UK Power Networks, Eastern Power Networks, London Power Networks and South Eastern Power Distribution
Kelvin Lee & Ayodele Ogunjumo
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Network Innovation Allowance
ED - Network improvements and system operability
Asset Management, Environmental, Health and Safety, Maintenance & Inspection and Measurement
UK Power Networks owns and operates Gas Insulated Switchgear (GIS), and some of them use Sulfur hexafluoride (SF6) as an electrical insulator. SF6 is an extremely good electrical insulator, is not poisonous to humans and has other advantageous engineering properties. However, SF6 is a potent greenhouse gas. Managing potential leaks of SF6 is increasingly important with the UK working to meet its Net Zero targets, and for UK Power Networks’ to meet its own environmental targets.
There is a large population of GIS on the network that are legacy models and no longer supported by manufacturers. However, they are still in good condition. One example is F35 GIS made by Areva (now GE).
It has been identified that enhanced monitoring of this asset could be beneficial in identifying developing faults. For example, if localised heating caused by loose connections in circuit breakers could be monitored, the asset could be switched out and maintained before failure occurred.
The objectives of the project are to:
· Test whether or not the DTS fibre technology can detect temperature changes as small as 0.5 degree Celsius outside of a chamber containing SF6 subjected to heating
· Correlate changes in temperature to the pressure of SF6 gas in a controlled environment
· Test a 132kV system in a live environment which aims to ascertain the relationship between load and temperature, and prove that sensible alarm levels can be configured to effectively discount heating effects due to load only and highlight heating due to incipient failure
· Prove that the integration and remote access of condition data will not be an issue during Business-As-Usual
The desired outcome of the project is to prove whether or not DTS fibre technology is a sensible solution to predict the presence of abnormal heating/hot spots in GIS in order to prevent disruptive failure.