Smart Routing of Electric Vehicles for Load Balancing in Smart Grids
For smart grid operators, this work addresses the challenge of managing EV charging load to prevent grid overload, but the results are incremental as they extend existing game-theoretic routing concepts to the EV domain.
This paper proposes a game-theoretic framework for routing electric vehicles to balance electricity load in smart grids, considering traffic congestion and charging station waiting times. The framework achieves a pure-strategy Nash equilibrium with a bounded price of anarchy, and simulations provide insights for efficient energy pricing.
Electric vehicles (EVs) are expected to be a major component of the smart grid. The rapid proliferation of EVs will introduce an unprecedented load on the existing electric grid due to the charging/discharging behavior of the EVs, thus motivating the need for novel approaches for routing EVs across the grid. In this paper, a novel gametheoretic framework for smart routing of EVs within the smart grid is proposed. The goal of this framework is to balance the electricity load across the grid while taking into account the traffic congestion and the waiting time at charging stations. The EV routing problem is formulated as a noncooperative game. For this game, it is shown that selfish behavior of EVs will result in a pure-strategy Nash equilibrium with the price of anarchy upper bounded by the variance of the ground load induced by the residential, industrial, or commercial users. Moreover, the results are extended to capture the stochastic nature of induced ground load as well as the subjective behavior of the owners of EVs as captured by using notions from the behavioral framework of prospect theory. Simulation results provide new insights on more efficient energy pricing at charging stations and under more realistic grid conditions.