Modeling the dependency relationship of coupled power and transportation networks

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.