IDEAS home Printed from https://ideas.repec.org/a/eee/energy/v249y2022ics036054422200617x.html
   My bibliography  Save this article

Electric vehicle charging scheduling considering urgent demand under different charging modes

Author

Listed:
  • Liu, Lu
  • Zhou, Kaile

Abstract

This study proposes a multi-objective electric vehicle (EV) charging scheduling model, aiming at minimizing both the peak-valley load difference of power grid and the total charging cost of EV users. Two modes with different charging power and tariff schemes are investigated for EVs with urgent and unurgent charging demand, respectively. A case study is carried out with 100 EVs under home and public charging mode to demonstrate the effectiveness of the proposed model. Moreover, 200, 300 and 500 EVs are considered to further investigate the influence of number of EVs. The proposed multi-objective charging scheduling model can benefit both the power grid and the EV users, since it can not only reduce the impact of EVs on the stable and safe operation of power grid but also reduce the charging cost of EV users. It also shows that the number of EVs has no significant effect on the reduction ratio of peak-valley load difference and total charging cost. But EV users’ charging behavior affect the effectiveness of coordinated charging scheduling model. The results of this study can better support the operation of power system with high penetration of EVs and the sustainable development of EV industry.

Suggested Citation

  • Liu, Lu & Zhou, Kaile, 2022. "Electric vehicle charging scheduling considering urgent demand under different charging modes," Energy, Elsevier, vol. 249(C).
  • Handle: RePEc:eee:energy:v:249:y:2022:i:c:s036054422200617x
    DOI: 10.1016/j.energy.2022.123714
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S036054422200617X
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.energy.2022.123714?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. Su, Jun & Lie, T.T. & Zamora, Ramon, 2020. "A rolling horizon scheduling of aggregated electric vehicles charging under the electricity exchange market," Applied Energy, Elsevier, vol. 275(C).
    2. Zhou, Kaile & Cheng, Lexin & Lu, Xinhui & Wen, Lulu, 2020. "Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices," Applied Energy, Elsevier, vol. 276(C).
    3. Jian, Linni & Zheng, Yanchong & Xiao, Xinping & Chan, C.C., 2015. "Optimal scheduling for vehicle-to-grid operation with stochastic connection of plug-in electric vehicles to smart grid," Applied Energy, Elsevier, vol. 146(C), pages 150-161.
    4. He, Yi & Liu, Zhaocai & Song, Ziqi, 2020. "Optimal charging scheduling and management for a fast-charging battery electric bus system," Transportation Research Part E: Logistics and Transportation Review, Elsevier, vol. 142(C).
    5. Škugor, Branimir & Deur, Joško, 2015. "Dynamic programming-based optimisation of charging an electric vehicle fleet system represented by an aggregate battery model," Energy, Elsevier, vol. 92(P3), pages 456-465.
    6. Zhou, Kaile & Cheng, Lexin & Wen, Lulu & Lu, Xinhui & Ding, Tao, 2020. "A coordinated charging scheduling method for electric vehicles considering different charging demands," Energy, Elsevier, vol. 213(C).
    7. Luo, Yugong & Zhu, Tao & Wan, Shuang & Zhang, Shuwei & Li, Keqiang, 2016. "Optimal charging scheduling for large-scale EV (electric vehicle) deployment based on the interaction of the smart-grid and intelligent-transport systems," Energy, Elsevier, vol. 97(C), pages 359-368.
