Skip to main content

Advertisement

SpringerLink
Log in

Charging infrastructure latency optimization

  • Original Paper
  • Published:
Electrical Engineering Aims and scope Submit manuscript

Abstract

In this paper, a new model for charging infrastructure placement with latency optimization is presented. Nodal charging latency coefficients are calculated including the traffic flow over a candidate location and charging time of the charging technology to be installed. Faster charging and lower traffic flow reduce charging latency and vice versa. To exceed optimization problem’s complexity, set-cover modeling is applied to model the road network and the electric vehicle driving trajectories comprising the drivers’ behavior. As a result, optimal number and layout of charging locations are found for the minimal charging infrastructure latency, subject to the charging reliability constraint. Numeric results illustrate integration of the charging latency as part of optimal charging infrastructure placement modeling. An optimal locations layout is shown for applying the optimization model to a 10 × 10 discrete grid with driving trajectories. A comparison is made with a reference model that is user-centric and quality of service based to oversee advantages of the newly infrastructure-centric planning model by minimizing charging latency. Differences are found in optimal layouts with the change of optimal locations.

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

Similar content being viewed by others

References

  1. Jung J, Chow JY, Jayakrishnan R, Park JY (2014) Stochastic dynamic itinerary interception refueling location problem with queue delay for electric taxi charging stations. Transp Res Part C Emerg Technol 40:123–142

    Article  Google Scholar 

  2. Feng W (2021) Spectral analysis of the queueing model for IEEE 802.16 wireless networks. Wirel Pers Commun 121(3):2073–2110

    Article  Google Scholar 

  3. Xiao D, An S, Cai H, Wang J, Cai H (2020) An optimization model for electric vehicle charging infrastructure planning considering queuing behavior with finite queue length. J Energy Storage 29:101317

    Article  Google Scholar 

  4. Davidov S, Pantoš M (2017) Planning of electric vehicle infrastructure based on charging reliability and quality of service. Energy 118:1156–1167

    Article  Google Scholar 

  5. Davidov S, Pantoš M (2019) Optimization model for charging infrastructure planning with electric power system reliability check. Energy 166:886–894

    Article  Google Scholar 

  6. Davidov S, Pantoš M (2017) Stochastic expansion planning of the electric-drive vehicle charging infrastructure. Energy 141:189–201

    Article  Google Scholar 

  7. Davidov S, Pantoš M (2017) Impact of stochastic driving range on the optimal charging infrastructure expansion planning. Energy 141:603–612

    Article  Google Scholar 

  8. Masi DMB, Fischer MJ, Garbin DA (2007) Modeling the performance of low latency queueing for emergency telecommunications. In: 2007 Winter simulation conference, pp 2266–2275. IEEE

  9. Chen H, Abbas R, Cheng P, Shirvanimoghaddam M, Hardjawana W, Bao W, Li Y, Vucetic B (2018) Ultra-reliable low latency cellular networks: use cases, challenges and approaches. IEEE Commun Mag 56(12):119–125

    Article  Google Scholar 

  10. Padmanabhan VN, Mogul JC (1995) Improving HTTP latency. Comput Netw ISDN Syst 28(1–2):25–35

    Article  Google Scholar 

  11. Shih YY, Chung WH, Pang AC, Chiu TC, Wei HY (2016) Enabling low-latency applications in fog-radio access networks. IEEE Netw 31(1):52–58

    Article  Google Scholar 

  12. Al Zishan A, Haji MM, Ardakanian O (2021) Adaptive congestion control for electric vehicle charging in the smart grid. IEEE Trans Smart Grid 12:2439–2449

    Article  Google Scholar 

  13. Petrou K, Quiros-Tortos J, Ochoa LF (2015) Controlling electric vehicle charging points for congestion management of UK LV networks. In: 2015 IEEE power and energy society innovative smart grid technologies conference (ISGT), pp 1–5. IEEE

  14. Caramanis M, Foster JM (2009) Management of electric vehicle charging to mitigate renewable generation intermittency and distribution network congestion. In: Proceedings of the 48h IEEE conference on decision and control (CDC) held jointly with 2009 28th Chinese control conference, pp 4717–4722

  15. Eliasson J, Hultkrantz L, Nerhagen L, Rosqvist LS (2009) The Stockholm congestion–charging trial 2006: overview of effects. Transp Res Part A Policy Pract 43(3):240–250

    Article  Google Scholar 

  16. Tvinnereim E, Haarstad H, Rødeseike A, Bugnion V (2020) Explaining public acceptance of congestion charging: the role of geographical variation in the Bergen case. Case Stud Transp Policy 8(3):992–1001

    Article  Google Scholar 

  17. Baouche F, Billot R, Trigui R, El Faouzi NE (2014) Electric vehicle charging stations allocation model. In: ROADEF-15ème congrès annuel de la Société française de recherche opérationnelle et d’aide à la décision

  18. Chvatal V (1979) A greedy heuristic for the set-covering problem. Math Oper Res 4(3):233–235

    Article  MathSciNet  MATH  Google Scholar 

  19. Toregas C, Swain R, ReVelle C, Bergman L (1971) The location of emergency service facilities. Oper Res 19(6):1363–1373

    Article  MATH  Google Scholar 

  20. Bayram IS, Bayhan S (2020) Location analysis of electric vehicle charging stations for maximum capacity and coverage. In: 2020 IEEE 14th international conference on compatibility, power electronics and power engineering (CPE-POWERENG), vol 1, pp 409–414. IEEE

  21. Sun Z, Gao W, Li B, Wang L (2020) Locating charging stations for electric vehicles. Transp Policy 98:48–54

    Article  Google Scholar 

  22. Kmetec M, Knez M (2022) Electric vehicle charging stations coverage: a study of Slovenia. Tehnički vjesnik 29(1):285–292

    Google Scholar 

  23. Daskin MS (2011) Network and discrete location: models, algorithms, and applications. Wiley

    MATH  Google Scholar 

  24. Danielsson PE (1980) Euclidean distance mapping. Comput Graph Image Process 14(3):227–248

    Article  Google Scholar 

Download references

Author information

Authors and Affiliations

  1. Faculty of Electrical Engineering, University of Ljubljana, Tržaška 25, 1000, Ljubljana, Slovenia

    Sreten Davidov & Miloš Pantoš

Authors
  1. Sreten Davidov
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Miloš Pantoš
    View author publications

    You can also search for this author in PubMed Google Scholar

Corresponding author

Correspondence to Sreten Davidov.

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

Davidov, S., Pantoš, M. Charging infrastructure latency optimization. Electr Eng 105, 719–731 (2023). https://doi.org/10.1007/s00202-022-01693-3

Download citation

  • Received:

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00202-022-01693-3

Keywords

Search

Navigation