this article

Collaborative Operation Optimization Scheduling Strategy of Electric Vehicle and Steel Plant Considering V2G

Author

Listed:
  • Weiqi Pan

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Bokang Zou

    (School of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210023, China)

  • Fengtao Li

    (School of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210023, China)

  • Yifu Luo

    (School of Electrical & Automation Engineering, Nanjing Normal University, Nanjing 210023, China)

  • Qirui Chen

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Yuanshi Zhang

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

  • Yang Li

    (School of Electrical Engineering, Southeast University, Nanjing 210096, China)

Abstract

With the shortage of fossil fuels and the increasingly serious problem of environmental pollution, low-carbon industrial production technology has become an effective way to reduce industrial carbon emissions. Electrified steel plants based on electronic arc furnaces (EAF) can reduce most carbon emissions compared with traditional steel production methods, but the production steps have fixed electricity consumption behavior, and impact loads are easily generated in the production process, which has an impact on the stability of the power system. EV has the characteristics of a mobile energy storage unit. When a large number of EVs are connected to the power grid, they can be regarded as distributed energy storage units with scheduling flexibility. Through the orderly scheduling of EVs, the spatial–temporal transfer of EV charging and discharging load can be realized. Therefore, the EV situated in the steel plant’s distribution network node has the capacity to be utilized by providing peak shaving and valley filling services for the steel production load. This study proposes an operation optimization scheduling method for EVs and steel plants. Taking the lowest overall operating cost as the objective, an optimal scheduling model considering EVs operation, steel plant, and distributed generator is established. Based on the IEEE-33 node distribution network model considering distributed generators, the proposed model is simulated and analyzed, and the effectiveness of the EV steel plant operation optimization scheduling strategy is investigated.

