Domestic Infrastructure and Network Optimisation (DINO)

Designing a load management system to help low-voltage local grids cope with increasing future demands from electric vehicles and heat pumps.

Lead Organisation

Evergreen Smart Power

URL

cdn.evergreenenergy.co.uk/smart-power/dino-final-report.pdf

Location

Glasgow

Funding

£343,000

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About the project

Project DINO aimed to develop a load management platform which uses communication between energy networks and household equipment to manage and adjust loads and demands.

It succeeded in developing a technical solution but found that regulatory changes for this type of control are not yet in place and business models that work for all stakeholders are not yet clear.

Project aims and approach

The project aimed to address the fact that increasing reliance on electricity is causing issues for domestic electricity operators, and low-voltage networks will be constrained by increasing numbers of heat pumps, EVs and domestic batteries. These could increase local networks’ peak loads by over 80% by 2040, with headroom starting to run out before 2035.

Digging up streets to reinforce cabling is counterproductive – both economically and from a carbon emissions perspective – so a smart solution is needed to allow households to share the available energy ‘bandwidth’.

Below you can watch a short film clip outlining the aims of the project.

Project DINO aimed to develop a load management platform to enable network assets to communicate with household equipment, to warn household systems when the local network is under stress, and automatically relieve that stress. The aim was to maximise the usage of the network while actively managing the load within set parameters and constraints.

If an electric vehicle is charging rapidly at home but won’t be needed until the morning, the technology would temporarily reduce its charge rate to share the available energy across the neighbourhood – keeping the lights on while making sure the car still has a full battery by morning.

The project prototyped a system using real-time information from the Maidenhill Grove new-build housing estate in Glasgow, combined with models of electric vehicle charging and heat pump usage.

The core elements were:

  • Developing hardware to monitor network condition and control key domestic loads remotely.
  • Designing a prototype load management system (LMS) that balances domestic load between houses.
  • Applying the LMS to a case study of a new-build housing estate and showing how it can communicate with load monitors in substations.

Project partners

  • Evergreen Smart Power (lead)
  • Energy Assets Networks
  • myenergi

Dates

April 2020 to June 2022

Achievements and barriers

  • The DINO system has shown that it can successfully balance network load by intelligently shifting the loads of heat pumps, EVs and domestic batteries. In one trial, the LMS successfully managed the heating schedules of 20 houses with heat pumps during cold winter temperatures (around -2 degrees) to avoid breaching network limits.
  • Evergreen Energy’s Homely smart thermostat system for heat pumps was expanded into a comprehensive network model that can simulate the networks of the future at different times of year and perform price-optimised network load management.
  • The project developed a new battery controller and enhanced the communication function of myenergi’s zappi EV charger.
  • However business models that work for all stakeholders are not yet clear, and regulatory changes for this type of control are not yet in place. Regulation for demand-side reduction on individual local low-voltage networks is being explored by the Managing Impact of Low-Carbon Technologies on Low-Voltage Networks working group.

Next steps

At the end of the project the prototype load management system was ready to be rolled out for further development and testing in a real-world setting. DINO network management complements household energy management systems and could be installed on a traditional low-voltage network or as part of a microgrid.

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