Multi-objective charging scheduling for electric vehicles at charging stations with renewable energy generation

  • Lei Zhang*
  • , Yingjun Ji
  • , Xiaohui Li
  • , Zhijia Huang
  • , Dingsong Cui
  • , Haibo Chen
  • , Jingyu Gong
  • , Fabian Breer
  • , Mark Junker
  • , Dirk Uwe Sauer
  • *Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

Abstract

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.

Original languageEnglish
Article number100283
JournalGreen Energy and Intelligent Transportation
Volume4
Issue number4
DOIs
Publication statusPublished - Aug 2025
Externally publishedYes

Keywords

  • Charging scheduling
  • Charging stations
  • Electric vehicles
  • Micro-grid
  • V2G

Fingerprint

Dive into the research topics of 'Multi-objective charging scheduling for electric vehicles at charging stations with renewable energy generation'. Together they form a unique fingerprint.

Cite this