Abstract

Conventional dielectric response measurement techniques, for instance, recovery voltage measurement (RVM), frequency domain spectroscopy (FDS) and polarization–depolarization current (PDC) are effective nondestructive insulation monitoring techniques for oil-impregnated power transformers. Previous studies have focused mainly on some single type of dielectric measurement method. However, the condition of oil paper insulation in transformer is affected by many factors, so it is difficult to predict the insulation status by means of a single method. In this paper, the insulation condition assessment is performed by grey relational analysis (GRA) technique after carefully investigating different dielectric response measurement data. The insulation condition sensitive parameters of samples with unknown insulation status are extracted from different dielectric response measurement data and then these are used to contrast with the standard insulation state vector models established in controlled laboratory conditions by using GRA technique for predicting insulation condition. The performance of the proposed approach is tested using both the laboratory samples and a power transformer to demonstrate that it can provide reliable and effective insulation diagnosis.

Highlights

  • An oil-impregnated transformer is commonly considered as one of the most crucial pieces of equipment in the electric power transmission and distribution systems [1,2,3]

  • Except for the abnormal results from the samples with the moisture content of 2.82% which have been aging for 8 days, it could be seen that the polarization current curve of the oil-paper insulation sample with different moisture gradients moved to the upper left as moisture content increases and the tail of the polarization current increased gradually

  • A power transformer in service is employed to verify the grey relational analysis (GRA) analysis based upon conventional dielectric response measurement

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Summary

Introduction

An oil-impregnated transformer is commonly considered as one of the most crucial pieces of equipment in the electric power transmission and distribution systems [1,2,3]. It is a fact that the electrical and mechanical properties of the transformer oil-paper insulation system become aging gradually due to the combination stresses of the mechanical vibration, thermal, electrical, oxygen, water and other factors, in the long-term service process [4,5,6,7,8]. Have been commonly used for performing non-destructive condition monitoring of transformer insulation [9,10,11,12]. The OSA technique only presents limited knowledge about the aging status of transformer solid insulation. GRA technique isdoes that similarities or differences of different factors. The advantage of GRA is that it it does not require a large number of test samples. The grey related algorithm can be depicted not require a large number of test samples.

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