Interaction of electric vehicle and smart grid based on game theory for smoothing peak load and co 2 reduction

Abstract

Vehicle to Grid (V2G) concept concerns the ability to inject the power contained in the batteries of the electric vehicles (EVs) into the smart grid (SG). The present paper deals with this concept in order to flatten the daily load curve with a particular focus on the interaction between EVs and SG. Based on that, a proposed novel model using a Bayesian game approach is built to study this interaction. The model takes into account the major challenges of V2G technology, such as the availability of EV and the battery lifetime. In addition, unlike most of the existing research work, we introduce in our formulation a new factor representing the impact on the environment so as to encourage the usage of renewable sources. This factor has a significant effect on the player's decisions as well as on the simulation results. Finally, with the help of Bayesian Nash Equilibrium (BNE), we study the interaction's probability between players (SG and EV) for three periods of the day (off-peak, mid and peak hours). Simulations are carried out using real data and illustrate the effectiveness and merits of the proposed model in order to answer the raisedquestions: what is the best period of the day chosen by EV to provide power to the electric grid and SG to supply energy from the EV?, and what is the benefit of EV owners, SG and the environment in using V2G technology?.