V2G and G2V are the new modes of Energy transfer and management by making use of electric vehicles. The proposed project implements the idea on basis of an Energy management system, the central nervous system that will control the V2G and G2V system body. The proposed EMS focuses on two key paramete
Load Shedding Prevention Using EMS based Vehichle to Grid and Grid to Vehicle Technology
V2G and G2V are the new modes of Energy transfer and management by making use of electric vehicles. The proposed project implements the idea on basis of an Energy management system, the central nervous system that will control the V2G and G2V system body. The proposed EMS focuses on two key parameters i.e. predicted load and SOC of vehicles for making decisions between V2G and G2V.Moreover, the proposed EMS will also consider further parameters such as location and availability of vehicles, and battery health to improvise the overall efficiency and ensure smooth flow of power.
Our project is an innovative step towards the utilization of green energy by making use of Electric Vehicles.This project enables a successful Bi- Directional power flow and will provide us an efficient charging and discharging mechanism for V2G application.
The prototype of the project would contain a grid tied invertor, Controller based EMS System, Bi-directional charging topolgy. EMS system will further has a prediction mechanism which will be done by some Machine learning algorithm on the basis of historical data and the notify process would be done with the help of GSM Module.
This project prevents load shedding by filling the gap between available power and demanded power and enhances grid stability.Last but not the least, our project will prevent climate change that is one of UN sustainaible development goals.
For our prototype we'll be having a 12V 125Ah Lead Acid battery that will represent EV battery. From the SOC of this battery our EMS, consisting of controllers and relays, will be taking decisions of charging of the battery or discharging of the battery. In order to discharge, it we'll design a Grid Tie Inverter that will convert 12V DC into 220V AC and this system will be power the load up to 30-50W. For SOC measurements we'll be having controllers and necessary sensors of current and voltage. This will be the hardware part.
Our EMS will be working on the basis of Machine Learning Algorithm. For this we'll design our system that will be predicting the load demand of the system and calculating the actual demand as well this will help our EMS to take decisions more accurately on the basis of load demand and SOC of battery.
| Item Name | Type | No. of Units | Per Unit Cost (in Rs) | Total (in Rs) |
|---|---|---|---|---|
| Lithium ion Battery | Equipment | 1 | 17500 | 17500 |
| Controllers | Equipment | 5 | 1000 | 5000 |
| Transformers | Equipment | 5 | 300 | 1500 |
| Power MOSFETS | Equipment | 300 | 10 | 3000 |
| Discrete ICs | Equipment | 300 | 10 | 3000 |
| PCBs | Equipment | 5 | 500 | 2500 |
| Breadboards | Equipment | 5 | 500 | 2500 |
| Oscilloscope | Equipment | 1 | 35000 | 35000 |
| Total in (Rs) | 70000 |
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