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Projects: Projects for Investigator
Reference Number	NIA_SSEN_0051
Title	Synaps 2 - Fault Detection, Classification & Location Solution
Status	Completed
Energy Categories	Other Power and Storage Technologies(Electricity transmission and distribution) 100%;
Research Types	Applied Research and Development 100%
Science and Technology Fields	ENGINEERING AND TECHNOLOGY (Electrical and Electronic Engineering) 100%
UKERC Cross Cutting Characterisation	Not Cross-cutting 100%
Principal Investigator	Project Contact No email address given Scottish and Southern Energy Power Distribution
Award Type	Network Innovation Allowance
Funding Source	Ofgem
Start Date	01 December 2020
End Date	01 July 2022
Duration	ENA months
Total Grant Value	£661,140
Industrial Sectors	Power
Region	Scotland
Programme	Network Innovation Allowance
Investigators	Principal Investigator	Project Contact , Scottish and Southern Energy Power Distribution (99.999%)
	Other Investigator	Project Contact , UK Power Networks (0.001%)
	Industrial Collaborator	Project Contact , Scottish and Southern Energy plc (0.000%)
Web Site	https://smarter.energynetworks.org/projects/NIA_SSEN_0051
Objectives	The SYNAPS 1 project closedown report identified that:- SYNAPS detects a transient or “pecking” fault event of short duration, usually shorter than 1 cycle, and lower energy that does not rupture a fuse or does not trigger an LV network circuit breaker- SYNAPS can classify the type of fault (phase-to-phase or phase-to-neutral)- The SYNAPS AI algorithm assigns a classification to an event to predict whether the fault occurred along the main cable or a spurThe SYNAPS (synchronous analysis and protection system) solution will be deployed in substations and feeder link-boxes/feeder pillars. It applies innovative algorithms to power waveforms to detect and classify fault events.SYNAPS uses state-of-the-art advanced statistical signal processing and machine learning algorithms to identify unique features of LV feeder cable faults (including early transient faults). A high sample rate detector is then employed. When a manifesting fault is detected the sensor records the fault waveform and transmits data to the server software for further processing. The server software classifies fault type and location (target accuracy 3m) utilising Powerline Technologies (PLT) proprietary algorithms.Existing solutions use voltage/current analysis that give an approximate location of the fault, which is then pinpointed with gas sniffers and thermal cameras. These techniques are mainly used for permanent faults.Returned SYNAPS data enables the DNO to make significant reductions in the cost of LV network operations. The detection and location of faults at an early stage, before they become permanent, will facilitate efficient asset cable replacement schemes rather than expensive reactive emergency action. The Project will be organised into two trial stages:- Basic Fault Location (3-4 months duration) will be trialled on two sets (four units) of the existing generation of prototype sensors to collect more data to improve the algorithm model for the advanced fault location stage- Advanced Fault Location (8-9 months duration) will be trialled on ten sets of next generation sensors to continue collecting the data while improving the algorithms on different cable architectures and fault scenarios.There will be a project review after 6 months. Basic Fault LocationThis will continue from the previous SYNAPS 1 project — the installation of the current sensors on LV feeders with known faults to determine their location. This work will focus on optimising the network calibration procedure and tuning the location technology to improve accuracy of the fault information and minimise the time required to generate it.Once a fault is identified the equipment will be moved between feeder locations at regular intervals after liaison with UKPN. This will allow continued collection of fault data in multiple cable type environments. Fault location information will be communicated to asset teams for investigation and validation. DNO Operational IT System Connection Specification Development of a specification for an interface between the SYNAPS cloud server and DNO operational IT systems to enable DNO operational staff to be informed in real time when LV faults are detected on specific feeders and to provide fault location information when this is available. The target system will be determined through mutual discussion between the NIA partners and could include iHost or similar platform. Advanced Fault Location This will be based on around ten sets of the next generation SYNAPS sensors. These will be divided between SSEN and UKPN and the installation of the sensors will be on LV feeders with known faults and/or fault history. In addition to increasing the number of data collection sites, this work package will also aim to test and validate the technology in support of the following use cases:- Low voltage networks that run in parallel known in the industry as fully meshed networks- Long Term Fault Evolution. Investigation of the network disturbances noted in SYNAPS 1 project. to determine which are early faults, to follow their evolution into permanent faults, to seek to determine at what stage they can be located and to ascertain the scope for predicting the time before they become critical.- Investigate if faults can be identified as either cable or joint faults. Prototype DNO Operational IT System Connection Based on the “DNO Operational IT System Connection specification” developed above, implementation and testing of a working interface between the SYNAPS system and the DNO Operational IT system.Business as Usual Demonstration A demonstration of the final TRL8 commercial prototype will be carried out on the distribution network with the intent to demonstrate the solution in a network environment and to evaluate the data connectivity.
Abstract	This will continue from the previous SYNAPS 1 project — the installation of the current sensors on LV feeders with known faults to determine their location. This work will focus on optimising the network calibration procedure and tuning the location technology to improve accuracy of the fault information and minimise the time required to generate it.
Publications	(none)
Final Report	(none)
Added to Database	02/11/22