Dielectric Loss Factor Measurement in Power Systems Based on Sampling Sequence Reconstruction Approach

Li, Jianmin; Teng, Zhaosheng; Tang, Qiu; Song, Junhao; Li, Xiaoju

doi:10.1109/tpel.2016.2602232

Cited by 15 publications

(3 citation statements)

References 18 publications

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“…Moreover, the transient overvoltage of primary voltage, partial discharge, and resonance overvoltage may cause irreversible damage to insulation dielectric, reduce the breakdown strength of CVT and directly lead to the capacitor's breakdown in severe cases. In contrast to insulation dielectric having many mature research methods 6,7,8,9 , capacitors do not have appropriate parameters to accurately diagnose the state of capacitors. Therefore, this paper presents capacitor breakdown, the main form of deterioration in CVT.…”

Section: 1the Insulation Structure Of Cvtmentioning

confidence: 99%

The online diagnosis of internal insulation fault of capacitance voltage transformers based on machine learning

Wei

Tao

Fang

et al. 2022

J. Phys.: Conf. Ser.

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In order to diagnose internal insulation faults of CVT in time, an online diagnosis method for the internal insulation performance of CVT is proposed in this paper. The relationship between CVT insulation performance and measured data is obtained by analyzing CVT internal insulation structure and transfer function. After constructing an appropriate eigenvector by the inter-group correlation amplitude parameter of CVT, three methods of SVM, Bayes, and KNN are used as classifiers for insulation fault diagnosis. The experiment result shows that KNN method can effectively diagnose internal insulation faults with an accuracy rate of 100%.

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Section: 1the Insulation Structure Of Cvtmentioning

confidence: 99%

The online diagnosis of internal insulation fault of capacitance voltage transformers based on machine learning

Wei

Tao

Fang

et al. 2022

J. Phys.: Conf. Ser.

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show abstract

“…The hardware methods mainly include zero comparison [10 ] and Schering Bridge [11 ], which have some drawbacks such as the low precision, difficult compensation and poor anti‐interference ability. The software methods mainly include correlation function algorithm [12 ], higher‐order sine fitting algorithm [13 ], fast Fourier transform (FFT) [14 ], fundamental harmonic separation algorithm [15 ] and so on, which are characteristic of the low cost, high precision and good anti‐interference ability, so they are the main method to calculate the power angle.…”

Section: Introductionmentioning

confidence: 99%

Research on the online measuring technology of inter-turn insulation of dry air-core reactor

Huang

Zhu

et al. 2020

IET Science, Measurement &Amp; Technology

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The fault model of the inter‐turn short circuit of the dry air‐core reactor is first analysed in this study, by which an online monitoring method of the reactor inter‐turn insulation fault is proposed by using the change of the power angle. In order to achieve high‐precision measurement, the fundamental harmonic separation algorithm improved by Hanning windowed interpolation method can effectively reduce the error of power angle measurement caused by frequency fluctuation and harmonic interference. By comparing it with the power angle measurement errors of fast Fourier transform (FFT) and Hanning window interpolation FFT, the algorithm is verified. The sensitivity and stability of the equipment are verified by the experiment of simulating and eliminating the fault in the initial stage of the inter‐turn short circuit. At the same time, an online monitoring system for inter‐turn insulation fault of dry‐type air‐core reactor based on this method is designed, including field monitoring device, the intelligent electronic device of the dry air‐core reactor and expert software. The method and monitoring device proposed in this study enables the fault to be accurately monitored in the early stage, which is of great significance for the safe operation of the reactor.

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“…In recent years, some insulation condition monitoring methods with brand-new concepts have been proposed. Li proposed a dielectric loss factor measurement approach based on sampling sequence reconstruction for capacitive equipment 10 , this method also needs to monitoring a) Electronic mail: wfr101@163.com the voltage and current synchronously, and it is not particular to CVTs, the specific type of insulation faults cannot be diagnosed. Daryani proposed an evidence theory-based insulation aging identification approach for CVTs 11 , the output voltage, the negative sequence components, the zero sequence components and the park transformation parameter of groups of CVTs are considered to generate the indicators of insulation condition, but the case studies illustrate that this method could only detect more than three capacitors outage, the dielectric loss is not considered in it.…”

Section: Introductionmentioning

confidence: 99%

Internal insulation condition identification for high-voltage capacitor voltage transformers based on possibilistic fuzzy clustering

Zhan

Chen

et al. 2020

Review of Scientific Instruments

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The internal insulation condition of capacitor voltage transformers (CVTs) is a key influence factor to its measurement performance and safe operation, but the internal insulation would be aged along with long-time operation and degraded influenced by environmental factors, once the insulation degradation grows, serious damages and even explosion may happen to CVTs, so it is necessary to monitor the internal insulation condition of CVTs, and the fault type and fault degree need to be identified. In this paper, a data-driven internal insulation condition identification method for CVTs is proposed. Both the amplitude and phase of the output voltage of CVTs are collected, then recognition models based on the combination of the output voltages and distribution topology of CVTs in substations are built, a possibilistic fuzzy clustering method is used to monitor the internal insulation condition of CVTs, different type and different degree of insulation faults could be identified effectively. Finally, the proposed method is verified by several cases, not only the preset typical faults in the method can be identified effectively, but also the faults beyond the preset faults could be diagnosed.

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Dielectric Loss Factor Measurement in Power Systems Based on Sampling Sequence Reconstruction Approach

Cited by 15 publications

References 18 publications

The online diagnosis of internal insulation fault of capacitance voltage transformers based on machine learning

The online diagnosis of internal insulation fault of capacitance voltage transformers based on machine learning

Research on the online measuring technology of inter-turn insulation of dry air-core reactor

Internal insulation condition identification for high-voltage capacitor voltage transformers based on possibilistic fuzzy clustering

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