UK consortium to develop comms and control system for V2G charging points

A communication and control system for vehicle-to-grid (V2G) charging points is being developed by a UK consortium.

charging points
EV charging

Vehicle-to-grid technology allows electric cars to supply energy back to the grid or to buildings such as office blocks or shopping centres when parked. This could help to stabilise electricity networks and support greater use of intermittent renewable energy sources.

The two-year project, which is part of a £30m initiative funded by the Office for Low Emission Vehicles (OLEV) and the Department for Business, Energy, and Industrial Strategy (BEIS), will develop a system designed to control how, when and the rate at which electric batteries are charged and discharged.

The VIGIL (Vehicle to Grid Intelligent control) system will take account of local substation constraints and the energy requirements of both the building and the electric vehicle itself.

The project is being led by Nortech Management, and also includes Birmingham-based ByteSnap Design, Aston University and Grid Edge.

As part of the project, ByteSnap is developing a communications adaptor to allow the system to operate with a range of different manufacturer’s V2G charging points, according to Dunstan Power, the company’s director.

“We’re designing a communications platform that can convert different vendor’s charging posts into a single protocol, called the Open Charge Point Protocol (OCPP), an industry standard,” said Power. “V2G is still at an embryonic stage in the UK, and VIGIL is going to help move the smart energy market forward.”

The company will also be developing a mobile app, to allow drivers to communicate with the system, he said.

Grid Edge, meanwhile, will develop the systems needed to manage the flow of electricity between the vehicle charge points and the building, while Nortech will manage the monitoring of local substations and communication with network operators.

Finally, researchers at Aston University will be investigating the development of a model to predict battery-life performance.