Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective

March 9, 2021

graphSmart Grid and Renewable Energy Laboratory, Tsinghua-Berkeley Shenzhen Institute's Zhe Zhou, UC Berkeley Civil and Environmental Engineering and Smart Grid and Renewable Energy Laboratory, Tsinghua-Berkeley Shenzhen Institute's Scott Moura, Smart Grid and Renewable Energy Laboratory, State Key Laboratory of Internet of Things for Smart City, University of Macau's Hongcai Zhang, Smart Grid and Renewable Energy Laboratory, Smart Grid and Renewable Energy Laboratory, Tsinghua-Berkeley Shenzhen Institute and State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University'sQinglai Guoad, Smart Grid and Renewable Energy Laboratory, Tsinghua-Berkeley Shenzhen Institute and State Key Laboratory of Power Systems, Department of Electrical Engineering, Tsinghua University's Hongbin Sunad recently published Power-traffic network equilibrium incorporating behavioral theory: A potential game perspective.

Highlights

• A game-theoretic model to capture the interconnections between the coupled networks.
• Discrete choice models to describe the behavioral process of drivers.
• Decentralized algorithm to compute equilibrium flows by independent system operators.

Abstract

This paper examines the interconnections between the power and transportation networks from a game theoretic perspective. Electric vehicle travelers choose the lowest-cost routes in response to the price of electricity and traffic conditions, which in turn affects the operation of the power and transportation networks. In particular, discrete choice models are utilized to describe the behavioral process of electric vehicle drivers. A game theoretic approach is employed to describe the competing behavior between the drivers and power generation units. The power-traffic network equilibrium is proved to possess a potential type structure, which establishes the properties of the network equilibrium. Moreover, the network equilibrium state is shown to be a welfare-maximizing operating point of the electric distribution network considering the spatial demand response of electric vehicle loads. A decentralized algorithm based on the optimality condition decomposition technique is developed to attain the equilibrium flow solutions. Numerical experiments demonstrate how the proposed framework can be used to alleviate both power and traffic congestion.

 

DOI: https://doi.org/10.1016/j.apenergy.2021.116703