Joint Differentiated Pricing and Energy-Carbon Trading for Electric Vehicle Charging Stations: An ADMM-Based Nash Bargaining Solution

With the widespread proliferation of electric vehicles (EVs), optimizing the operation of EV charging stations (EVCSs) has become increasingly important. Strategic charging prices can influence both revenue and service efficiency, while differentiated pricing for different EVs can further help mitigate overstay issues. Moreover, under the concept of the peer-to-peer (P2P) sharing economy, energy, and carbon (E&C) allowance trading among EVCSs presents a significant opportunity to reduce both operational costs and carbon emissions. However, limited research has examined such interactions and the specific economic and environmental impacts of joint E&C trading in multi-EVCS systems. In this article, we investigate a joint differentiated pricing and E&C trading problem for multiple EVCSs, aiming to maximize both economic and environmental benefits. Specifically, we first formulate a total revenue-maximization problem that incorporates anxiety-differentiated pricing and P2P E&C trading among multiple interconnected EVCSs. We then propose an operational algorithm to solve the problem based on Nash bargaining and the alternating direction method of multipliers (ADMM), which can protect privacy and mitigate communication barriers among EVCSs. Simulation results demonstrate that the proposed algorithm can simultaneously improve revenue and achieve low-carbon goals.