The Application of Correlation Technique in Detecting Internal and External Faults in Three-Phase Transformer and Saturation of Current Transformer

Etumi, Adel Ali Amar; Anayi, Fatih

doi:10.1109/tpwrd.2016.2572608

Cited by 32 publications

(18 citation statements)

References 18 publications

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“…Power transformers are an important part of the power system [1,2]. Failure of power transformers may lead to interruption of power supply and loss of profit.…”

Section: Introductionmentioning

confidence: 99%

Transformer Fault Diagnosis Model Based on Improved Gray Wolf Optimizer and Probabilistic Neural Network

et al. 2021

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Dissolved gas analysis (DGA) based in insulating oil has become a more mature method in the field of transformer fault diagnosis. However, due to the complexity and diversity of fault types, the traditional modeling method based on oil sample analysis is struggling to meet the industrial demand for diagnostic accuracy. In order to solve this problem, this paper proposes a probabilistic neural network (PNN)-based fault diagnosis model for power transformers and optimizes the smoothing factor of the pattern layer of PNN by the improved gray wolf optimizer (IGWO) to improve the classification accuracy and robustness of PNN. The standard GWO easily falls into the local optimum because the update mechanism is too single. The update strategy proposed in this paper enhances the convergence ability and exploration ability of the algorithm, which greatly alleviates the dilemma that GWO is prone to fall into local optimum when dealing with complex data. In this paper, a reliability analysis of thirteen diagnostic methods is conducted using 555 transformer fault samples collected from Jiangxi Power Supply Company, China. The results show that the diagnostic accuracy of the IGWO-PNN model reaches 99.71%, which is much higher than that of the traditional IEC (International Electrotechnical Commission) three-ratio method. Compared with other neural network models, IGWO-PNN also has higher diagnostic accuracy and stability, and is more applicable to the field of transformer fault diagnosis.

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“…Power transformers are an important part of the power system [1,2]. Failure of power transformers may lead to interruption of power supply and loss of profit.…”

Section: Introductionmentioning

confidence: 99%

Transformer Fault Diagnosis Model Based on Improved Gray Wolf Optimizer and Probabilistic Neural Network

et al. 2021

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“…The distance Dn between the centralized test sample, gtest, and the n th sample in G, gn, can be calculated based on the (8) where cov represents the covariance between gtest and gn. σ means the standard deviation of the vector.…”

Section: B Repairing Methods Based On Improved Knnmentioning

confidence: 99%

“…Details of the weight calculation method can be found in [42]. A smaller distance in (8) results in a larger weight in the estimation of the missing data, which indicates its greater similarity to the test sample gtest.…”

Section: B Repairing Methods Based On Improved Knnmentioning

confidence: 99%

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A Data Mining Approach for Transformer Failure Rate Modeling Based on Daily Oil Chromatographic Data

Huang

et al. 2020

IEEE Access

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“…When the phase difference is α , ρ xy = cos α . There are many usages for an electric power system by utilizing the correlation coefficient to judge phase relation of two signals, such as inrush current discrimination , differential protection , fault judgment and fault phase selection .…”

Section: Theory Of Discriminating Fault Side Based On Correlation Coementioning

confidence: 99%

Selective‐tripping scheme for power supply arm on high‐speed railway based on correlation analysis between feeder current fault components in multisite

Lin

Gao

2019

IEEJ Transactions Elec Engng

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Auto-transformer (AT) power traction networks with a parallel connection are the unique mode on high-speed electric railways in China. The up line and down line of power traction networks are connected at substation (SS), AT post (ATP) and sectioning post (SP) through busbars, circuit breakers and disconnectors. Currently, when a fault occurs on power traction networks, the feeder line protection devices at the up line and down line in SS trip simultaneously. After that, the nonfault line and instantaneous fault line recover by means of autoreclosing. This tripping mode enlarges the power supply-interrupted region. Based on the analysis of circuit networks of power traction networks on high-speed electric railways, the interrelations of currents in SS and ATP and in SS and SP are derived. When a fault occurs on one side of the power traction networks, the feeder currents in ATP and SP flow from the nonfault side to the fault side. The relation between feeder currents in SS and ATP and between feeder currents in SS and SP reflect this characteristic. A criterion for discriminating the fault side and selective-tripping scheme of breakers is proposed based on the correlation analysis of feeder current fault components in multisite. The simulation results show that this scheme can discriminate fault side and make a selective trip rapidly and correctly.

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The Application of Correlation Technique in Detecting Internal and External Faults in Three-Phase Transformer and Saturation of Current Transformer

Cited by 32 publications

References 18 publications

Transformer Fault Diagnosis Model Based on Improved Gray Wolf Optimizer and Probabilistic Neural Network

Transformer Fault Diagnosis Model Based on Improved Gray Wolf Optimizer and Probabilistic Neural Network

A Data Mining Approach for Transformer Failure Rate Modeling Based on Daily Oil Chromatographic Data

Selective‐tripping scheme for power supply arm on high‐speed railway based on correlation analysis between feeder current fault components in multisite

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