Online Dynamic Pricing for Electric Vehicle Charging Stations with Reservations

• URL: http://arxiv.org/abs/2410.05538v1
• Date: Mon, 7 Oct 2024 22:36:40 GMT
• Title: Online Dynamic Pricing for Electric Vehicle Charging Stations with Reservations
• Authors: Jan Mrkos, Antonín Komenda, David Fiedler, Jiří Vokřínek,
• Abstract summary: The transition to electric vehicles (EVs) will significantly impact the electric grid. Unlike conventional fuel sources, electricity for EVs is constrained by grid capacity, price fluctuations, and long EV charging times. This paper proposes a model for online dynamic pricing of reserved EV charging services.
• Score: 0.3374875022248865
• License: http://creativecommons.org/licenses/by/4.0/
• Abstract: The transition to electric vehicles (EVs), coupled with the rise of renewable energy sources, will significantly impact the electric grid. Unlike conventional fuel sources, electricity for EVs is constrained by grid capacity, price fluctuations, and long EV charging times, requiring new pricing solutions to manage demand and supply. This paper proposes a model for online dynamic pricing of reserved EV charging services, including reservation, parking, and charging as a bundled service priced as a whole. Our approach focuses on the individual charging station operator, employing a stochastic demand model and online dynamic pricing based on expected demand. The proposed model uses a Markov Decision Process (MDP) formulation to optimize sequential pricing decisions for charging session requests. A key contribution is the novel definition and quantification of discretization error introduced by the discretization of the Poisson process for use in the MDP. The model's viability is demonstrated with a heuristic solution method based on Monte-Carlo tree search, offering a viable path for real-world application.

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