• The Transactions of The Korean Institute of Electrical Engineers
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• v.62 no.2
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• pp.155-163
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• 2013

As the increasing HIF(High Impedance Fault) with the arc cannot be easily detected for the low fault current magnitude compared to actual load in distribution line. However, the arcing current shows that the magnitude varies with time and the signal is asymmetric. In addition, discontinuous changes occur at starting point of arc. Considering these characteristics, wavelet transformation of actual current data shows difference between before and after the fault. Althogh raw data(detail coefficient) of wavelet transform may not be directly applied to HIF detection logic in a device, there are several developing methods of HIF monitoring data using the original wavelet coefficients. In this paper, a simple and effective developing methods of HIF monitoring data were analized by using the signal data through an actual HIF experiment to apply them to economic devices. The methods using the sumation of the wavelet coefficient squares in one cycle of the fundamental frequency as the energies of the wavelet coefficeits and the sumation of the absolute values were compared. Besides, the improved method which less occupies H/W resouces and can be applied to field detection devices was proposed. and also Verification of this HIF detection method through field test on distribution system in KEPCO power testing center was performed.

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1182-1184
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• 1998

Recently high impedance fault(HIF), which includes arcing wave, has often occured in power system. Some papers related to arcing phenomena and its modeling have been published. However the proposed methods show much different form in compare with actual arc wave under HIF. It is not so available to use to analyze HIF because of such problem. This paper proposes the new arcing wave model, which is nearly similar to actual arcing wave, developed using PSCAD/EMTDC. The arcing waves obtained from arcing model that applied in actual. power system are compared with some actual arcing wave gained from the field test and show the availability to application of relay test.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.850-852
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• 1996

High impedance fault (HIF) is defined as fault that general overcurrent relay can't detect or interrupt, Especially when HIF occur under 15 kV, energized high voltage conductor results in fire hazard, equipment damage or personal threat. Because most HIF occur arc, HIF detection using arc is to increase. Numerical arc model can be applied in an electromagnetic transients program (EMTP) to reproduce the dynamic and random characteristic of arcs for any insulator arrangement, current and system voltage. It allows the representation of any network configuration to be investigated, so the digital simulation of arc faults through air can be substitute for demanding power arc test.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.9
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• pp.417-423
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• 2001

This paper proposes a technique for fault detection and classification for both LIF(Low Impedance Fault)s and HIF(High Impedance Fault)s using Adaptive Network-based Fuzzy Inference System(ANFIS). The inputs into ANFIS are current signals only based on Root-Mean-Square(RMS) values of 3-phase currents and zero sequence current. The performance of the proposed technique is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classily faults including (LIFs and HIFs) accurately within half a cycle.

• Proceedings of the KIEE Conference
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• 2000.07d
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• pp.2525-2527
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating, so it is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion. Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• Proceedings of the Korean Institute of Information and Commucation Sciences Conference
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• 2000.10a
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• pp.459-462
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• 2000

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device operating. so it is well hon that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional protection system. In this paper, we prove that the nature of the high impedance faults is indeed a deterministic chaos, not a random motion Algorithms for estimating Lyapunov spectrum and the largest Lyapunov exponent are applied to various fault currents detections in order to evaluate the orbital instability peculiar to deterministic chaos dynamically, and fractal dimensions of fault currents which represent geometrical self-similarity are calculated. Wavelet transform analysis is applied the time-scale information to fault signal. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• The Journal of the Korea institute of electronic communication sciences
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• v.18 no.5
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• pp.817-826
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• 2023

In this paper, a fault determination methodology based on an artificial neural network was proposed to protect the system from faults on the lines in the smart grid distribution system. In the proposed methodology, first, it was designed to determine whether there is a low impedance line fault (LIF) based on the magnitude of the current RMS value, and if it is determined to be a normal current, it was designed to determine whether a high impedance ground fault (HIF) is present using Normal/HIF classifier based on artificial neural network. Among repetitive DSP module-based algorithm verification tests, the normal/HIF classifier recognized the current waveform as normal and did not show reclosing operation for the cases of normal state current waveform simulation test where the RMS value was smaller than the minimum operating current value. On the other hand, for the cases of LIF where RMS value is greater than the minimum operating current value, the validity of the proposed methodology could be confirmed by immediately recognizing it as a fault state and showing reclosing operation according to the prescribed procedure.

• Proceedings of the KIEE Conference
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• 1999.07b
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• pp.856-858
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• 1999

The analysis of distribution line faults is essential to the proper protection of power system. A high impedance fault(HIF) dose not make enough current to cause conventional protective device. It is well known that undesirable operating conditions and certain types of faults on electric distribution feeders cannot be detected by using conventional Protection system. This paper describes an algorithm using neural network for pattern recognition and detection of high impedance faults. Wavelet transform analysis gives the time-scale information. Time-scale representation of high impedance faults can detect easily and localize correctly the fault waveform.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.975-978
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• 1997

This Paper presents a high impedance fault (HIF) detection algorithm of distribution systems using wavelet transform. Two HIFs on dry soil and sandy soil were simulated on various load conditions in 22.9 kV distribution systems using EMTP, and the current wavelets were decomposed by wavelet transform. The current root mean square(rms) change, the index change rate and the relative amplitude change were used as the multi-criteria for a HIF detection. The index change rate and the relative amplitude were made using the wavelet coefficients.

• Proceedings of the KIEE Conference
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• 2000.07a
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• pp.446-448
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• 2000

This paper discribes the modeling and transient analysis of cable in combined transmission line under high impedance fault(HIF). And also, transient characterstic analyzed on cable covering protection unit(CCPU) is presented. Modeling of the combined transmission line is established in PSCAD/EMTDC V3. The required data to analyze the transient phenomena is given from the actual system. The results show the HIF modeling in cable, fault current according to the value of fault resistance. And also when the value and method of grounding resistance is changed in CCPU, simulation results are presented.