您当前的位置:
首页 >
文章列表页 >
A collaborative planning and allocation solution for PV-storage integration in flexible traction substations based on a neural population dynamics optimization algorithm
Key Technologies for the Integrated Development of Smart Energy and Rail Transit | 更新时间:2026-04-25
    • A collaborative planning and allocation solution for PV-storage integration in flexible traction substations based on a neural population dynamics optimization algorithm

    • Electric Drive for Locomotives   Issue 6, Pages: 84-93(2025)
    • DOI:10.13890/j.issn.1000-128X.2025.06.009    

      CLC: U223
    • Received:28 August 2025,

      Revised:2025-09-22,

      Published:10 November 2025

    移动端阅览

  • YANG Chenye, LIU Qiujiang, WU Mingli, et al. A collaborative planning and allocation solution for PV-storage integration in flexible traction substations based on a neural population dynamics optimization algorithm[J]. Electric drive for locomotives,2025(6): 84-93. DOI:10.13890/j.issn.1000-128X.2025.06.009.

  •  
  •  

0

Views

0

下载量

0

CSCD

0

CNKI被引量

>
Alert me when the article has been cited
提交
Tools
Download
Export Citation
Share
Add to favorites
Add to my album

Related Articles

Carbon emission accounting for traction power supply systems based on dynamic power-flow tracing
Multi-source energy dispatching strategy for "source-network-train-storage" coordinated power supply on electrified railways
A traction load modeling method of metro trains based on the regenerative braking energy effective utilization and its application
Modeling of traction power supply system and analysis on its influence on power quality of power grid
Research on Non-contact Fault Location System of Traction Power Supply Line

Related Author

LI Teng
XIAO Zhihan
FAN Haoran
FU Jun
WANG Yongbin
GUAN Da
MEI Wenqing
WANG Yue

Related Institution

Power Supply Branch of Guoneng Xinshuo Railway Co., Ltd.
CRRC Zhuzhou Institute Co., Ltd.
Beijing Urban Construction Design & Development Group Co., Ltd.
Electric Power Research Institute, State Grid Henan Electric Power Company
Sichuan Energy Internet Research Institute Tsinghua University
0