Cost–Benefit Analysis on Electrical Vehicle Charging Station Using the Vehicle-To-Grid Technology from Python Language

In the present scenario, most of the vehicles use an integrated combustion engine which consumes fossil fuels and pollutes the atmosphere. As fossil fuels are going to be depleted in the future, Vehicle electrification will have a positive impact on the system as electric vehicles have a low emission rate which in turn reduces global warming. Therefore, the usage of electric vehicles increases in the future. The huge penetration of electric vehicles is going to bring an additional load on the existing grid. Hence, there is a need to control and manage electric power wisely. To overcome this demand on the grid at peak times and to conserve energy, the vehicle-to-grid concept is introduced. Electric vehicle users can supply back the available power in their vehicle to the grid at peak times. This minimizes the load on the grid at peak times and users can be benefitted as they get paid by supplying power back to the grid. Hence, the vehicle-to-grid technology benefits both the user and the grid. To implement this vehicle-to-grid concept there is a need for an interface that connects both the user and the grid. This can be done by using an electric vehicle aggregator. In the proposed approach, an IEEE 33 bus system integrated with four electric vehicle charging stations (10, 14, 17 and 30) was considered to analyse the performance of the system for a 24-h horizon. Here, the Python coding is carried out for cost–benefit analysis based on the load demand and SoC constraints during off and peak load times for 24 h of the day.