• Proceedings of the KIEE Conference
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• 2004.11b
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• pp.243-245
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• 2004

This paper proposes the discrimination method for the fault location, whether it is within the line where the distributed generation(DG) is integrated or out of the line (but sharing the same bus of the substation). In general, DG has to be disconnected from the grid when the fault occurs on the interconnected distribution feeder as soon as possible. However, the faults occured on the neighboring feeder would mistakenly cause the disconnection of the DG. For reliable operation of DG, DG should be sustained at the fault occurred on neighboring distribution feeders. The proposed identification method utilizes the impedance monitored from the DG and examines the coordination of overcurrent relay of the distribution system. This paper describes how the proposed method to identify the faulted feeder and how the method can be utilized.

• Proceedings of the KIEE Conference
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• summer
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• pp.384-387
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• 2004

The direction and the type of a fault on a transmission line need to be identified rapidly and correctly, The work described in this paper addresses the problem encountered by a conventional algorithm in a fault type classification in double circuit line, this arises due to a mutual coupling and CT saturation under the fault condition. We present an approach to identify fault type with novel neural network on double circuit transmission line. The neural network based on combined unsupervised training method provides the ability classify the fault type by different patterns of the associated voltages and currents.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.51 no.5
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• pp.247-254
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• 2002

This paper describes a fault location algorithm in real combined transmission systems with underground power cable. The algorithm to calculate the fault location was developed using DWT wavelet transform and travelling wave occurred at fault point. And the proposed algorithm is also used the transient signal of one end in stead of the signal information of two ends. On the other hand, in this papers, the method to discriminate fault point between overhead line and cable section is also Proposed. Variety simulations were carried out to verify the accuracy and effectiveness of the proposed algorithm using EMTP/ATFDraw and Matlab. Simulation results show that the proposed method has the excellent ability for discrimination of fault section and fault location in combined transmission systems with power cables.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1376-1378
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• 1999

Most conventional protection relays are based on processing information in the spectrum that is close to or at power frequency. It is, however, widely known that faults on transmission lines produce frequency components of a wide range In this respect, this paper describes the basis of a Protection technique for transmission lines which utilises high-frequency components. Fault-generated signals caused by post-fault and the signal derived from stack tuner is connected to the coupling capacitor of CVT. Digital signal processing is then applied to the captured information to determine whether the fault is inside or outside the Protected zone, and to discriminate the fault type on transmission line.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.67 no.9
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• pp.1146-1151
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• 2018

Recently, researches on the intelligence of electric power facilities have been trying to apply artificial intelligence techniques as computer platforms have improved. In particular, faults occurring in substation should be able to quickly identify possible faults and minimize power fault recovery time. This paper presents fault location technique for 154kV substation using neural network. We constructed a training matrix based on the operating conditions of the circuit breaker and IED to identify the fault location of each component of the target 154kV substation, such as line, bus, and transformer. After performing the training to identify the fault location by the neural network using Weka software, the performance of fault location discrimination of the designed neural network was confirmed.

• The Transactions of the Korean Institute of Electrical Engineers
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• v.40 no.12
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• pp.1203-1210
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• 1991

This paper proposes a new distance relaying method based on fault initiated travelling waves for transmission line protection. The characteristics of this method are ultra high speed and excellent sensitivity. Travelling wave technique which is one of the distance relaying methods uses the discrete cross correlation function for discrimination between internal and external fault is remarkably reduced in case of a close up fault and an inception angle near or equal to zero fault. To cope with this problem, a new fast algorithm which uses backward wave summation method with fixed window is presented. The proposed method has been tested by numerical simulations using the EMTP.

• The Transactions of the Korean Institute of Electrical Engineers P
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• v.57 no.2
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• pp.91-95
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• 2008

The large AC generator fault may lead to large impacts or perturbations in power system. The generator protection control systems in Korea have been imported and operated through a turn-key from overseas entirely. Therefore a study of the generator protection field has in urgent need for a stable operation of the imported goods. In present, the algorithm using the current ratio differential relaying based DFT for stator winding protection or a fault detection had been applied that of internal fault protection of a generator. the DFT used for the analysis of transient state signal conventionally had defects losing a time information in the course of transforming a target signal to frequency domain. In this paper, the discrete wavelet transform (DWT) was applied a fault detection of the generator being superior to a transient state signal analysis and being easy to real time realization. The fault signals after executing a terminal fault modeling collect using a MATLAB package, and calculate the wavelet coefficients through the process of a muiti-level decomposition (MLD). The proposed algorithm for a fault detection using the Daubechies WT (wavelet transform) was executed with a C language and the commend line function for the real time realization after analyzing MATLAB's graphical interface. The advanced technique had improved faster a speed of fault discrimination than a conventional DFR based on DFT.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.21 no.3
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• pp.75-81
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• 2007

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to Fourier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the Fast Fourier Transform(FFT).

• Proceedings of the Korean Society of Marine Engineers Conference
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• 2002.05a
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• pp.213-217
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to courier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier, and more useful method than the FFW (Fast courier Transform).ransform).

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2002.12a
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• pp.427-430
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• 2002

Recently the subject of "wavelet analysis" has be drawn by both mathematical and engineering application fields such as Signal Processing, Compression/Decomposition, Wavelet-Neural Network, Statistics and etc. Even though its similar to Fourier analysis, wavelet is a versatile tool with much mathematical content and great potential for applications. Especially, wavelet transform uses localizable various mother wavelet functions in time-frequency domain. Therefore, wavelet transform has good time-analysis ability for high frequency component, and has good frequency-analysis ability for low frequency component. Using the discriminative ability is more easy method than other conventional techniques. In this paper, Morlet wavelet transform was applied to discriminate the kind of line fault by acquired data from real power transformation network. The experimental result presented that Morlet wavelet transform is easier,and more useful method than the FFT (Fast Fourier Transform).