4.7 Article

On Dynamic Network Equilibrium of a Coupled Power and Transportation Network

期刊

IEEE TRANSACTIONS ON SMART GRID
卷 13, 期 2, 页码 1398-1411

出版社

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2021.3130384

关键词

Vehicle dynamics; Vehicles; Power system dynamics; Real-time systems; Costs; Routing; Pricing; Electric vehicle; dynamic network equilibrium; dynamic user equilibrium; variational inequality; fixed-point theorem

资金

  1. China Scholarship Council [201906270125]

向作者/读者索取更多资源

This study focuses on the temporal and spatial coupling between power distribution networks and transportation networks. It proposes a dynamic network equilibrium model to capture the dynamic interactions between the two networks, and accurately describe the choices of drivers, traffic flows, queues, and electricity prices.
The increasing prevalence of electric vehicles (EVs) has intensified the coupling between power distribution networks (PDNs) and transportation networks (TNs) in both temporal and spatial dimensions. In order to accurately model the coupled network, this paper studies the dynamic network equilibrium to capture the temporally-dynamic interactions between PDNs and TNs. This equilibrium encapsulates the driver's choices of route, departure time, and charging location, and the electricity price. In the TN, a dynamic traffic model with point queues is proposed to describe the spatial and temporal evolution of traffic flows that is congruent with established user equilibrium choices. In particular, the queues formed at charging stations are, for the first time, modeled by a point queue. In the PDN, the electricity prices are accurately determined from a second-order conic program with a guarantee of strong duality. After theoretically proving the existence of an equilibrium solution, an improved fixed-point algorithm based on extrapolation is also proposed to solve the equilibrium problem efficiently. Numerical results show that the dynamic network equilibrium can be efficiently solved to capture the temporally variant nature of traffic flows, queues, and electricity prices.

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