Revenue Maximization for Electric Vehicle Charging Service Providers Using Sequential Dynamic Pricing

With the increasing prevalence of electric vehicles (EVs), the provision of EV charging is becoming a standard commercial service. With this shift, EV charging service providers are looking for ways to make their business more profitable. Dynamic pricing is a proven technique to increase revenue in markets with time-variant, heterogeneous demand. In this paper, we propose a Markov Decision Process (MDP)-based approach to revenue-maximizing dynamic pricing for charging service providers. We implement the approach using an ensemble of policy iteration MDP solvers and evaluate it using a simulation based on real-world data. We show that our proposed method achieves significantly higher revenue than methods utilizing flat-based pricing. In addition to achieving higher revenue for charging service providers, the method also increases the efficiency of allocation measured in terms of the total utilization of the charging station.