Multi-objective charging scheduling for electric vehicles at charging stations with renewable energy generation
Journal article, 2025

The rapid adoption of electric vehicles (EVs) in recent years has posed significant challenges to the safe operation of local grids, particularly due to massive charging operations at public charging stations. This paper proposes a real-time charging scheduling scheme to enable efficient Vehicle-to-Grid (V2G) interactions and facilitate renewable energy integration at public charging stations while accounting for real-world EV charging behaviors. First, an EV charging/discharging behavior database is developed to capture the temporal uncertainty and charging characteristics of both fast- and slow-charging operations on weekdays and weekends. Then a charging pile allocation mechanism is introduced to optimize the charging power distribution for each EV to maximize the operational efficiency of the studied charging station. A micro-grid system model is developed by incorporating efficient V2G interactions and renewable energy integration. Finally, a comprehensive charging scheduling scheme is proposed to achieve a balanced optimization of multiple objectives. Extensive simulation studies are conducted to evaluate the performance of the proposed scheduling method. The results demonstrate that the proposed scheme achieves strong performance across all three selected indicators.

Charging scheduling

Micro-grid

Electric vehicles

V2G

Charging stations

Author

Lei Zhang

Beijing Institute of Technology

Yingjun Ji

Beijing Institute of Technology

Xiaohui Li

Chalmers, Space, Earth and Environment, Physical Resource Theory

Zhijia Huang

Beijing Institute of Technology

Dingsong Cui

University of Leeds

Haibo Chen

University of Leeds

Jingyu Gong

RWTH Aachen University

Fabian Breer

RWTH Aachen University

Mark Junker

RWTH Aachen University

Dirk Uwe Sauer

RWTH Aachen University

Green Energy and Intelligent Transportation

20972512 (ISSN) 27731537 (eISSN)

Vol. 4 4 100283

Subject Categories (SSIF 2025)

Transport Systems and Logistics

Energy Engineering

Energy Systems

DOI

10.1016/j.geits.2025.100283

More information

Latest update

10/5/2026