Skip to main content
SpringerLink
Log in

Smart Vehicle-to-Grid Operation of Power System based on EV User Behavior

  • Original Article
  • Published:
Journal of Electrical Engineering & Technology Aims and scope Submit manuscript

Abstract

The power system is becoming increasingly complex due to the rise of Renewable Energy Sources (RESs) and Electric Vehicles (EVs), making it more challenging to maintain supply–demand balance. Relying on day-ahead power market planning has limitations in addressing the volatility caused by RESs, resulting in unnecessary reserve capacity consumption. The optimal utilization of flexible resources, including Energy Storage Systems (ESSs), is crucial to tackle these issues. Economic Dispatch (ED) plays a vital role in power system operation and planning, which has become even more significant with the growth of RESs and the widespread adoption of EVs. It introduces dynamic loads due to varying user behaviors, posing operational challenges for the power system. The integration of EVs into the grid through Vehicle-to-Grid (V2G) technology is becoming increasingly important. This paper proposes a comprehensive solution for day-ahead and real-time application, considering the interconnection between EVs and RESs. It presents methods utilizing V2G to minimize operational costs in power systems.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10
Fig. 11
Fig. 12
Fig. 13
Fig. 14
Fig. 15
Fig. 16
Fig. 17
Fig. 18
Fig. 19
Fig. 20

Similar content being viewed by others

References

  1. Lu X, Chan KW, Xia S, Zhou B, Luo X (2019) Security-constrained multiperiod economic dispatch with renewable energy utilizing distributionally robust optimization. IEEE Trans Sustain Energy 10(2):768–779. https://doi.org/10.1109/TSTE.2018.2847419

    Article  ADS  Google Scholar 

  2. Gao S, Liu S, Liu Y, Zhao X, Song TE (2019) Flexible and economic dispatching of AC/DC distribution networks considering uncertainty of wind power. IEEE Access 7:100051–100065. https://doi.org/10.1109/ACCESS.2019.2930248

    Article  Google Scholar 

  3. Habib HUR, Subramaniam U, Waqar A, Farhan BS, Kotb KM, Wang S (2020) Energy cost optimization of hybrid renewables based V2G microgrid considering multi objective function by using artificial bee colony optimization. IEEE Access 8:62076–62093. https://doi.org/10.1109/ACCESS.2020.2984537

    Article  Google Scholar 

  4. Al-Bahrani LT, Horan B, Seyedmahmoudian M, Stojcevski A (2020) Dynamic economic emission dispatch with load demand management for the load demand of electric vehicles during crest shaving and valley filling in smart cities environment. Energy 195:116946

    Article  Google Scholar 

  5. Gao S, Dai R, Cao W, Che Y (2023) combined provision of economic dispatch and frequency regulation by aggregated EVs considering electricity market interaction. IEEE Trans Transp Electrif 9(1):1723–1735. https://doi.org/10.1109/TTE.2022.3195567

    Article  Google Scholar 

  6. Liao Y-T, Lu C-N (2015) Dispatch of EV charging station energy resources for sustainable mobility. IEEE Trans Transp Electrif 1(1):86–93. https://doi.org/10.1109/TTE.2015.2430287

    Article  ADS  Google Scholar 

  7. CENEX (2021) Project sciurus trial insights: findings from 300 domestic V2G units in 2020

  8. . Marra F, Yang GY, Træholt C, Larsen E, Rasmussen CN, You S (2012) Demand profile study of battery electric vehicle under different charging options. In: Proc. IEEE Power Energy Soc. General Meeting. 1–7

  9. Shukla A, Verma K, Kumar R (2017) Multi-stage voltage dependent load modelling of fast charging electric vehicle. In Proc. 6th Int. Conf. Comput. Appl. Elect. Eng.-Recent Adv. pp. 86–91

  10. J. Lofberg (2004) YALMIP: a toolbox for modeling and optimization in MATLA. In: 2004 IEEE International conference on robotics and automation (IEEE Cat. No.04CH37508), Taipei, Taiwan 284–289, doi: https://doi.org/10.1109/CACSD.2004.1393890

  11. Gurobi Optimization, LLC. (2022). Gurobi optimizer, https://www.gurobi.com

  12. The California Independent System Operator (ISO) (2023). Today’s outlook

  13. Zimmerman RD, Murillo-Sánchez CE, Thomas RJ (2011) MATPOWER: steady-state operations, planning, and analysis tools for power systems research and education. IEEE Trans Power Syst 26(1):12–19

    Article  ADS  Google Scholar 

  14. Gush T, Kim C-H, Admasie S, Kim J-S, Song J-S (2021) Optimal smart inverter control for PV and BESS to Improve PV hosting capacity of distribution networks using slime mould algorithm. IEEE Access 9:52164–52176. https://doi.org/10.1109/ACCESS.2021.3070155

    Article  Google Scholar 

  15. Junwei Lu, Jahangir Hossain (2015) Vehicle-to-Grid: linking electric vehicles to the smart grid. Institution of engineering and technology

Download references

Acknowledgements

This paper was supported by Korea institute for Advancement of Technology (KIAT) grant funded by the Korea Government (MOTIE) (P0017305,Human Resource Development Program for Industrial Innovation) and the National Research Foundation of Korea (NRF) grant funded by the Korean government (MSIP) (No. 2021R1A2B5B03086257).

Author information

Authors and Affiliations

  1. Dept. of Electrical Engineering, Polytechnique Montreal, Montreal, Canada

    Jean Mahseredjian

  2. Dept. of Electronic and Electrical Engineering, Sungkyunkwan University, Suwon, Korea

    Chul-Hwan Kim

  3. Dept. of Electrical and Computer Engineering, Sungkyunkwan University, Suwon, Korea

    Gwang-Su Shin & Ho-Young Kim

Authors
  1. Gwang-Su Shin
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Ho-Young Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Jean Mahseredjian
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Chul-Hwan Kim
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding authors

Correspondence to Jean Mahseredjian or Chul-Hwan Kim.

Additional information

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Springer Nature or its licensor (e.g. a society or other partner) holds exclusive rights to this article under a publishing agreement with the author(s) or other rightsholder(s); author self-archiving of the accepted manuscript version of this article is solely governed by the terms of such publishing agreement and applicable law.

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Shin, GS., Kim, HY., Mahseredjian, J. et al. Smart Vehicle-to-Grid Operation of Power System based on EV User Behavior. J. Electr. Eng. Technol. (2024). https://doi.org/10.1007/s42835-024-01797-9

Download citation

  • Received:

  • Revised:

  • Accepted:

  • Published:

  • DOI: https://doi.org/10.1007/s42835-024-01797-9

Keywords

Search

Navigation