Modeling the dependency relationship of coupled power and transportation networks
Qing-Chang Lu,
Shixin Wang,
Peng-Cheng Xu,
Jing Li,
Xu Meng and
Adil Hussain
Energy, 2025, vol. 320, issue C
Abstract:
The dependency between the power network (PN) and transportation network (TN) has been increasing with the rise of electric vehicles (EVs). This study proposes a supply-demand-based dependency methodology that explicitly incorporates the functional heterogeneity of fast charging stations (FCSs). Different from conventional homogeneous-node assumptions for FCSs, both internal and external heterogeneity are addressed in the proposed model to interpret network dependency relationship. The methodology is applied to the main power and intercity expressway networks of Guizhou Province, China. Results show that dependency relationship is affected by internal and external heterogeneity of FCSs, with those in the network center being approximately 2.33 times higher than that of the suburban areas. This difference is due to the fact that charging price of FCS dominates urban dependency relationship, while the redundancy of FCSs plays a major role in the suburbs. When the EV penetration rate reaches 80 %, the dependency relationship of 72.7 % of the FCSs would not change. Besides, dynamic charge pricing at FCSs can adjust the dependency relationship under failure conditions. The conclusions and recommendations can inform the management and improvement of the PN and TN, FCS design, and traffic flow control.
Keywords: Electric vehicle; Fast charging station; Coupled power and transportation networks; Dependency relationship; Supply-demand-based approach (search for similar items in EconPapers)
Date: 2025
References: Add references at CitEc
Citations:
Downloads: (external link)
http://www.sciencedirect.com/science/article/pii/S0360544225009727
Full text for ScienceDirect subscribers only
Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.
Export reference: BibTeX
RIS (EndNote, ProCite, RefMan)
HTML/Text
Persistent link: https://EconPapers.repec.org/RePEc:eee:energy:v:320:y:2025:i:c:s0360544225009727
DOI: 10.1016/j.energy.2025.135330
Access Statistics for this article
Energy is currently edited by Henrik Lund and Mark J. Kaiser
More articles in Energy from Elsevier
Bibliographic data for series maintained by Catherine Liu ().