LAUSR

Abstract Integration of renewable and other distributed generated energy resources has put enormous strains on the traditional power grid. The world is moving towards green energy and trying hard to reduce carbon footprints by promoting distribution generation at their end. By generating surplus energy, consumers want to inject extra energy to the grid or trade it with nearby consumers. Likewise, increasing number of electric vehicles (EVs) also necessitate the energy trading mechanisms to motivate other prosumers to participate in energy trading. There are various challenges associated with the current energy trading system like fluctuating energy prices, demand uncertainty, capacity and time uncertainty, congestion and charging station location, energy storage system capacity, security and privacy preservation, voltage and frequency regulation, communication overheads, charging strategies etc. Stackelberg game is a powerful strategic tool to model the interaction between various agents in the energy market including EV users, prosumers, energy retailers, grid stations, and charging stations. It is a leader following game, in which there is a leader who sets his strategy first and other players become his followers, who adjust their strategies by looking at the strategy announced by the leader. Stackelberg game plays a crucial role in an environment where people involved are rational and all want to optimize their payoffs. This paper presents a novel classification of EVs energy trading using the Stackelberg game approach to the date, and technical approaches to find corresponding optimal strategies. The paper also gives a brief overview of the simulation tools reported in the literature to formulate and solve optimization problems in the current energy trading systems. Finally, the manuscript highlights the potential challenges and prospective solutions associated with the integration of EVs into current energy trading framework that can be solved and modelled through Stackelberg game.