IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v284y2023ics0360544223018881.html
   My bibliography  Save this article

Study on optimal configuration of EV charging stations based on second-order cone

Author

Listed:
  • Yin, Wanjun
  • Ji, Jianbo
  • Qin, Xuan

Abstract

The Electric Vehicle(EV) charging station frequently participates in the daily regulation and operation of the power distribution system, whether the installation position is reasonable and the configuration capacity is appropriate, it will directly affect the operation strategy and operating conditions of the distribution system, and then affect the economic and environmental benefits of the distributed power supply and EV load connected to the power grid, based on the analysis of fuel vehicles, EV travel characteristics and electrical geography coupled state, by fitting the charging data of EV with travel chain, more accurate EV charging load can be obtained. Secondly, the optimal allocation model of EV charging stations is established to optimize the grid loss, and the nonconvex problem is solved by combining the second-order cone relaxation technique with the distflow power flow model, the configuration scheme of EV charging station is obtained. Finally, taking an EV charging scene in a certain area as an example, the optimal configuration of the charging station is simulated by setting up two types of charging station: conventional charging station and conventional charging station and fast charging station, the effectiveness of the proposed configuration scheme is verified. The optimal configuration scheme of EV charging station described in this paper provides a theoretical basis for charging station planning and capacity expansion.

