4.7 Article

Network Equilibrium of Coupled Transportation and Power Distribution Systems

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 9, Issue 6, Pages 6764-6779

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2017.2723016

Keywords

Electric vehicle; interdependency; locational marginal price (LMP); network equilibrium; optimal power flow; power distribution network; static traffic assignment; transportation network; Wardrop user equilibrium

Funding

  1. National Natural Science Foundation of China [51621065]
  2. U.S. National Science Foundation [PFI:BIC-1534035]
  3. U.S. Natural Science Foundation [1638348]

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This paper presents a holistic modeling framework for the interdependent transportation network and power distribution network. From a system-level perspective, on-road fast charging stations would simultaneously impact vehicle routing in the transportation system and load flows in the distribution system, therefore tightly couple the two systems. In this paper, a dedicated traffic user equilibrium model is proposed to describe the steady-state distribution of traffic flows comprised of gasoline vehicles and electric vehicles. It encapsulates route selections, charging opportunities, electricity prices, and individual rationalities of minimum travel expense in a convex traffic assignment problem over an extended transportation network. An adaptive path generation oracle is suggested to solve the problem in a tractable manner. Economic operation of the power distribution system is formulated as an alternating current optimal power flow problem. Convex relaxation is performed. The optimal generation dispatch and nodal electricity prices can be computed from a second-order cone program. It is revealed that an equilibrium state will emerge due to the rational behaviors in the coupled systems, which is characterized via a fixed-point problem. A best-response decomposition algorithm is suggested to identify the network equilibrium through iteratively solving the traffic assignment problem and the optimal power flow problem, both of which entail convex optimization. Illustrative examples are presented to validate related concepts and methods.

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