Suggested Citation

  • Weiqi Pan & Bokang Zou & Fengtao Li & Yifu Luo & Qirui Chen & Yuanshi Zhang & Yang Li, 2024. "Collaborative Operation Optimization Scheduling Strategy of Electric Vehicle and Steel Plant Considering V2G," Energies, MDPI, vol. 17(11), pages 1-14, May.
    • Handle: RePEc:gam:jeners:v:17:y:2024:i:11:p:2448-:d:1398667
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/17/11/2448/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/17/11/2448/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Zhang, Yuanshi & Qian, Wenyan & Ye, Yujian & Li, Yang & Tang, Yi & Long, Yu & Duan, Meimei, 2023. "A novel non-intrusive load monitoring method based on ResNet-seq2seq networks for energy disaggregation of distributed energy resources integrated with residential houses," Applied Energy, Elsevier, vol. 349(C).
    2. He, Lifu & Yang, Jun & Yan, Jun & Tang, Yufei & He, Haibo, 2016. "A bi-layer optimization based temporal and spatial scheduling for large-scale electric vehicles," Applied Energy, Elsevier, vol. 168(C), pages 179-192.
    3. Mohamed Mokhtar & Mostafa F. Shaaban & Mahmoud H. Ismail & Hatem F. Sindi & Muhyaddin Rawa, 2022. "Reliability Assessment under High Penetration of EVs including V2G Strategy," Energies, MDPI, vol. 15(4), pages 1-17, February.
    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. Aghajani, Saemeh & Kalantar, Mohsen, 2017. "Optimal scheduling of distributed energy resources in smart grids: A complementarity approach," Energy, Elsevier, vol. 141(C), pages 2135-2144.
    2. Ding, Dong & Li, Junhuai & Wang, Huaijun & Wang, Kan & Feng, Jie & Xiao, Ming, 2024. "ApplianceFilter: Targeted electrical appliance disaggregation with prior knowledge fusion," Applied Energy, Elsevier, vol. 365(C).
    3. Moon, Sang-Keun & Kim, Jin-O, 2017. "Balanced charging strategies for electric vehicles on power systems," Applied Energy, Elsevier, vol. 189(C), pages 44-54.
    4. Subramanian, Vignesh & Feijoo, Felipe & Sankaranarayanan, Sriram & Melendez, Kevin & Das, Tapas K., 2022. "A bilevel conic optimization model for routing and charging of EV fleets serving long distance delivery networks," Energy, Elsevier, vol. 251(C).
    5. Yang, Linfeng & Zhang, Chen & Jian, Jinbao & Meng, Ke & Xu, Yan & Dong, Zhaoyang, 2017. "A novel projected two-binary-variable formulation for unit commitment in power systems," Applied Energy, Elsevier, vol. 187(C), pages 732-745.
    6. Sui, Quan & Zhang, Rui & Wu, Chuantao & Wei, Fanrong & Lin, Xiangning & Li, Zhengtian, 2020. "Stochastic scheduling of an electric vessel-based energy management system in pelagic clustering islands," Applied Energy, Elsevier, vol. 259(C).
    7. Gustavo L. Aschidamini & Gederson A. da Cruz & Mariana Resener & Maicon J. S. Ramos & Luís A. Pereira & Bibiana P. Ferraz & Sérgio Haffner & Panos M. Pardalos, 2022. "Expansion Planning of Power Distribution Systems Considering Reliability: A Comprehensive Review," Energies, MDPI, vol. 15(6), pages 1-29, March.
    8. Yan Bao & Yu Luo & Weige Zhang & Mei Huang & Le Yi Wang & Jiuchun Jiang, 2018. "A Bi-Level Optimization Approach to Charging Load Regulation of Electric Vehicle Fast Charging Stations Based on a Battery Energy Storage System," Energies, MDPI, vol. 11(1), pages 1-21, January.
    9. Zhou, Yue & Wang, Chengshan & Wu, Jianzhong & Wang, Jidong & Cheng, Meng & Li, Gen, 2017. "Optimal scheduling of aggregated thermostatically controlled loads with renewable generation in the intraday electricity market," Applied Energy, Elsevier, vol. 188(C), pages 456-465.
    10. Faddel, Samy & Aldeek, A. & Al-Awami, Ali T. & Sortomme, Eric & Al-Hamouz, Zakariya, 2018. "Ancillary Services Bidding for Uncertain Bidirectional V2G Using Fuzzy Linear Programming," Energy, Elsevier, vol. 160(C), pages 986-995.
    11. Samy Faddel & Ali T. Al-Awami & Osama A. Mohammed, 2018. "Charge Control and Operation of Electric Vehicles in Power Grids: A Review," Energies, MDPI, vol. 11(4), pages 1-21, March.
    12. Škugor, Branimir & Deur, Joško, 2016. "A bi-level optimisation framework for electric vehicle fleet charging management," Applied Energy, Elsevier, vol. 184(C), pages 1332-1342.
    13. Yuan, Zhao & Hesamzadeh, Mohammad Reza, 2017. "Hierarchical coordination of TSO-DSO economic dispatch considering large-scale integration of distributed energy resources," Applied Energy, Elsevier, vol. 195(C), pages 600-615.
    14. Jin, Xiaolong & Wu, Qiuwei & Jia, Hongjie, 2020. "Local flexibility markets: Literature review on concepts, models and clearing methods," Applied Energy, Elsevier, vol. 261(C).
    15. Jun Yang & Jiejun Chen & Lei Chen & Feng Wang & Peiyuan Xie & Cilin Zeng, 2016. "A Regional Time-of-Use Electricity Price Based Optimal Charging Strategy for Electrical Vehicles," Energies, MDPI, vol. 9(9), pages 1-18, August.
    16. Zhang, Yachao & Le, Jian & Liao, Xiaobing & Zheng, Feng & Liu, Kaipei & An, Xueli, 2018. "Multi-objective hydro-thermal-wind coordination scheduling integrated with large-scale electric vehicles using IMOPSO," Renewable Energy, Elsevier, vol. 128(PA), pages 91-107.
    17. Liping Huang & Haisheng Li & Chun Sing Lai & Ahmed F. Zobaa & Bang Zhong & Zhuoli Zhao & Loi Lei Lai, 2024. "Electric Vehicle Cluster Scheduling Model for Distribution Systems Considering Reactive-Power Compensation of Charging Piles," Energies, MDPI, vol. 17(11), pages 1-24, May.
    18. Abdulaziz Almutairi, 2022. "Impact Assessment of Diverse EV Charging Infrastructures on Overall Service Reliability," Sustainability, MDPI, vol. 14(20), pages 1-16, October.

    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:gam:jeners:v:17:y:2024:i:11:p:2448-:d:1398667. 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: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    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.