    8. Wu, Fei & Sioshansi, Ramteen, 2017. "A two-stage stochastic optimization model for scheduling electric vehicle charging loads to relieve distribution-system constraints," Transportation Research Part B: Methodological, Elsevier, vol. 102(C), pages 55-82.
    9. Brinkel, N.B.G. & Schram, W.L. & AlSkaif, T.A. & Lampropoulos, I. & van Sark, W.G.J.H.M., 2020. "Should we reinforce the grid? Cost and emission optimization of electric vehicle charging under different transformer limits," Applied Energy, Elsevier, vol. 276(C).
    10. Hou, Hui & Xue, Mengya & Xu, Yan & Xiao, Zhenfeng & Deng, Xiangtian & Xu, Tao & Liu, Peng & Cui, Rongjian, 2020. "Multi-objective economic dispatch of a microgrid considering electric vehicle and transferable load," Applied Energy, Elsevier, vol. 262(C).
    11. Liu, Hui & Huang, Kai & Wang, Ni & Qi, Junjian & Wu, Qiuwei & Ma, Shicong & Li, Canbing, 2019. "Optimal dispatch for participation of electric vehicles in frequency regulation based on area control error and area regulation requirement," Applied Energy, Elsevier, vol. 240(C), pages 46-55.
    12. Das, H.S. & Rahman, M.M. & Li, S. & Tan, C.W., 2020. "Electric vehicles standards, charging infrastructure, and impact on grid integration: A technological review," Renewable and Sustainable Energy Reviews, Elsevier, vol. 120(C).
    13. Zheng, Yanchong & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2018. "A novel real-time scheduling strategy with near-linear complexity for integrating large-scale electric vehicles into smart grid," Applied Energy, Elsevier, vol. 217(C), pages 1-13.
    14. Jian, Linni & Zheng, Yanchong & Shao, Ziyun, 2017. "High efficient valley-filling strategy for centralized coordinated charging of large-scale electric vehicles," Applied Energy, Elsevier, vol. 186(P1), pages 46-55.
    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. Hussain, Shahid & Irshad, Reyazur Rashid & Pallonetto, Fabiano & Hussain, Ihtisham & Hussain, Zakir & Tahir, Muhammad & Abimannan, Satheesh & Shukla, Saurabh & Yousif, Adil & Kim, Yun-Su & El-Sayed, H, 2023. "Hybrid coordination scheme based on fuzzy inference mechanism for residential charging of electric vehicles," Applied Energy, Elsevier, vol. 352(C).
    2. Hany Habbak & Mohamed Baza & Mohamed M. E. A. Mahmoud & Khaled Metwally & Ahmed Mattar & Gouda I. Salama, 2022. "Privacy-Preserving Charging Coordination Scheme for Smart Power Grids Using a Blockchain," Energies, MDPI, vol. 15(23), pages 1-23, November.
    3. Tostado-Véliz, Marcos & Jordehi, Ahmad Rezaee & Mansouri, Seyed Amir & Jurado, Francisco, 2023. "A two-stage IGDT-stochastic model for optimal scheduling of energy communities with intelligent parking lots," Energy, Elsevier, vol. 263(PD).
    4. Liu, Shuohan & Cao, Yue & Ni, Qiang & Xu, Lexi & Zhu, Yongdong & Zhang, Xin, 2023. "Towards reservation-based E-mobility service via hybrid of V2V and G2V charging modes," Energy, Elsevier, vol. 268(C).
    5. Pegah Alaee & Julius Bems & Amjad Anvari-Moghaddam, 2023. "A Review of the Latest Trends in Technical and Economic Aspects of EV Charging Management," Energies, MDPI, vol. 16(9), pages 1-28, April.
    6. Zeinab Teimoori & Abdulsalam Yassine, 2022. "A Review on Intelligent Energy Management Systems for Future Electric Vehicle Transportation," Sustainability, MDPI, vol. 14(21), pages 1-23, October.

