A Survey on Algorithmic Approaches on Electric Vehicle Adaptation in a Smart Grid: An Introduction to Battery Consolidation Systems
During the past decade, the smart grid (SG) concept has been advancing better global acceptance of the electric vehicle (EV) notion. Additionally, the incorporation of renewable energy (RE) resources in the SG is a promising solution to reduce carbon emissions in an intelligent manner. Due to technological barriers at this moment, battery charging time is one of the most significant hurdles for wide adaptation of EVs. The average charging time for EVs is relatively long compared to conventional vehicles refueling. Battery Exchange Stations (BES), which can offer battery exchange plans, facilitate the adaptation of EVs into the SG. Optimizing the incorporation of components such as EVs, RE, and BESs into the base of the SG is a key challenge. In the literature, there are many studies on BESs, which propose algorithms in a solus manner to improve the incorporation of existing components into the SG. However, none of these studies have proposed a comprehensive model that considers the incorporation and transaction of all of the above mentioned components into the SG. In this paper, the authors present a survey on the existing algorithmic approaches to adapt EVs into the SG through BESs. They then introduce the concept of a battery consolidation system, which is a solution that focuses on optimizing the incorporation and transaction of all of the components in the SG. The authors propose a system model for a battery consolidation system, and then formulate the BES optimization problem based on the system model. Finally, the authors present different scenarios for some theoretical situations for EV adaptation in the SG.