Modelling congestion and price competition in EV charging markets

Qi Wang; Dongmo Zhang; Bo Du

doi:10.1007/978-3-031-77367-9_10

Modelling congestion and price competition in EV charging markets

Qi Wang
, Dongmo Zhang
, Bo Du

School of Computer, Data & Mathematical Sciences

Western Sydney University
Griffith University Queensland

Research output: Chapter in Book / Conference Paper › Chapter › peer-review

Abstract

This paper model the EV charging market, treating EVs and stations as players. Our findings indicate that the Nash equilibrium does not accurately reflect the real-world competition among charging stations. This discrepancy arises because the decision-making processes of EVs and charging stations are not simultaneous. In this paper, we model this hierarchical decision-making process as a Stackelberg game, where charging stations act as leaders and EVs as followers. We further demonstrate that, under certain conditions, the Stackelberg equilibrium not only exists but is also unique. To validate our model, we use EV charging data from the Sydney city road network to examine how changes in charging prices impact EV flows. The results show the dynamic interaction between EVs and charging stations, highlighting the balancing effect of charging queues and price variations.

Original language	English
Title of host publication	PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings
Editors	Ryuta Arisaka, Victor Sanchez-Anguix, Sebastian Stein, Reyhan Aydoğan, Leon van der Torre, Takayuki Ito
Place of Publication	Switzerland
Publisher	Springer
Pages	114-119
Number of pages	6
ISBN (Electronic)	9783031773679
ISBN (Print)	9783031773662
DOIs	https://doi.org/10.1007/978-3-031-77367-9_10
Publication status	Published - 2025

Publication series

Name	Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
Volume	15395
ISSN (Print)	0302-9743
ISSN (Electronic)	1611-3349

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

SDG 7 Affordable and Clean Energy
SDG 11 Sustainable Cities and Communities

Keywords

Charging stations
Electric vehicles
Stackelberg equilibrium

Access to Document

10.1007/978-3-031-77367-9_10

Cite this

Wang, Q., Zhang, D., & Du, B. (2025). Modelling congestion and price competition in EV charging markets. In R. Arisaka, V. Sanchez-Anguix, S. Stein, R. Aydoğan, L. van der Torre, & T. Ito (Eds.), PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings (pp. 114-119). (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15395). Springer. https://doi.org/10.1007/978-3-031-77367-9_10

Wang, Qi ; Zhang, Dongmo ; Du, Bo. / Modelling congestion and price competition in EV charging markets. PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings. editor / Ryuta Arisaka ; Victor Sanchez-Anguix ; Sebastian Stein ; Reyhan Aydoğan ; Leon van der Torre ; Takayuki Ito. Switzerland : Springer, 2025. pp. 114-119 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)).

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Wang, Q, Zhang, D & Du, B 2025, Modelling congestion and price competition in EV charging markets. in R Arisaka, V Sanchez-Anguix, S Stein, R Aydoğan, L van der Torre & T Ito (eds), PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings. Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), vol. 15395, Springer, Switzerland, pp. 114-119. https://doi.org/10.1007/978-3-031-77367-9_10

Modelling congestion and price competition in EV charging markets. / Wang, Qi; Zhang, Dongmo; Du, Bo.
PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings. ed. / Ryuta Arisaka; Victor Sanchez-Anguix; Sebastian Stein; Reyhan Aydoğan; Leon van der Torre; Takayuki Ito. Switzerland: Springer, 2025. p. 114-119 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 15395).

Research output: Chapter in Book / Conference Paper › Chapter › peer-review

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N2 - This paper model the EV charging market, treating EVs and stations as players. Our findings indicate that the Nash equilibrium does not accurately reflect the real-world competition among charging stations. This discrepancy arises because the decision-making processes of EVs and charging stations are not simultaneous. In this paper, we model this hierarchical decision-making process as a Stackelberg game, where charging stations act as leaders and EVs as followers. We further demonstrate that, under certain conditions, the Stackelberg equilibrium not only exists but is also unique. To validate our model, we use EV charging data from the Sydney city road network to examine how changes in charging prices impact EV flows. The results show the dynamic interaction between EVs and charging stations, highlighting the balancing effect of charging queues and price variations.

AB - This paper model the EV charging market, treating EVs and stations as players. Our findings indicate that the Nash equilibrium does not accurately reflect the real-world competition among charging stations. This discrepancy arises because the decision-making processes of EVs and charging stations are not simultaneous. In this paper, we model this hierarchical decision-making process as a Stackelberg game, where charging stations act as leaders and EVs as followers. We further demonstrate that, under certain conditions, the Stackelberg equilibrium not only exists but is also unique. To validate our model, we use EV charging data from the Sydney city road network to examine how changes in charging prices impact EV flows. The results show the dynamic interaction between EVs and charging stations, highlighting the balancing effect of charging queues and price variations.

KW - Charging stations

KW - Electric vehicles

KW - Stackelberg equilibrium

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PB - Springer

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Wang Q, Zhang D, Du B. Modelling congestion and price competition in EV charging markets. In Arisaka R, Sanchez-Anguix V, Stein S, Aydoğan R, van der Torre L, Ito T, editors, PRIMA 2024: Principles and Practice of Multi-Agent Systems, 25th International Conference, Kyoto, Japan, November 18-24, 2024, Proceedings. Switzerland: Springer. 2025. p. 114-119. (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)). doi: 10.1007/978-3-031-77367-9_10