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| Reference Number | NIA2_NGET0052 | |
| Title | Detailed Analysis of Transformer Ageing Mechanisms for Intelligent Estimation of Reliability - DATAMInER | |
| Status | Started | |
| 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 2024 | |
| End Date | 31 March 2026 | |
| Duration | ENA months | |
| Total Grant Value | £1,850,000 | |
| Industrial Sectors | Power | |
| Region | London | |
| Programme | Network Innovation Allowance | |
| Investigators | Principal Investigator | Project Contact , National Grid Electricity Transmission (100.000%) |
| Industrial Collaborator | Project Contact , National Grid Electricity Transmission (0.000%) |
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| Web Site | https://smarter.energynetworks.org/projects/NIA2_NGET0052 |
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| Objectives | NGET has, over many years, used research to improve its understanding of the ageing mechanisms of transformers and how to detect when a transformer is approaching end of life. In combination with a strategy for analysis of retired assets, the knowledge gained through innovation has enable NGET to extend transformer asset lives and reduce capital investment. Through further university-based research we will continue to develop our understanding through lab testing and aligning indicators with specific transformer designs. As part of the project, we will extend our understanding of ageing mechanisms and indications in mineral oil filled transformers to those filled with esters.This work will consider the factors that affect variability in service aged wound plant and take account of them in retrospective analysis of NGET data and in better models for understanding how ageing markers traditional or novel may be better evaluated to understand winding condition. The research will involve in depth data analysis, development of both digital and physical models to represent transformer internal workings, wet chemistry and various analytical chemistry techniques. Wound plant ageing mechanisms have been studied in depth in laboratory conditions and understanding of in-service systems has largely focussed on furans and, more recently, alcohols that are produced when cellulose based solid insulation breaks down. Laboratory studies show good correlation between the presence of these breakdown products in the insulating liquid and the condition of the paper as measured by degree of polymerisation. However, in service assets are more complex systems than laboratory models and the correlations are not always as clear. The difference between models and reality tends to reduce certainty around when wound plant may reach a state requiring replacement until a few years before it reaches that point when ideally replacement decisions could be made earlier. This project seeks to explain the difference between laboratory ageing studies of insulation systems for wound plant and service aged assets.The project will develop guidance for interpretation of ageing markers in wound plant for more accurate understanding of the insulation system and for longer term visibility of when an asset may need to be replaced.The project will extend understanding of mineral oil filled assets to those filled with esters as these become more widely used. | |
| Abstract | The application of laboratory studies to in-service transformers is often only indicative rather than leading to accurate assessment of remaining asset life. Challenges with interpretation of chemical markers measured through oil sampling of in-service transformer are uncertainties in production, partitioning and stability. These uncertainties tend to make it harder to predict when transformers have reached end of life until they are already almost in that state. More predictability of degradation over a longer time horizon will enable more efficient planning.This project aims to improve our understanding of insulation ageing for in-service assets and to make better assessments of when wound plant is likely to reach end of life. | |
| Data | No related datasets |
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| Projects | No related projects |
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| Publications | No related publications |
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| Added to Database | 18/09/24 | |
