Abstract

Detection of the axial displacement of power-transformer winding is important to ensure its highly reliable operation. Frequency response analysis is a promising candidate in detecting the axial displacement. However, a method of detecting the axial displacement at an incipient stage without the need for fingerprint data has not been investigated yet. This paper focuses on resonances showing a bipolar signature in the transfer function of inductive interwinding measurement, which is sensitive to the axial displacement of the winding. Transfer functions in the inductive interwinding measurements of eight power transformers are measured before shipping to elucidate the features of resonances showing a bipolar signature. The measured resonances showing the bipolar signature can be divided into the “stair type” and the “crossing-curve type”. It is found that the grounding points in an inductive interwinding measurement determine the type of resonance showing the bipolar signature, irrespective of the type of winding, such as interleaved or multilayer winding, the winding arrangement, and the existence of stabilizing and tertiary windings. On the basis of this finding, a method of detecting the axial displacement of a transformer winding is proposed. In the proposed method, the amplitudes of the resonances among three phases are compared, or the three-phase pattern of the resonances is compared with normal patterns. Therefore, the proposed method is applicable to three-phase transformers without fingerprint data. The proposed method is applied to a real transformer that experienced a ground fault due to a lightning strike at a nearby transmission tower, and the effectiveness of the proposed method is confirmed.

Highlights

  • Power transformers are one of the key apparatuses in electric power networks

  • This paper proposes a detection method for AD at the incipient stage, i.e., less than 1% of the winding height, without the need for fingerprint data

  • TFs in inductive interwinding (IIW) measuremTeFnstinofIItW ranmsfeoarsmuerresmwenerteomf teraasnusrfoedrmbeerfsorweetrheemy weaesruereshdipbpefeodre they were shipped to elucidate the featutroeseloufcRidBaStes, twhehifcehatvuarreys doufeRtBoSAs,Dw. hTihcehmveaarysudreude RtoBSAsDca. nThbee mdie- asured RBSs can be vided into two groupdsi:vtihdeedstianirtotytwpeoagnrdouthpes:ctrhoesssintagi-rctuyrpvee atynpde.thIte wcraosssfoinugn-dcutrhvaet ttyhpee

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Summary

Introduction

Power transformers (hereafter referred to as transformers) are one of the key apparatuses in electric power networks. The amount of AD investigated in [27] is not presented; it would be around 10% because the simulated variation in the capacitance between the high-voltage (HV) and the low-voltage (LV) winding is 10% Such a large AD would result from breakage of the clamping structure into fragments, which will probably be followed by catastrophic electric faults such as a turn-to-torn short, a ground fault, and an arcing discharge. Even when there are no fingerprint data and the quantitative AD diagnosis method cannot be applied, diagnostic information, such as whether the winding is axially displaced, will be useful in the maintenance and replacement planning of transformers [30]. This paper proposes a detection method for AD at the incipient stage, i.e., less than 1% of the winding height, without the need for fingerprint data. The comparison reveals the effectiveness of the proposed detection method of AD at the incipient stage by FRA without the need for fingerprint data

Review of AD Diagnosis by FRA
Accumulation of Data of Normal Transformers without AD
Findings
Conclusions

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