An approach on lifetime estimation of distribution transformers based on degree of polymerization
•Proposing a dynamic aging model of the paper insulation of distribution transformers.•Using degree of polymerization as the condition assessment index.•Consideration of the real operating conditions i.e. loading, ambient temperature and the moisture content.•Determination of the optimum time for im...
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Veröffentlicht in: | Reliability engineering & system safety 2020-06, Vol.198, p.106881-9, Article 106881 |
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Format: | Artikel |
Sprache: | eng |
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Zusammenfassung: | •Proposing a dynamic aging model of the paper insulation of distribution transformers.•Using degree of polymerization as the condition assessment index.•Consideration of the real operating conditions i.e. loading, ambient temperature and the moisture content.•Determination of the optimum time for implementing reductions in moisture content of the paper insulation.
Lifetime of oil-immersed transformers is highly dependent on condition of paper insulation. This contribution is aimed to quantify the deterioration and ageing process of the paper insulation of distribution transformers based on degree of polymerization (DP). The proposed approach involves real operating conditions of a transformer such as variable ambient temperature, load factor, and moisture content of the paper insulation through calculation of hot-spot temperature to estimate remaining lifetime of the transformers. The results indicate that a DP profile obtained based on actual conditions is completely different to that usually discussed in other researches under completely constant conditions. Consequently, the proposed dynamic DP model could predict lifetime of the transformers more precisely based on real-time measurable quantities. In addition to the remnant lifetime estimation, the proposed dynamic DP profile is utilized to suggest the optimum time for implementing reductions in moisture content of the paper insulation through three scenarios regarding the practical limitations. Finally, reliability of the transformer is evaluated based on statistical data. |
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ISSN: | 0951-8320 1879-0836 |
DOI: | 10.1016/j.ress.2020.106881 |