Suggested Citation

  • Yin, Wanjun & Ji, Jianbo & Qin, Xuan, 2023. "Study on optimal configuration of EV charging stations based on second-order cone," Energy, Elsevier, vol. 284(C).
    • Handle: RePEc:eee:energy:v:284:y:2023:i:c:s0360544223018881
    DOI: 10.1016/j.energy.2023.128494
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0360544223018881
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.energy.2023.128494?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. Freeman, Gerad M. & Drennen, Thomas E. & White, Andrew D., 2017. "Can parked cars and carbon taxes create a profit? The economics of vehicle-to-grid energy storage for peak reduction," Energy Policy, Elsevier, vol. 106(C), pages 183-190.
    2. Yin, WanJun & Qin, Xuan, 2022. "Cooperative optimization strategy for large-scale electric vehicle charging and discharging," Energy, Elsevier, vol. 258(C).
    3. Yin, WanJun & Qin, Xuan & Huang, ZhiZhong, 2022. "Optimal dispatching of large-scale electric vehicles into grid based on improved second-order cone," Energy, Elsevier, vol. 254(PB).
    4. Zhang, Jing & Yan, Jie & Liu, Yongqian & Zhang, Haoran & Lv, Guoliang, 2020. "Daily electric vehicle charging load profiles considering demographics of vehicle users," Applied Energy, Elsevier, vol. 274(C).
    5. Yin, WanJun & Ming, ZhengFeng & Wen, Tao, 2021. "Scheduling strategy of electric vehicle charging considering different requirements of grid and users," Energy, Elsevier, vol. 232(C).
    6. Arias, Mariz B. & Bae, Sungwoo, 2016. "Electric vehicle charging demand forecasting model based on big data technologies," Applied Energy, Elsevier, vol. 183(C), pages 327-339.
    7. Burillo, Daniel & Chester, Mikhail V. & Pincetl, Stephanie & Fournier, Eric D. & Reyna, Janet, 2019. "Forecasting peak electricity demand for Los Angeles considering higher air temperatures due to climate change," Applied Energy, Elsevier, vol. 236(C), pages 1-9.
    8. Abu Eldahab, Yasser E. & Saad, Naggar H. & Zekry, Abdalhalim, 2016. "Enhancing the design of battery charging controllers for photovoltaic systems," Renewable and Sustainable Energy Reviews, Elsevier, vol. 58(C), pages 646-655.
    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. Zhang, Meijuan & Yan, Qingyou & Guan, Yajuan & Ni, Da & Agundis Tinajero, Gibran David, 2024. "Joint planning of residential electric vehicle charging station integrated with photovoltaic and energy storage considering demand response and uncertainties," Energy, Elsevier, vol. 298(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. Zhang, Xiaofeng & Kong, Xiaoying & Yan, Renshi & Liu, Yuting & Xia, Peng & Sun, Xiaoqin & Zeng, Rong & Li, Hongqiang, 2023. "Data-driven cooling, heating and electrical load prediction for building integrated with electric vehicles considering occupant travel behavior," Energy, Elsevier, vol. 264(C).
    2. Arshdeep Singh & Shimi Sudha Letha, 2019. "Emerging energy sources for electric vehicle charging station," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 21(5), pages 2043-2082, October.
    3. Yan, Jie & Zhang, Jing & Liu, Yongqian & Lv, Guoliang & Han, Shuang & Alfonzo, Ian Emmanuel Gonzalez, 2020. "EV charging load simulation and forecasting considering traffic jam and weather to support the integration of renewables and EVs," Renewable Energy, Elsevier, vol. 159(C), pages 623-641.
    4. Huang, Wenxin & Wang, Jianguo & Wang, Jianping & Zeng, Haiyan & Zhou, Mi & Cao, Jinxin, 2024. "EV charging load profile identification and seasonal difference analysis via charging sessions data of charging stations," Energy, Elsevier, vol. 288(C).
    5. Li, Xiaohui & Wang, Zhenpo & Zhang, Lei & Sun, Fengchun & Cui, Dingsong & Hecht, Christopher & Figgener, Jan & Sauer, Dirk Uwe, 2023. "Electric vehicle behavior modeling and applications in vehicle-grid integration: An overview," Energy, Elsevier, vol. 268(C).
    6. Jian Chen & Fangyi Li & Ranran Yang & Dawei Ma, 2020. "Impacts of Increasing Private Charging Piles on Electric Vehicles’ Charging Profiles: A Case Study in Hefei City, China," Energies, MDPI, vol. 13(17), pages 1-17, August.
    7. Kandpal, Bakul & Pareek, Parikshit & Verma, Ashu, 2022. "A robust day-ahead scheduling strategy for EV charging stations in unbalanced distribution grid," Energy, Elsevier, vol. 249(C).
    8. Duggal, Angel Swastik & Singh, Rajesh & Gehlot, Anita & Gupta, Lovi Raj & Akram, Sheik Vaseem & Prakash, Chander & Singh, Sunpreet & Kumar, Raman, 2021. "Infrastructure, mobility and safety 4.0: Modernization in road transportation," Technology in Society, Elsevier, vol. 67(C).
    9. Jiaan Zhang & Chenyu Liu & Leijiao Ge, 2022. "Short-Term Load Forecasting Model of Electric Vehicle Charging Load Based on MCCNN-TCN," Energies, MDPI, vol. 15(7), pages 1-25, April.
    10. Khan, Waqas & Somers, Ward & Walker, Shalika & de Bont, Kevin & Van der Velden, Joep & Zeiler, Wim, 2023. "Comparison of electric vehicle load forecasting across different spatial levels with incorporated uncertainty estimation," Energy, Elsevier, vol. 283(C).
    11. Okay, Kamil & Eray, Sermet & Eray, Aynur, 2022. "Development of prototype battery management system for PV system," Renewable Energy, Elsevier, vol. 181(C), pages 1294-1304.
    12. Burillo, Daniel & Chester, Mikhail V. & Pincetl, Stephanie & Fournier, Eric, 2019. "Electricity infrastructure vulnerabilities due to long-term growth and extreme heat from climate change in Los Angeles County," Energy Policy, Elsevier, vol. 128(C), pages 943-953.
    13. Zhao, Yang & Jiang, Ziyue & Chen, Xinyu & Liu, Peng & Peng, Tianduo & Shu, Zhan, 2023. "Toward environmental sustainability: data-driven analysis of energy use patterns and load profiles for urban electric vehicle fleets," Energy, Elsevier, vol. 285(C).
    14. Buzna, Luboš & De Falco, Pasquale & Ferruzzi, Gabriella & Khormali, Shahab & Proto, Daniela & Refa, Nazir & Straka, Milan & van der Poel, Gijs, 2021. "An ensemble methodology for hierarchical probabilistic electric vehicle load forecasting at regular charging stations," Applied Energy, Elsevier, vol. 283(C).
    15. Müller, Mathias & Blume, Yannic & Reinhard, Janis, 2022. "Impact of behind-the-meter optimised bidirectional electric vehicles on the distribution grid load," Energy, Elsevier, vol. 255(C).
    16. Lee, Yerim & Hur, Jin, 2019. "A simultaneous approach implementing wind-powered electric vehicle charging stations for charging demand dispersion," Renewable Energy, Elsevier, vol. 144(C), pages 172-179.
    17. Mariz B. Arias & Sungwoo Bae, 2021. "Solar Photovoltaic Power Prediction Using Big Data Tools," Sustainability, MDPI, vol. 13(24), pages 1-19, December.
    18. Li, Yanbin & Wang, Jiani & Wang, Weiye & Liu, Chang & Li, Yun, 2023. "Dynamic pricing based electric vehicle charging station location strategy using reinforcement learning," Energy, Elsevier, vol. 281(C).
    19. Lixing Chen & Xueliang Huang & Hong Zhang, 2020. "Modeling the Charging Behaviors for Electric Vehicles Based on Ternary Symmetric Kernel Density Estimation," Energies, MDPI, vol. 13(7), pages 1-17, March.
    20. Wang, Yue & Shi, Jianmai & Wang, Rui & Liu, Zhong & Wang, Ling, 2018. "Siting and sizing of fast charging stations in highway network with budget constraint," Applied Energy, Elsevier, vol. 228(C), pages 1255-1271.

    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:284:y:2023:i:c:s0360544223018881. 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.