Realisation of automation for vehicle to grid charging and its impact on grid.

This paper introduces and underscores the automation of the E-vehicle charging process through optimization between the grid and the vehicle, incorporating real-time constraints in the charging and discharging processes. With the surge in E-vehicle usage and heightened electricity demand, automating the vehicle battery charging process becomes imperative to mitigate its impact on the grid. The research outlined in this paper focuses on automating electric vehicle charging and discharging based on real-time power demand considerations. The automation process, facilitated through a connection to the power grid, is managed by the interconnected network and algorithm-based monitoring of real-time parameters. These parameters include power, voltage, state of charge of the battery, charging cost, grid load demand, distance from the grid to the vehicle and vehicle demand. The actor-critic algorithm serves as a guide for electric vehicle charging automation, aligning with vehicle-specific data such as charging cost, vehicle demand, and grid demand to assess switching responses and enhance result accuracy. Load variations in real and reactive power for different configurations—domestic, industrial, and vehicle connections to the grid—throughout the day are considered using the IEEE 33 standard bus system. Frequency analysis of vehicle charging, grid stability analysis, and evaluation of voltage sag and swell during faulty conditions are conducted with MATLAB and the IEEE 33 standard bus system. The results provide insights into the switching time for the charging process based on algorithmic guidelines, ensuring the process follows the correct trajectory. The study demonstrates that charging time and cost are directly proportional to demand, even in time-varying processes. In the course of this research, an embedded hardware prototype model was developed to implement the proposed concept of E-vehicle charging automation. [ABSTRACT FROM AUTHOR]