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Projects: Projects for Investigator
Reference Number NIA_NGET0204
Title Frequency Response Analysis for Transformer Characterisation and Objective Interpretation of Results
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
National Grid Electricity Transmission
Award Type Network Innovation Allowance
Funding Source Ofgem
Start Date 01 January 2017
End Date 01 January 2021
Duration 48 months
Total Grant Value £340,000
Industrial Sectors Power
Region London
Programme Network Innovation Allowance
Investigators Principal Investigator Project Contact , National Grid Electricity Transmission (100.000%)
Web Site http://www.smarternetworks.org/project/NIA_NGET0204
Objectives The objective of this project is to improve our understanding of FRA results, with a view to establishing a method of automatically determining what specific differences in FRA mean in terms of design changes or winding damage. This project will be deemed successful if the database of FRA results is created; the data can be parameterised so that comparisons can be made and similar transformers identified; known design features can be correlated and quantitative measures can be developed to determine whether transformer damage has occurred.
Abstract Frequency Response Analysis (FRA) is a measurement carried out on transformers both in the factory and in service to determine the complex relationship between electrical impedance and frequency. The result is a bit like a fingerprint for a particular transformer design which will change if the transformer is damaged internally and is different for each design. With the knowledge gained by this project it should be possible to more accurately identify which design category a transformer belongs to and focus the asset replacement plan on the most reliable designs. FRA results have been collected for many years on all new transformers and on many in service units. This is primarily in order to establish a benchmark for future occasions when it is needed to use FRA to determine if the transformer has been damaged by a high current event, such as, a short circuit on the terminal or a tap-changer fault. It may be possible to use this accumulated data for asset management. Specifically, the asset management of transformers depends heavily on being able to identify which transformers are of the same design within the tank, or which ones share particular design features that may have a bearing on the expected lifetime of the unit. An example of this would be the presence or absence of stress rings with a poor performance record within a group of externally identical units. Often the original manufacturer of the transformer is no longer in business and the availability of information on internal details is patchy at best. Previous studies undertaken by the University of Manchester, established that it is possible to reduce the raw FRA data into a limited number of key parameters that can be easily compared between transformers in the database. At present FRA interpretation and comparison is a manual process that is hard or impossible to do if a large number of records are to be compared. The method this four year PhD iCase seeks to advance, is to improve the usefulness and understanding of FRA results. This project involves establishing a database of FRA results, in a common format, to enable automatic processing, parameterising the data to enable records to be compared and similar transformers identified and correlating FRA characteristics with known design features. This project will run in parallel with, and to some extent be guided by, work within the A2. 52 Cigre working group.Note : Project Documents may be available via the ENA Smarter Networks Portal using the Website link above
Publications (none)
Final Report (none)
Added to Database 15/08/18