IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v14y2021i6p1614-d516845.html
   My bibliography  Save this article

Distribution Network Hierarchically Partitioned Optimization Considering Electric Vehicle Orderly Charging with Isolated Bidirectional DC-DC Converter Optimal Efficiency Model

Author

Listed:
  • Qiushi Zhang

    (College of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Jian Zhao

    (College of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Xiaoyu Wang

    (College of Electric Power Engineering, Shanghai University of Electric Power, Shanghai 200090, China)

  • Li Tong

    (State Grid Zhejiang Electric Power Research Institute, Hangzhou 310006, China)

  • Hang Jiang

    (State Grid Zhejiang Electric Power Research Institute, Hangzhou 310006, China)

  • Jinhui Zhou

    (State Grid Zhejiang Electric Power Research Institute, Hangzhou 310006, China)

Abstract

The access of large-scale electric vehicles (EVs) will increase the network loss of medium voltage distribution network, which can be alleviated by adjusting the network structure and orderly charging for EVs. However, it is difficult to accurately evaluate the charging efficiency in the orderly charging of electric vehicle (EV), which will cause the scheduling model to be insufficiently accurate. Therefore, this paper proposes an EV double-layer scheduling model based on the isolated bidirectional DC–DC (IBDC) converter optimal efficiency model, and establishes the hierarchical and partitioned optimization model with feeder–branch–load layer. Firstly, based on the actual topology of medium voltage distribution network, a dynamic reconfiguration model between switching stations is established with the goal of load balancing. Secondly, with the goal of minimizing the branch layer network loss, a dynamic reconstruction model under the switch station is established, and the chaotic niche particle swarm optimization is proposed to improve the global search capability and iteration speed. Finally, the power transmission loss model of IBDC converter is established, and the optimal phase shift parameter is determined to formulate the double-layer collaborative optimization operation strategy of electric vehicles. The example verifies that the above model can improve the system load balancing degree and reduce the operation loss of medium voltage distribution network.

Suggested Citation

  • Qiushi Zhang & Jian Zhao & Xiaoyu Wang & Li Tong & Hang Jiang & Jinhui Zhou, 2021. "Distribution Network Hierarchically Partitioned Optimization Considering Electric Vehicle Orderly Charging with Isolated Bidirectional DC-DC Converter Optimal Efficiency Model," Energies, MDPI, vol. 14(6), pages 1-20, March.
    • Handle: RePEc:gam:jeners:v:14:y:2021:i:6:p:1614-:d:516845
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/14/6/1614/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/14/6/1614/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Teketay Mulu Beza & Yen-Chih Huang & Cheng-Chien Kuo, 2020. "A Hybrid Optimization Approach for Power Loss Reduction and DG Penetration Level Increment in Electrical Distribution Network," Energies, MDPI, vol. 13(22), pages 1-17, November.
    2. Saad Ullah Khan & Khawaja Khalid Mehmood & Zunaib Maqsood Haider & Muhammad Kashif Rafique & Muhammad Omer Khan & Chul-Hwan Kim, 2021. "Coordination of Multiple Electric Vehicle Aggregators for Peak Shaving and Valley Filling in Distribution Feeders," Energies, MDPI, vol. 14(2), pages 1-16, January.
    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. Daud Mustafa Minhas & Josef Meiers & Georg Frey, 2022. "Electric Vehicle Battery Storage Concentric Intelligent Home Energy Management System Using Real Life Data Sets," Energies, MDPI, vol. 15(5), pages 1-29, February.
    2. Rupesh Jha & Mattia Forato & Satya Prakash & Hemant Dashora & Giuseppe Buja, 2022. "An Analysis-Supported Design of a Single Active Bridge (SAB) Converter," Energies, MDPI, vol. 15(2), pages 1-22, January.

    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. Shahid Nawaz Khan & Syed Ali Abbas Kazmi & Abdullah Altamimi & Zafar A. Khan & Mohammed A. Alghassab, 2022. "Smart Distribution Mechanisms—Part I: From the Perspectives of Planning," Sustainability, MDPI, vol. 14(23), pages 1-109, December.
    2. Abdullah Shaheen & Ragab El-Sehiemy & Salah Kamel & Ali Selim, 2022. "Optimal Operational Reliability and Reconfiguration of Electrical Distribution Network Based on Jellyfish Search Algorithm," Energies, MDPI, vol. 15(19), pages 1-14, September.
    3. Ezequiel C. Pereira & Carlos H. N. R. Barbosa & João A. Vasconcelos, 2023. "Distribution Network Reconfiguration Using Iterative Branch Exchange and Clustering Technique," Energies, MDPI, vol. 16(5), pages 1-20, March.
    4. Saleh Aghajan-Eshkevari & Sasan Azad & Morteza Nazari-Heris & Mohammad Taghi Ameli & Somayeh Asadi, 2022. "Charging and Discharging of Electric Vehicles in Power Systems: An Updated and Detailed Review of Methods, Control Structures, Objectives, and Optimization Methodologies," Sustainability, MDPI, vol. 14(4), pages 1-31, February.
    5. Muhammad Azhar Hassan & Saad Ullah Khan & Muhammad Fahad Zia & Azka Sardar & Khawaja Khalid Mehmood & Fiaz Ahmad, 2023. "Demand-Side Management and Its Impact on the Growing Circular Debt of Pakistan’s Energy Sector," Energies, MDPI, vol. 16(15), pages 1-20, July.
    6. Morteza Nazari-Heris & Mehdi Abapour & Behnam Mohammadi-Ivatloo, 2022. "An Updated Review and Outlook on Electric Vehicle Aggregators in Electric Energy Networks," Sustainability, MDPI, vol. 14(23), pages 1-24, November.
    7. Robert Pietracho & Christoph Wenge & Przemyslaw Komarnicki & Leszek Kasprzyk, 2022. "Multi-Criterial Assessment of Electric Vehicle Integration into the Commercial Sector—A Case Study," Energies, MDPI, vol. 16(1), pages 1-29, December.
    8. Daud Mustafa Minhas & Josef Meiers & Georg Frey, 2022. "Electric Vehicle Battery Storage Concentric Intelligent Home Energy Management System Using Real Life Data Sets," Energies, MDPI, vol. 15(5), pages 1-29, February.
    9. Edy Quintana & Esteban Inga, 2022. "Optimal Reconfiguration of Electrical Distribution System Using Heuristic Methods with Geopositioning Constraints," Energies, MDPI, vol. 15(15), pages 1-20, July.
    10. Zbigniew Kłosowski & Łukasz Mazur, 2023. "Influence of the Type of Receiver on Electrical Energy Losses in Power Grids," Energies, MDPI, vol. 16(15), pages 1-22, July.
    11. Sunday Adeleke Salimon & Gafari Abiola Adepoju & Isaiah Gbadegesin Adebayo & Harun Or Rashid Howlader & Samson Oladayo Ayanlade & Oludamilare Bode Adewuyi, 2023. "Impact of Distributed Generators Penetration Level on the Power Loss and Voltage Profile of Radial Distribution Networks," Energies, MDPI, vol. 16(4), pages 1-32, February.

    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:14:y:2021:i:6:p:1614-:d:516845. 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.