    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. Zhou, Kaile & Cheng, Lexin & Wen, Lulu & Lu, Xinhui & Ding, Tao, 2020. "A coordinated charging scheduling method for electric vehicles considering different charging demands," Energy, Elsevier, vol. 213(C).
    2. Zou, Wenke & Sun, Yongjun & Gao, Dian-ce & Zhang, Xu & Liu, Junyao, 2023. "A review on integration of surging plug-in electric vehicles charging in energy-flexible buildings: Impacts analysis, collaborative management technologies, and future perspective," Applied Energy, Elsevier, vol. 331(C).
    3. Zhou, Kaile & Cheng, Lexin & Lu, Xinhui & Wen, Lulu, 2020. "Scheduling model of electric vehicles charging considering inconvenience and dynamic electricity prices," Applied Energy, Elsevier, vol. 276(C).
    4. Jasmine Ramsebner & Albert Hiesl & Reinhard Haas, 2020. "Efficient Load Management for BEV Charging Infrastructure in Multi-Apartment Buildings," Energies, MDPI, vol. 13(22), pages 1-23, November.
    5. Ma, Shao-Chao & Yi, Bo-Wen & Fan, Ying, 2022. "Research on the valley-filling pricing for EV charging considering renewable power generation," Energy Economics, Elsevier, vol. 106(C).
    6. Shang, Yitong & Yu, Hang & Niu, Songyan & Shao, Ziyun & Jian, Linni, 2021. "Cyber-physical co-modeling and optimal energy dispatching within internet of smart charging points for vehicle-to-grid operation," Applied Energy, Elsevier, vol. 303(C).
    7. Zheng, Yanchong & Niu, Songyan & Shang, Yitong & Shao, Ziyun & Jian, Linni, 2019. "Integrating plug-in electric vehicles into power grids: A comprehensive review on power interaction mode, scheduling methodology and mathematical foundation," Renewable and Sustainable Energy Reviews, Elsevier, vol. 112(C), pages 424-439.
    8. 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).
    9. Shafqat Jawad & Junyong Liu, 2020. "Electrical Vehicle Charging Services Planning and Operation with Interdependent Power Networks and Transportation Networks: A Review of the Current Scenario and Future Trends," Energies, MDPI, vol. 13(13), pages 1-24, July.
    10. Boud Verbrugge & Mohammed Mahedi Hasan & Haaris Rasool & Thomas Geury & Mohamed El Baghdadi & Omar Hegazy, 2021. "Smart Integration of Electric Buses in Cities: A Technological Review," Sustainability, MDPI, vol. 13(21), pages 1-23, November.
    11. Parlikar, Anupam & Schott, Maximilian & Godse, Ketaki & Kucevic, Daniel & Jossen, Andreas & Hesse, Holger, 2023. "High-power electric vehicle charging: Low-carbon grid integration pathways with stationary lithium-ion battery systems and renewable generation," Applied Energy, Elsevier, vol. 333(C).
    12. Li, Bin & Dong, Xujun & Wen, Jianghui, 2022. "Cooperative-driving control for mixed fleets at wireless charging sections for lane changing behaviour," Energy, Elsevier, vol. 243(C).
    13. Adil Amin & Wajahat Ullah Khan Tareen & Muhammad Usman & Haider Ali & Inam Bari & Ben Horan & Saad Mekhilef & Muhammad Asif & Saeed Ahmed & Anzar Mahmood, 2020. "A Review of Optimal Charging Strategy for Electric Vehicles under Dynamic Pricing Schemes in the Distribution Charging Network," Sustainability, MDPI, vol. 12(23), pages 1-28, December.
    14. Kayhan Alamatsaz & Sadam Hussain & Chunyan Lai & Ursula Eicker, 2022. "Electric Bus Scheduling and Timetabling, Fast Charging Infrastructure Planning, and Their Impact on the Grid: A Review," Energies, MDPI, vol. 15(21), pages 1-39, October.
    15. Geng, Lijun & Lu, Zhigang & He, Liangce & Zhang, Jiangfeng & Li, Xueping & Guo, Xiaoqiang, 2019. "Smart charging management system for electric vehicles in coupled transportation and power distribution systems," Energy, Elsevier, vol. 189(C).
    16. Junaid Bin Fakhrul Islam & Mir Toufikur Rahman & Shameem Ahmad & Tofael Ahmed & G. M. Shafiullah & Hazlie Mokhlis & Mohamadariff Othman & Tengku Faiz Tengku Mohmed Noor Izam & Hasmaini Mohamad & Moham, 2023. "Multi-Objective-Based Charging and Discharging Coordination of Plug-in Electric Vehicle Integrating Capacitor and OLTC," Energies, MDPI, vol. 16(5), pages 1-20, February.
    17. 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).
    18. Ming, Fangzhu & Gao, Feng & Liu, Kun & Li, Xingqi, 2023. "A constrained DRL-based bi-level coordinated method for large-scale EVs charging," Applied Energy, Elsevier, vol. 331(C).
    19. Bagheri Tookanlou, Mahsa & Pourmousavi, S. Ali & Marzband, Mousa, 2023. "A three-layer joint distributionally robust chance-constrained framework for optimal day-ahead scheduling of e-mobility ecosystem," Applied Energy, Elsevier, vol. 331(C).
    20. Zongfei Wang & Patrick Jochem & Hasan Ümitcan Yilmaz & Lei Xu, 2022. "Integrating vehicle‐to‐grid technology into energy system models: Novel methods and their impact on greenhouse gas emissions," Journal of Industrial Ecology, Yale University, vol. 26(2), pages 392-405, April.

    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:249:y:2022:i:c:s036054422200617x. 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.