A Cooperative Game Approach for Electric Vehicle Charging Site Recommendation Considering User Price Sensitivity

Yuming Zhao1; Mengge Shi2; Shan He1; Wenjun Tang1; Youwei Jia2

10.1109/EI259745.2023.10513279

2023-12-18

979-8-3503-4510-0

2023 IEEE 7th Conference on Energy Internet and Energy System Integration (EI2)

15-18 Dec. 2023

Hangzhou, China

The widespread adoption of electric vehicles (EVs) has created an opportunity to enhance system operational performance by leveraging the charging flexibility of EVs. This paper investigates the coordinated recommendation and scheduling of EV charging sites, addressing both the optimization problem of EV-charging station (CS) matching and scheduling as well as the problem of benefit distribution among the participating CSs. To optimize the controllability of EV charging behavior, a two-stage EV-CS matching and energy management model has been developed, which considers several factors including EV user price sensitivity, driving distances, and real-time traffic conditions, in order to model user behavior more realistically. To reconcile the conflicting interests among CSs, a benefit distribution approach based on the Shapley value method has been proposed. Numerical simulations show that the proposed methods can simultaneously benefit EV users and reduce the cost of CS operators. The effectiveness of the proposed methods has been demonstrated using four real-world CS load data and traffic data from Shenzhen, resulting in a significant 74.8% reduction in CS real-time cost.

其他

1.Shenzhen Power Supply Bureau Co., Ltd, Shenzhen, China
2.Department of Electrical and Electronic Engineering, Southern University of Science and Technology, Shenzhen, China

Yuming Zhao,Mengge Shi,Shan He,et al. A Cooperative Game Approach for Electric Vehicle Charging Site Recommendation Considering User Price Sensitivity[C],2023.