FUNDAMENTALS announces completion of a location-based early warning system project which detects electric vehicle charging with 99% accuracy

€1.62m contract part-funded by the European Space Agency incorporates the power of satellite navigation technology into power grids.

FUNDAMENTALS, a leader in electrical grid technology, today announces it has worked with the European Space Agency, Chronos Technology and University of Strathclyde on the ‘ENERSYN’ project to incorporate the power of satellite navigation technology into power grids. This location-based early warning system detects electric vehicle charging with an accuracy of 99 percent and provides localised, early, real-time visibility of potentially unexpected electricity network loads on the Low Voltage (LV) network.

Powered by satellite navigation technology, it monitors subsystems and power lines. It uses sensors that combine a range of timing tools – including satellite navigation signals and the eLoran longwave radio system – to build up a data picture accurate to a few billionths of a second. 

“The power distribution system was never built to handle the power flows required for electric vehicles. There is a significant lack of data in most low-voltage substations, so distribution companies are often operating in the dark in terms of localised power surges or outages,” said Brian Lasslett, Head of IP, FUNDAMENTALS. “The ENERSYN project provides early warning of potentially dangerous electricity network failures equipping network operators with the data they need to make decisions, fast.”

More is being asked of power grids than ever before with distributed network operators facing challenges in balancing generation and demand at a local level.  It is estimated there will be over 11 million electric vehicles on British roads by 2030 and by 2050 up to 80% of households with an electric vehicle will be ‘smart charging’ their car. The ENERSYN platform provides early visibility of increasing load on the LV network considering the combination of normal/peak load, EV charging load and other unscheduled and unexpected loads. This means that operators can manage the connection of loads such as EV charging, and balance generation and demand efficiently at a local level.

Richard Swinden, Technical Officer at the European Space Agency said: “Never before has GNSS technology been used to insert an intelligent sense of place and time to power grids in this way. This project has demonstrated we can provide an early warning of potentially dangerous electricity network failures and has shown a new approach to turn power grids into smart systems.”

The contract was conducted over two years, from 4th April 2018 to 31st March 2020 and was supported through the ESA’s Navigation Innovation and Support Programme (NAVISP). The next stage of the project is to propose a Network Innovation Allowance with a wide group of Distributed Network Operators.

Background on the ENERSYN project

The early warning system uses machine learning and big data techniques combined with deep industry knowledge to deliver high speed, time synchronised measurements of voltage and current waveforms. If a change in load due to an electric vehicle being charged or a power surge occurs, the system takes hundreds of snapshots of electricity current and voltage every second to allow further analysis that could help predict and balance load demand. For more information, please visit: https://navisp.esa.int/project/details/26/show

About ESA’s NAVISP Programme

Since 2017, the Navigation Innovation and Support Programme (NAVISP) encourages European industry - Large system integrators as well as SMEs and Start-ups -, but also Universities, Research Institutions and public entities to generate new exciting ideas within the Positioning, Navigation and Timing (PNT) sector, through the following axis:
Element 1: Fostering innovation in satellite Navigation through competitive.
Element 2: Boosting the development of PNT competitive products.
Element 3: Supporting PNT National Programmes of Member States.
More information on https://navisp.esa.int