OpenLV: seven community groups selected

We’ve chosen the groups who will run pilot projects using data from local electricity networks

4 May 2018

Seven community competition winners have been selected as part of a ground breaking trial that will provide access to open data on local electricity networks. The winning innovation ideas could have a real impact on the future of local networks while providing benefits to a wide range of users.

The OpenLV project selected seven successful applications from community organisations along with 17 applications from the business and academic arena. All 24 projects will now progress to the next stage, in most cases developing apps to access data from the networks.

OpenLV, a Network Innovation Competition project led by Western Power Distribution and EA Technology, is opening up live data from local electricity networks for the first time.

"It's been a fascinating and inspiring process," said CSE's Bridget Newbery who is managing the communities aspect of OpenLV. "There are a lot of great ideas out there. The projects we've selected cover a variety of applications from micro-grid development to making the best use of new tariffs, and from awareness raising to demand management."

The community projects that were approved for OpenLV trials will develop apps that will, in brief:

  • Enable home owners to use energy generation and storage in the most effective way.
  • Provide a visual representation of substation demand and local generation in order to inform the development of local tariffs.
  • Show energy demand across a village, to help balancing of local generation, storage and demand.
  • Help optimise the match between photovoltaics (PV) and heat pump installations, so that local households flex their demand to minimise losses in the low voltage network.
  • Let households know when there is high demand at the local substation, to help build the case for local business models.
  • Create a public approach to reducing peak demand on substations, to lower carbon emissions, and ultimately help tackle fuel poverty.
  • Raise awareness of energy usage in a tower block and demonstrate how residents can save money on bills by shifting demand from peak times.

Scroll down for details.

Outline of projects slected for Community Trials, April 2018

Marshfield Energy Group
In this project, an app using OpenLV data will allow local people to see real-time energy demand in the village, alongside data about grid carbon intensity. Data will also be used to provide an evidence base for a village-wide energy strategy, for business planning around time-of-use tariffs, for the expected increase in electric vehicle use and potential energy storage solutions associated with it, and to assess potential for additional renewable energy installation.

Bath and West Community Energy
BWCE will exploit OpenLV data to develop an app for demand management, which will enable homeowners to adapt their energy use and encourage the take up of battery storage and solar PV. They also hope to test models for the role of community enterprise within local electricity markets.

Rooftop Housing Group
This OpenLV trial will take place on a housing development in the Bishop’s Cleeve area of Cheltenham and test out an app to give residents in the trial area access to their community’s real-time electricity demand, with the intention of raising awareness and changing behaviour around energy use. Findings from this trial will form the foundations of a larger extrapolated approach to tackle fuel poverty across all Rooftop communities.

Yealm Community Energy
YCE were a late arrival into the Method 2 trials, replacing WHG housing association. Their aim was to use OpenLV data to engage local people in local energy issues through messaging on substation behaviour, local energy consumption, local generation and carbon intensity. By putting energy data loggers into homes of residents who volunteer they planned to help people understand the link between domestic electricity use, substation activity and local renewable generation.

They planned to integrate solar generation data from the Newton Downs Solar Farm onto the community web app, alongside information from individual household data loggers (although there have been delays in accessing this data and integrating it with the web app). Generally, YCE have used the data to give general talks about electricity systems to their community and to highlight the impacts changes to the system (from low carbon technologies) may have on DNOs.

Exeter Community Energy Ltd
The OpenLV app developed in this project will show community users energy use at substation level, data on local generation from assets owned by the group, and information about national grid carbon intensity and modelled local tariffs. Monitoring equipment will be installed in a substation where ECOE already has active members.

Owen Square Community Energy 
OpenLV substation data will be used to raise awareness of energy use in the community, to promote take up of low carbon technologies by local households, and to help optimise the match between the PV and heat pump installations, so that local households will flex their demand in such a way that losses in the low voltage network are minimised.

Tamar Energy Community   
The TEC OpenLV project will centre around awareness raising, changing behaviour around energy use, and the development of local tariff models. The app will give a visual representation of demand at the substation, which will be combined with data on local generation from assets owned by the group, as well as national grid carbon intensity.

Some examples of what the business and academic projects that are due to access data through OpenLV will do are:

  • Studying the effects that localised renewables-based generation and consumption would have on local energy services.
  • Investigating how future energy technology in homes could help alleviate low voltage network grid constraints and allow the roll-out of low carbon technologies without the need for costly reinforcement.
  • Feeding LV network data into a prototype energy project identification platform that identifies solar energy and ground source heat pump potential as well as building performance.
  • Utilising LV network data and a dedicated OpenLV platform to implement managed EV charging.
  • Bringing LV network data and existing academic research into the construction of a dynamic pricing model based on current grid demand integrated with an energy trading platform.
  • Developing a software application that allows electrical appliances to be automatically managed according to smart grid requirements.

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