IDEAS home Printed from https://ideas.repec.org/a/eee/appene/v325y2022ics0306261922011072.html
   My bibliography  Save this article

A temporal–spatial charging coordination scheme incorporating probability of EV charging availability

Author

Listed:
  • Li, Zhikang
  • Ma, Chengbin

Abstract

The charging coordination of electric vehicle (EV) fleets in both temporal domain and spatial domain has attracted growing attention in recent years. Meanwhile, the uncertainties in EV arrival time and total available charging power from charging stations make the coordination problem highly dynamic and challenging. This paper develops a new temporal–spatial EV charging coordination scheme that jointly considers the above two major uncertainties. Firstly, EV charging scheduling (i.e., temporal coordination) is treated as a generalized Nash equilibrium game, in which each EV (including an upcoming EV) prefers to meet its own charging demand with minimized charging cost. The probability of EV charging availability is especially proposed to incorporate the charging demands of the upcoming EVs into the coordination scheme. In order to provide flexibility and private information protection, a distributed receding horizon optimization-based solution is developed, through which the Lagrange multipliers to reach the social equilibrium are determined via an iterative manner. The charging station selection is then recommended that minimizes the objective function over the entire optimization horizon. Finally, simulations under both small-scale and large-scale scenarios effectively demonstrate improved service quality of the EV charging, both in temporal and spatial domains, and avoidance of overload in charging stations. Results in a 150-EV scenario show that, averagely, the proposed method reduces battery SoC mismatch by 43% and increases degree of consistency by 5.9%.

