• CSCD核心库收录期刊
  • 中文核心期刊
  • 中国科技核心期刊

Electric Power Construction ›› 2020, Vol. 41 ›› Issue (1): 13-22.doi: 10.3969/j.issn.1000-7229.2020.01.002

Previous Articles     Next Articles

Analysis on Disturbance Propagation of Charging Station Fault Considering Grid-Traffic Network Coupling

ZHANG Yuwei, YANG Jun, WU Fuzhang, ZHAN Xiangpeng, LONG Xuemei, ZHANG Jun, XU Jian   

  1. School of Electrical Engineering and Automation, Wuhan University, Wuhan 430072, China
  • Online:2020-01-01
  • Supported by:
    This work is supported by National Key Research and Development Program of China (No. 2017YFB0902900), Program of the Humanities and Social Research of Ministry of Education(No.17YJCZH212) and National Natural Science Foundation of China(No. 51977154).

Abstract: In recent years, with the increase of EVs, the grid and traffic networks are closely connected. In 2018, the failure of the charging stations in Shenzhen caused a lot of EVs to stop working, which indicates that the disturbance of the grid may spread to the traffic network through the coupling of charging stations and EVs, resulting in a cascading failure. Therefore, aiming at the coupling of the grid-traffic networks, the propagation of fault disturbance is studied. Firstly, the coupling relationship between the two networks is analyzed, and the coupling network model is established on the basis of the multi-layer network theory. The travel chain is used to simulate the driving path of electric vehicles, and the travel and charging model of EVs is established. On the basis of the coupling network and considering the impact of charging station fault disturbance on EVs, the fault disturbance analysis method based on cascading failure of multi-layer network is proposed. Finally, the spatial-temporal propagation characteristics of charging station fault disturbance in traffic network are analyzed through simulation example. The results show that the proposed fault propagation analysis framework based on grid-transport network coupling can accurately describe the impact of grid disturbance on the traffic network. And the method can classify according to the temporal and spatial evolution characteristics of traffic conditions of different road sections, and provide a scientific basis for traffic managers to make decisions.

Key words: electric vehicles, complex network, multi-layer networks, cascading failure, disturbance propagation

CLC Number: