Load Shedding Prevention Using EMS based Vehichle to Grid and Grid to Vehicle Technology

Project Title

Load Shedding Prevention Using EMS based Vehichle to Grid and Grid to Vehicle Technology

Project Area of Specialization Electrical/Electronic EngineeringProject Summary

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.

Project Objectives

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.

Project Implementation Method

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. 

Benefits of the Project

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.

Technical Details of Final Deliverable

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.

Final Deliverable of the Project HW/SW integrated systemCore Industry Energy Other Industries Others Core Technology OthersOther Technologies Artificial Intelligence(AI)Sustainable Development Goals Responsible Consumption and Production, Climate Action, Life on LandRequired Resources

Item Name	Type	No. of Units	Per Unit Cost (in Rs)	Total (in Rs)
			Total in (Rs)	70000
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