Suggested Citation

  • Li, Zhikang & Ma, Chengbin, 2022. "A temporal–spatial charging coordination scheme incorporating probability of EV charging availability," Applied Energy, Elsevier, vol. 325(C).
    • Handle: RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011072
    DOI: 10.1016/j.apenergy.2022.119838
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0306261922011072
    Download Restriction: Full text for ScienceDirect subscribers only
    File URL: https://libkey.io/10.1016/j.apenergy.2022.119838?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. Francisco Facchinei & Christian Kanzow, 2010. "Generalized Nash Equilibrium Problems," Annals of Operations Research, Springer, vol. 175(1), pages 177-211, March.
    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. Etedadi, Farshad & Kelouwani, Sousso & Agbossou, Kodjo & Henao, Nilson & Laurencelle, François, 2023. "Consensus and sharing based distributed coordination of home energy management systems with demand response enabled baseboard heaters," Applied Energy, Elsevier, vol. 336(C).
    2. Zhao, Zhonghao & Lee, Carman K.M. & Ren, Jingzheng, 2024. "A two-level charging scheduling method for public electric vehicle charging stations considering heterogeneous demand and nonlinear charging profile," Applied Energy, Elsevier, vol. 355(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. Oliver Stein & Nathan Sudermann-Merx, 2016. "The Cone Condition and Nonsmoothness in Linear Generalized Nash Games," Journal of Optimization Theory and Applications, Springer, vol. 170(2), pages 687-709, August.
    2. Nadja Harms & Tim Hoheisel & Christian Kanzow, 2015. "On a Smooth Dual Gap Function for a Class of Player Convex Generalized Nash Equilibrium Problems," Journal of Optimization Theory and Applications, Springer, vol. 166(2), pages 659-685, August.
    3. Lorenzo Lampariello & Simone Sagratella, 2015. "It is a matter of hierarchy: a Nash equilibrium problem perspective on bilevel programming," DIAG Technical Reports 2015-07, Department of Computer, Control and Management Engineering, Universita' degli Studi di Roma "La Sapienza".
    4. Alexey Izmailov & Mikhail Solodov, 2014. "On error bounds and Newton-type methods for generalized Nash equilibrium problems," Computational Optimization and Applications, Springer, vol. 59(1), pages 201-218, October.
    5. Migot, Tangi & Cojocaru, Monica-G., 2020. "A parametrized variational inequality approach to track the solution set of a generalized nash equilibrium problem," European Journal of Operational Research, Elsevier, vol. 283(3), pages 1136-1147.
    6. Denizalp Goktas & Jiayi Zhao & Amy Greenwald, 2023. "T\^atonnement in Homothetic Fisher Markets," Papers 2306.04890, arXiv.org.
    7. Amir Gandomi & Amirhossein Bazargan & Saeed Zolfaghari, 2019. "Designing competitive loyalty programs: a stochastic game-theoretic model to guide the choice of reward structure," Annals of Operations Research, Springer, vol. 280(1), pages 267-298, September.
    8. Vladimir Shikhman, 2022. "On local uniqueness of normalized Nash equilibria," Papers 2205.13878, arXiv.org.
    9. Ming Hu & Masao Fukushima, 2011. "Variational Inequality Formulation of a Class of Multi-Leader-Follower Games," Journal of Optimization Theory and Applications, Springer, vol. 151(3), pages 455-473, December.
    10. Victor Picheny & Mickael Binois & Abderrahmane Habbal, 2019. "A Bayesian optimization approach to find Nash equilibria," Journal of Global Optimization, Springer, vol. 73(1), pages 171-192, January.
    11. Rahman Khorramfar & Osman Ozaltin & Reha Uzsoy & Karl Kempf, 2024. "Coordinating Resource Allocation during Product Transitions Using a Multifollower Bilevel Programming Model," Papers 2401.17402, arXiv.org.
    12. G. C. Bento & J. X. Cruz Neto & P. A. Soares & A. Soubeyran, 2022. "A new regularization of equilibrium problems on Hadamard manifolds: applications to theories of desires," Annals of Operations Research, Springer, vol. 316(2), pages 1301-1318, September.
    13. Corine M. Laan & Judith Timmer & Richard J. Boucherie, 2021. "Non-cooperative queueing games on a network of single server queues," Queueing Systems: Theory and Applications, Springer, vol. 97(3), pages 279-301, April.
    14. Trockel, Walter & Haake, Claus-Jochen, 2017. "Thoughts on social design," Center for Mathematical Economics Working Papers 577, Center for Mathematical Economics, Bielefeld University.
    15. John Cotrina & Javier Zúñiga, 2019. "Quasi-equilibrium problems with non-self constraint map," Journal of Global Optimization, Springer, vol. 75(1), pages 177-197, September.
    16. Sonja Brangewitz & Gaël Giraud, 2012. "Learning by Trading in Infinite Horizon Strategic Market Games with Default," Documents de travail du Centre d'Economie de la Sorbonne 12062r, Université Panthéon-Sorbonne (Paris 1), Centre d'Economie de la Sorbonne, revised Oct 2013.
    17. Yann BRAOUEZEC & Keyvan KIANI, 2021. "Economic foundations of generalized games with shared constraint: Do binding agreements lead to less Nash equilibria?," Working Papers 2021-ACF-06, IESEG School of Management.
    18. E. Allevi & G. Oggioni & R. Riccardi & M. Rocco, 2017. "An equilibrium model for the cement sector: EU-ETS analysis with power contracts," Annals of Operations Research, Springer, vol. 255(1), pages 63-93, August.
    19. Han, Deren & Zhang, Hongchao & Qian, Gang & Xu, Lingling, 2012. "An improved two-step method for solving generalized Nash equilibrium problems," European Journal of Operational Research, Elsevier, vol. 216(3), pages 613-623.
    20. Shipra Singh & Aviv Gibali & Simeon Reich, 2021. "Multi-Time Generalized Nash Equilibria with Dynamic Flow Applications," Mathematics, MDPI, vol. 9(14), pages 1-23, July.

    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:appene:v:325:y:2022:i:c:s0306261922011072. 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.elsevier.com/wps/find/journaldescription.cws_home/405891/description#description .

    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.