Title
SYNAPS - SYNchronous Automation and Protection System

CoPED ID
b6b6164d-9b28-4e24-8d56-cf7d6906c0c2

Status
Closed

Funders

Value
£486,570

Start Date
May 31, 2015

End Date
May 30, 2017

Description

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SYNAPS is an innovative project which brings together experts from the power engineering, powerline communications,
and statistical signal
processing communities to target the so-termed energy trilemma, namely the challenge to improve energy security, reduce
carbon emissions, and reduce costs.
SYNAPS aims to develop a networked distribution automation platform for low-voltage networks which will provide fault
detection, classification and location of faults, together with smart protection and reconfiguration, at a significantly lower
cost than has previously beenpossible. In effect, this project will add a cost-efficient smart layer across the national power
grid which will not only solve long-standing, industry-wide challenges but will also open up countless other opportunities for
stable, future-proofed growth as our cities and infrastructure become smarter and progress to the internet-of-things future.
Since the low-voltage network was originally intended for one-way distribution of energy, there has been little previous
interest in monitoring it. However, there is now a new imperative created by the impact on network stability due to the
growing deployment of consumer operated renewable distributed generation equipment, electric vehicles - not to mention
the 'exploding pavements' issue.
Currently, distributed generation amounts to only a small proportion of the total network generating capacity, hence its
impact on low-voltage
network performance is negligible. However, there is significant industry concern about the effects of increased numbers of
distributed generation and electric vehicle installations, especially when these are concentrated in co-located clusters.
The low-voltage electricity network needs to be able to support two way electrical flow and real-time communication. About
9% of electricity is lost in the distribution network, annually, and it has been reported that 45% of Distribution Network Operator total network costs and 50% of
customer minutes lost are due to low-voltage cable faults.
Managing these new low carbon technologies present significant challenges but early preparation and introduction of a
Smart Grid should make the transition easier and reduce overall costs. This project will draw upon machine learning
methodology to automatically monitor
low-voltage networks and detect and localise both known, and anomalous, problem events. Furthermore, algorithms will
also be progressed to
support software-based protection and reconfiguration of the network.
It is anticipated that such smart sensor networks will make a significant contribution in network efficiency and futureproofing,
and have immense benefits for both consumers and EU/UK environmental and energy policy targets.


More Information

Potential Impact:
The main direct beneficiaries will be all LV electricity network users through the eventual real-world deployment of SYNAPS
technology. This encompasses the vast majority of the general public, including consumers, producers, and increasingly,
"prosumers", who both generate electricity and consume it. These stakeholders will benefit through improved availability of
the LV network due to the combination of pro-active, scheduled maintenance, intelligent and safe fault handling and optimal
post fault reconfiguration.
Within the electricity industry, Distribution Network Operators (DNOs) are the key direct beneficiary, particularly in the
following ways:
- Through a reduction in customer minutes lost and thus reduced financial penalties and improved public relations.
- To enable them to operate more complex, active LV networks resilient to a greater penetration of heterogeneous lowcarbon
devices, moving towards largely self-sufficient micro-grids.
- By mitigating congestion at higher voltage levels through increased availability of the LV network.
- Increased overall real-time visibility of complex LV networks that are poorly documented, and have, since the dawn of
electrification, grown organically and incrementally to a sub-optimal final result.
The industrial partners in the consortium, PowerLine Technologies, Tehnca International Ltd and Akya Ltd, will benefit from
the business generated by their new hardware and software solutions, that exploit a tangible, quantifiable and compelling
market opportunity.
SYNAPS will bring transmission-level intelligence to the LV network, and thus massively increase the robustness of LV
networks to low carbon stresses, such as micro-generation and electric vehicles. Facilitating the connection of such
devices is a vital step in the modernisation of the LV network and ultimately the realisation of the smart grid paradigm.
Smart grids must become a reality to deliver the de-carbonisation of heat and transport, solve the energy trilemma, meet
legally binding emissions targets and ensure a globally sustainable future.

Simon Le Blond PI_PER
Miles Redfern COI_PER

Subjects by relevance
  1. Distribution of electricity
  2. Electrical power networks
  3. Networks (societal phenomena)
  4. Information networks
  5. Energy policy
  6. Data communications networks
  7. Networking (making contacts)
  8. Electricity
  9. Power-line communication
  10. Infrastructures
  11. Emissions
  12. Automation
  13. Cooperation (general)
  14. Objectives
  15. Production of electricity
  16. Signal processing
  17. Smart grids
  18. Machine learning
  19. Power engines
  20. Innovations

Extracted key phrases
  1. LV electricity network user
  2. SYNAPS
  3. Voltage electricity network
  4. Distribution Network Operator total network cost
  5. Active LV network resilient
  6. Complex LV network
  7. Voltage network
  8. Smart sensor network
  9. Distribution network
  10. Network performance
  11. Network stability
  12. Network efficiency
  13. SYNchronous Automation
  14. Protection System
  15. New low carbon technology

Related Pages

UKRI project entry

UK Project Locations