ADVENT: Advanced Data-driven Virtual Electricity Network Tracking
This project aimed to deliver low-cost, real-time data on the state of the electricity network and support the rapid and smooth growth of low-carbon smart-energy technologies.
About the project
The ADVENT project developed and tested a system to estimate the state of low-voltage networks, using mathematical modelling based on data from voltage sensors in multiple homes.
Project aims and approach
With the rapid changes affecting electricity grids, both in use and generation of power, new approaches are needed to monitor the health of the evolving electricity network, check resilience and spot problems before they occur.
The project aimed to provide low-cost, real-time data on the state of the electricity network, as a more cost-effective solution than extensive rollout of existing solutions for monitoring load, voltage and unreported micro-generation.
The ultimate goal was to help communities to enable the rapid growth of low-carbon smart-energy technologies.
The approach of the ADVENT project was to develop and test a virtual network monitoring device based on voltage readings from EV chargers and other sensors, exploring whether taking multiple readings from different homes would allow voltage estimates to be made more widely and at the substation.
The partners in the project worked to develop a virtual power meter, or distribution system state estimator (DSSE). This would estimate the power flow or feeder loading in the electricity grid using voltage readings from electricity meters, electrical vehicle chargers, and other sensors around the grid. Through mathematical models, the estimator would use these readings to estimate the flow at low-voltage substations.
Trials took place in Harbury in Warwickshire, Writtle in Essex and Marlow in Buckinghamshire. The team worked with householders to plug in a voltage recording device (such as the emonPi) in the home, connected to the household internet router. This measured the voltage in the home and submitted the data electronically for monitoring and comparison with measurements taken at the local substation.
Partners
- Crowd Charge (lead)
- Hanger19
- University of Reading
- Western Power Distribution plc
Dates
June 2020 to June 2022
Achievements and barriers
The project succeeded in developing and testing its distribution system state estimator, not only in simulations but also during real applications in pilot areas.