We are partners in an innovative resilience project – Project DINO – applying artificial intelligence (AI) to local network design to balance future demand with supply. Through this project – which is a UK ‘first’ – we are collaborating with key industry players to protect network integrity through smart through two-way communication with household appliances, including EV chargers.

Network Innovation

Through Project DINO (Domestic Infrastructure and Network Optimisation), EA Networks is partnering with Evergreen Smart Power and Myenergi to show how AI can safeguard network integrity in a newbuild setting.

The project will show how AI can prevent local power networks being overloaded during the projected rapid rise in demand for electricity. It has been launched with co-funding from Innovate UK, the UK’s innovation agency and is the first project of its type in the UK.

Currently, housing developments are designed to cope with an average peak load of 2kW per household. However, as EV charging and heat pumps become more common place, this could routinely exceed 10kW – and without intervention, this could lead to power outages.

There is growing realisation that local power networks may not be able to cope with the huge increase in demand for electricity as we transition to electric vehicles, battery storage/charging and air source heat pumps alongside traditional household appliances.

The DINO project aims to demonstrate how a network-to-device AI interface can manage loads dynamically by enabling appliances to automatically dial down consumption at peak times to relieve network stress and safeguard power to homes. Without such a solution, the country would need to invest in a hugely costly network reinforcement programme to increase capacity.”

As part of Project DINO, Evergreen Smart Power will apply an AI solution that enables two-way communication between networks and devices, such as EV chargers, so that when the local system is under stress, energy consumption will reduce automatically to allow households to share available bandwidth.

The pilot research project will last for two years, with the partners monitoring real time power flow and consumption on a newbuild housing scheme at both feeder and substation levels, with the data augmented with models of electric vehicle charging and heat pump usage.

This will lead to the development of new algorithms and proof of concept equipment that will automatically and precisely respond to system stress down to individual feeder cables. The project will also be further extended to model the effect of domestic battery storage to determine how these too could be similarly controlled.

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