Efficient V2G Model on Smart Grid Power Systems Using Genetic Algorithm

Abstract

The adaptation of electric vehicles has impacted various fields, like power grid, intelligent transport system etc. Despite the benefits of these vehicles, they do have negative influence on existing network operations due to their charging strategies. To control electric vehicles in uncertain environments, planning the path and dynamic steering control can be used. Relaxation of the path is beneficial for computing censorious points across a world-wide preferable path by the data of sensors. Automated parking and driving is envisaged that it will be the base of the structure. Vehicle to grid technology is advanced by the concept of development of smart grid. Smart grid development allows two-directional energy interchange among vehicles and power grid. To overcome the environmental issues, integration of energy systems that is renewable in electric vehicles. In the upcoming era, three advancements will be made in this technology, potential of in vehicle systems, worldliness of the driver and vehicle interface, and capability of vehicles to liaise with each other. The issue of energy is still present in V2G systems while implementing or upgrading power systems. In this paper an efficient model is presented which will save energy in power systems and smart grid using Genetic Algorithm. Genetic algorithm take input from user and get better solution from trained modeled.