An Improved Charging Navigation Strategy of Electric Vehicles via Optimal Time-of-Use Pricing

Electric vehicles (EVs) have attracted worldwide attention and have been vigorously promoted by the government. However, users' mileage anxiety and the intermittent charging load are still great challenges to the popularization of EVs. To tackle these problems, this paper proposes an improved charging navigation model, aiming at maximizing the benefits of multiple parties by setting time-of-use (TOU) price of fast charging stations (FCSs) to attract EVs to charge at off-peak hours and saving the costs of EVs with real-time navigation. It is modeled as a Stackelberg game, in which the FCSs operator and EVs are the leader and followers respectively. First, a rigorous and dedicated traffic simulation model, air conditioner energy consumption model and queuing model of EVs are established. Then, by researching the impact of prices on charging choices, an EV strategy including the selection of charging time, charging energy, charging station and routes is proposed to minimize EV's cost. Based on EV charging response behavior, the optimal TOU pricing strategy for FCSs is formulated to maximize FCSs' revenue. The simulation results confirm that the proposed approach is beneficial to EVs and FCSs, and can effectively reduce the peak-to-average ratio and the peak-valley difference of the power system.

Automated summary

This paper proposes an improved charging navigation model to tackle the challenges of users' mileage anxiety and intermittent charging load. By setting time-of-use price for fast charging stations and utilizing real-time navigation, the model aims to maximize the benefits for both electric vehicle users and charging stations. The simulation results confirm the effectiveness of the proposed approach in reducing the peak-to-average ratio and peak-valley difference of the power system.