Evaluation of Grid Connected Electric Vehicle Impact in the Power Demand Curve with PI/ANN Controller

This paper provides a complete analysis that is newest in development of electric cars (EVs) collaboration with power grid representing the future of smart grid design. This work elaborate study of a different control method in order to achieve the accurate control between electric vehicle and residential load connected to grid. As Electric Vehicles are equipped with Lithium ion battery which is more sensitive to overcharge and dip discharge and which leads to performance degradation due to unorganized absorption and injection of power into the grid. The EVs battery charging (G2V) and discharging (V2G) operation are must be synchronized in order maintain the power quality in the power grids. So, Seven modes of operation are used for G2V (Grid To vehicle) and V2G (Vehicle to Grid) operation to insure proper organize absorption and injection of power into grid by considering the load demand. The control algorithm for this modes also checks SOC of battery, grid demand, priority order between EV and the power difference required to flatten the demand curve. Depending upon all this factor G2V and V2G operation are performed. This proposed scheme modeled with conventional PI and ANN controller. The Comparative analysis between this two controllers are performed to ensure the proper flow of power when EVs connected to grid. This proposed methodology developed and simulated with help of MATLAB/Simulink.