Dec 2012
Electricity Transmission
Prognostics and Health Monitoring of Grid Connected Assets
NIA_SHET_0002
Complete
Dec 2012
Jun 2016
Scottish and Southern Electricity Networks and Scottish Hydro Electric Transmission
SSEN Future Networks Team
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Network Innovation Allowance
None
Comms & IT and Asset Management
£158,550.00
Improving asset management capabilities in line with the Smart Grid principle e.g. more intelligent monitoring of assets’ remaining life. PHM is, broadly speaking, the science of analysing the operating and environmental parameters of a system and using those data points to predict the remaining useful life of the system. PHM generally falls into three categories: Data Driven, Physics of Failure and Fusion. Data Driven prognostics uses historical knowledge of the system to build statistical models that can predict system condition and system life. Physics of Failure prognostics uses the underlying physics of an identified failure mechanism to predict the progression of the failure. Fusion prognostics take both of these models and fuse their results to obtain a broader and more accurate measure of failure.

·    Conduct a literature review of PHM, gain understanding of the various tools used and identify optimal tools for use with this project

·    Undertake a small initial relay based project using knowledge from the literature review to consolidate project researchers’ experience in the concepts of PHM

  • ·    Develop and optimise an online oil condition monitoring and prognostics system prototype

Test the prototype on a decommissioned SHE Transmission grid transformer and evaluate its cost-effectiveness

The learning generated from this project will directly benefit all transmission network licensees and Distribution Network Operators since they are all running ageing assets. The system can potentially provide better and more accurate assessment of an operational transformer’s health and condition and help system planners make informed asset management decisions.

Should the project be successful other network licensees could find use of the technology in assessing other assets on the grid thereby extending the potential financial benefits from the system.