Partial discharge (PD) is the most common sources of insulation failure in power transformers. The most important tools for quality assessment of power transformers are PD detection, measurement, and classification. As for the maintenance and repair of transformers, the major importance is the techniques for locating a PD source. The transfer function-based (TF) method for power transformers' winding in the high-frequency range is commonly used in power engineering applications, such as transient analysis, insulation coordination, and in transformer design. Although it is possible to localize PD in transformer winding using the transfer function (TF) method, this method cannot be used for transformers with no design data. Previous attempts toward finding a feature that localizes PD in transformers in general that lineate with PD location were found to be less successful. Therefore, in this paper, a neuro-fuzzy technique that uses unsupervised pattern recognition was proposed to localize PD source in power transformers. The proposed method was tested on a medium-voltage transformer winding in the laboratory. The results showed a significant improvement in localizing PD for major types of PD compared to currently available techniques, such as orthogonal transforms and the calibration line method.

Partial Discharge Localization in Power Transformers Using Neuro-Fuzzy Technique

Denoising is a key step in diagnosis and evaluation of partial discharge (PD) signals in power transformers. In this paper, a new PD signal denoising algorithm is presented, which is based on the combination of dual-tree complex wavelet transform (DTCWT) and adaptive singular value decomposition (ASVD). This new algorithm, which is introduced as adaptive DTCWT (ADTCWT), was evaluated through simulations and experimental tests. ADTCWT was employed in denoising from PD signals based on the selection of best singular values in each DTCWT level decomposition, corresponding to PD signal and noise. The superior performance of the ADTCWT algorithm was demonstrated using various indices in comparison with those of DTCWT and ASVD methods in noise reduction, besides preserving time of arrival of PD signals and PD localization.

A New Partial Discharge Signal Denoising Algorithm Based on Adaptive Dual-Tree Complex Wavelet Transform

The application of the XLPE cable under DC stress is now being considered as one of the promising tool for enlarging the limited transmission capacity of the traditional electric power cable due to the several technical advantages. Therefore, many research institutes are trying to improve the performance by carrying out experimental investigations related to the reliability of the cable to be used under DC stress. One of them is partial discharge (PD) detection, which is considered as the tool to indicate the insulation state of the apparatus; however, very few reports have been published based on the results obtained for the XLPE cable used under the DC stress. In this work, three different types of artificial defects are designed to produce PD under DC: void, surface and corona discharge defects. Pattern recognition of the detected PD signal is based on modified CAPD method. To improve the PD pattern recognition rate, the training data obtained through neural networks is combined with the results of the frequency domain analysis. Finally, the training data and mean square error of PD patterns obtained through neural networks is compared with the training data obtained with the use of only modified CAPD method.

Neural network based diagnosis of partial discharge defects patterns at XLPE cable under DC stress

Partial Discharge localization on cross-bonded cable systems

Correlation between surface charge and creepage discharge on polymeric dielectrics under high-frequency high-voltage stress

In the long electric equipment such as cables and GIS, it is very important to find out the location of the partial discharge(PD) source. In this study, PD location method was studied using arrival time difference and polarity of the pulses obtained from separately installed 2 sensors. For the purpose, pulse arrival time and pulse polarity analysis algorithm were developed. From the experiment for the long power cable, the proposed algorithm and the system were verified. Also, for the case of long cable system, the optical fiber transmission system including E/O and O/E module was composed and its performance was investigated through the PD experiments.

Partial discharge location using 2 sensors and optical fibers

One of the vital causes of the failure of oil transformers is considered as the creepage discharge propagation on pressboard. The authors performed an experimental investigation under an AC step test voltage to analyse the effects of the structure, distance and gluing direction of pressboard on creepage propagation. Flat, ribbed and grooved test specimens were prepared. Further, breakdown experiments were conducted for two gluing directions, parallel and vertical with respect to the electric field. For parallel gluing, the average breakdown voltage (V BD) of the ribbed and grooved types was 1.2–1.33 times that of the flat type. For vertical gluing, the V BD of the flat type was 1.28–1.66 times that of the same type with parallel gluing, whereas the values for the ribbed and grooved types were 1.02–1.11 times the corresponding values for parallel gluing. The rib height and groove depth do not seem to contribute greatly to the breakdown strength because most of the flashover propagation appeared not on the pressboard's surface but at the glued interface. The results of this preliminary investigation may be useful for improving the dielectric creepage strength of solid insulation systems using pressboard as radial spacers, and high-voltage winding lead support parts.

Experimental investigation of the effect of the design parameters of pressboard in mineral oil on creepage discharge propagation

In order to find out partial discharge (PD) phenomena in the cable joint due to the poor workmanship during the installation, the relationship between PD inception voltages and joint defects was investigated. For the purpose, in the joint of 22.9kV CNCV cables, electric fields were calculated for various semiconductive layer wrong positioning (WP) defects. And, PDIV were investigated through the experiments and compared with the results of electric field analysis. In all WP defect cases, the PD inception field calculated using measured PDIVs was similarly shown to be the average value of 1.84kV/mm. In addition, the calculated PDIV and the measured PDIV were almost equal, from the PDIV calculation using maximum electric fields and the measured PDIV for the normal case. Throughout this study, it is possible to analyze WP defects due to the poor workmanship and to establish better joint design for the distribution grade extruded cable system.

Young-Jo Lee

Papers

Partial discharge location using 2 sensors and optical fibers

Experimental investigation of the effect of the design parameters of pressboard in mineral oil on creepage discharge propagation

Analysis of Partial Discharge Inception Voltages for the Wrong Positioning Defects in the Joint of Distribution Power Cables