• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1373-1375
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• 1999

High impedance fault (HIF) is defined as fault the general overcurrent relay can not detect or interrupt. Especially when HIF occur in residential areas, energized high voltage conductor results in fire hazard, equiment damage or personal threat. This paper proposes the model of HIF in transmission line using the ZnO arrester and resistance to be implemented within EMTP. Wavelet transform is efficient and useful for the detection of HIF in power system, because it uses variable windows according to frequency. HIF detection method using wavelet transform can distinguish HIF from similar phenomena like arcfurance load, capacitor bank switching and line switching.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.243-245
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• 2001

This paper presents a new classification method for high impedance faults in power systems. Results of phase plane trajectory with Clarke modal transformation using postfault current and voltage are utilized to classify types of arcing faults. The performance of the proposed method is tested on a typical 154 kV korean transmission system under various fault conditions using EMTP. As can be seen from results, phase plane trajectory of postfault current should be combined with that of o component from Clarke modal transformation to give reliability of clear fault classification. Thus the proposed method can classify arcing faults including LIFs and HIFs accurately in power systems.

• 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 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.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.50 no.3
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• pp.105-111
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• 2001

The research presented in this paper focuses on a method for the detection of High Impedance Fault(HIF). The method will use the wavelet transform and neural network system. HIF on the multi-grounded three-phase four-wires primary distribution power system cannot be detected effectively by existing over current sensing devices. These paper describes the application of discrete wavelet transform to the various HIF data. These data were measured in actual 22-9kV distribution system. Wavelet transform analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate HIF from the normal status by a gradient descent method. The proposed method performed very well by proving the right state when it was applied staged fault data and normal load mimics HIF, such as arc-welder.

• Proceedings of the KIEE Conference
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• 1993.07a
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• pp.156-158
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• 1993

This paper presents several techniques of power spectrum estimation for high impedance fault detection. High impedance faults are those faults with current too low to be reliably cleared by conventional overcurrent protection. So power spectrum estimation is required. AR and MA techniques require optimal order for good performance of power spectrum estimation because these techniques are unstable for order selection. ARMA and Extended techniches are stable for order selection and have very sharp response. So ARMA and Extended Prony techniques are suitable for our purpose.

• Proceedings of the KIEE Conference
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• 1997.07b
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• pp.542-544
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• 1997

The analysis of distribution line faults is essential to the proper protections in the power system. A high impedance fault does not make enough current to cause conventional protective devices. In this paper, Fractal dimensions are estimated for distinction between normal status and fault status in the power system. Application of the concepts of the fractal geometry to analyze chaotic properties of high impedance fault current was described. In addition, to analyze variation of fault current and normal current on phase plane, embedding state variables are reconstructed from 1 dimensional time series.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.1015-1017
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• 1997

A high impedance fault on the multi-grounded three-phase four-wire distribution system can not be detected by conventional overcurrent sensing devices. In this paper, the neural network is used to detect high impedance faults. The proposed algorithm using back - propagation neural network is demonstrated by simulation with the staged fault test data. The harmonic components of current and the phase of voltage are used as the inputs of neural network. Results of the simulation can be used as a reference for the development of a high impedance fault detector.

• Proceedings of the KIEE Conference
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• 1997.07c
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• pp.897-899
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• 1997

The analysis of distribution line faults is essential to the proper protections of the power system. A high impedance fault does not make enough current to cause conventional protective devices. 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 back-propagation neural network for pattern recognition and detection of high impedance faults. Fractal dimensions are estimated for distinction between random noise and chaotic behavior in the power system. The fractal dimension of the line current is also used as a indication of the high impedance fault.

• Proceedings of the KIEE Conference
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• 1996.11a
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• pp.103-105
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• 1996

This paper describes real time dynamic tests on the digital distance relay using new digital test system including RTDS(Real Time Digital Simulator) in KEPRI. The RTDS is developed by the Manitoba HVDC Research Centre and consists of specialized hardware and software which allows transients simulation of electrical power systems in real time. From high impedance fault test, it is known that the characteristics of distance reach is influenced by load flow. A detailed discussion of relay test using the RTDS simulator, high impedance faults and test results are included in the paper.