Comprehensive DEA-Based Evaluation of Charging Station Operational Efficiency
This study aims to evaluate the operational efficiency of electric vehicle (EV) charging stations and explore optimization strategies to enhance resource utilization and service performance. A systematic review approach was first applied to identify the main evaluation indicators and influencing factors from existing studies. Subsequently, a super-efficiency Data Envelopment Analysis (DEA) model was used to assess the efficiency of six EV charging stations in a certain City, China. The robustness analysis was carried out, and the output variables were replaced, and the evaluation results did not change. The results show substantial disparities in efficiency across stations: C1 exhibits the highest operational efficiency, while C3 performs the lowest. The inefficiencies primarily result from supply–demand mismatches and redundant capacity investment. Based on these findings, the study proposes both overall and localized optimization strategies to improve operational performance. The results provide valuable insights for urban energy infrastructure planning and contribute to the enhancement of high-quality, low-carbon transportation development in China.
Authors
- Chunhua Jin (ORCID: https://orcid.org/0000-0002-7987-395X)
- ZhongHao ZHANG (ORCID: https://orcid.org/0009-0005-4565-6251)
- Zhen Yang (ORCID: https://orcid.org/0000-0002-6197-6168)
- Yang Hu (ORCID: https://orcid.org/0000-0001-6656-5686)
- Houzhi Li
- Jinyu Wang (ORCID: https://orcid.org/0000-0002-9449-3453)
- Jiawen Yan
Institutions
- State Grid Corporation of China (China) (CN)
- Beijing Information Science & Technology University (CN)
Publication Details
- Journal
- World Electric Vehicle Journal
- Published
- 2025-11-09
- DOI
- https://doi.org/10.3390/wevj16110613
- Primary Topic
- Electric Vehicles and Infrastructure
- Type
- article
- Field-Weighted Citation Impact
- 0.00