• Proceedings of the KIEE Conference
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• summer
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• pp.455-457
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• 2004

An accurate digital distance relaying algorithm which is immune to reactance effect of the fault resistance and the load current for phase-to-phase short fault in 765kV untransposed transmission lines is proposed. The algorithm can estimate adaptively the impedance to a fault point independent of the fault resistance. To compensate the magnitude and phase of the apparent impedance, this algorithm uses the angle of an impedance deviation vector. The impedance correction algorithm for phase-to-phase short fault uses a voltage equation at fault point to compensate the fault current at fault point. A series of tests using EMTP output data in a 765kv untransposed transmission lines have proved the accuracy and effectiveness of the proposed algorithm.

• Journal of Electrical Engineering and Technology
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• v.6 no.6
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• pp.742-749
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• 2011

Power transmission lines are one of the most important components of electric power system. Failures in the operation of power transmission lines can result in serious power system problems. Hence, fault diagnosis (transient or permanent) in power transmission lines is very important to ensure the reliable operation of the power system. A hidden Markov model (HMM), a powerful pattern recognizer, classifies events in a probabilistic manner based on fault signal waveform and characteristics. This paper presents application of HMM to classify faults in overhead power transmission lines. The algorithm uses voltage samples of one-fourth cycle from the inception of the fault. The simulation performed in EMTPWorks and MATLAB environments validates the fast response of the classifier, which provides fast and accurate protection scheme for power transmission lines.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.49 no.8
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• pp.405-411
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• 2000

When faults occur in transmission lines, the classification of faults is very important. If the fault is HIF(High Impedance Fault), it cannot be detected or removed by conventional overcurrent relays (OCRs), and results in fire hazards and causes damages in electrical equipment or personal threat. The fast discrimination of fault needs to effective protection and treatment and is important problem for power system protection. This paper propolsed the fault detection and discrimination algorithm for LIFs(Low Impedance Faults) and HIFs(High Impedance Faults). This algorithm uses artificial neural networks and variation of 3-phase maximum currents per period while faults. A double lines-to-ground and line-to-line faults can be detected using Neural Network. Also, the other faults can be detected using the value of variation of maximum current. Test results show that the proposed algorithms discriminate LIFs and HIFs accurately within a half cycle.

• Proceedings of the KIEE Conference
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• 1999.07c
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• pp.1440-1443
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• 1999

This paper proposes fault detection method using a neural network & fuzzy logic on distribution lines. Fault on distribution lines is simulated using EMTP. The pattern of high impedance fault on pebbles, ground and short-circuit fault were take as the learning model. In this paper proposed fault detection method is evaluated on various conditions. The average values after analyzing fault current by FFT of even odd harmonics and fundamental rms were used for the neural network input. Test results were verified the validity of the proposed method

• Proceedings of the KIEE Conference
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• 1998.07c
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• pp.1114-1117
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• 1998

Recent applications of neural networks to power system fault diagnosis have provided positive results and have shown advantages in process speed over conventional approaches. This paper describes the application of neural network to fault detection and classification in distribution lines using the fundamental component, 2-5th harmonics index, even and odd harmonics index, and zero phase current. The Electromagnetic Transients Program (EMTP) is used to obtain fault patterns for the training and testing of neural networks. The proposed fault detection and classification method in distribution lines is obtained by analysing the difference among normal, HIF, ground fault, short circuit fault condition.

• Progress in Superconductivity
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• v.5 no.2
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• pp.118-123
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• 2004

We investigated quench distribution in AU/YBCO thin film meander lines with a heater. Quench distribution during faults is important for superconducting fault current limter applications, because uniform quench allows application of higher voltages across the meander lines. AU/YBCO thin films grown on sapphire substrates were patterned into meander lines by photolithography. Gold films grown on the rear sides of the substrates were also patterned into meander lines, and used as heaters. Meander lines on the front and the rear sides were connected in parallel. The meander lines were subjected to simulated AC fault currents for quench measurements during faults. They were immersed in liquid nitrogen during the experiment for effective cooling. Resistance of the AU/YBCO meander lines initially increased more rapidly with the rear heater than without, and consequently the fault current was limited more. The resistance subsequently became similar, The resistance distribution was more uniform with the heater, especially during the initial quench. Quench was completed more uniformly and significantly earlier. This resulted in uniform distribution of dissipated power. These results could be explained with the concept of quench propagation, which was accelerated by heat transfer across the substrate from the rear heater.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.3
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• pp.116-122
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• 2006

The underground transmission lines is continuously expanded in power systems. Therefore the fault of underground transmission lines are increased every year because of the complication of systems. However the studies dealing with fault location in the case of the underground transmission lines are rarely reported except for few papers using traveling wave method and calculating underground cable impedance. This paper describes the algorithm using fuzzy system and travelling wave method in the underground transmission line. Fuzzy inference is used for fault discrimination. To organize fuzzy algorithm, it is important to select target data reflecting various underground transmission line transient states. These data are made of voltage and average of RMS value on zero sequence current within one cycle after fault occurrence. Travelling wave based on wavelet transform is used for fault location. In this paper, a variety of underground transmission line transient states are simulated by EMTP/ATPDraw and Matlab. The input which is used to fault location algorithm are Detail 1(D1) coefficients of differential current. D1 coefficients are obtained by wavelet transform. As a result of applying the fuzzy inference and travelling wave based on wavelet transform, fault discrimination is correctly distinguished within 1/2 cycle after fault occurrence and fault location is comparatively correct.

• Proceedings of the KIEE Conference
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• 2003.11a
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• pp.412-415
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• 2003

It is important to classily fault types, discriminate fault section and calculate the fault location by any detecting technique for combined transmission lines. This paper proposes the technique to classily the fault types and fault section using neuro-fuzzy systems. Neuro-fuzzy systems are composed of three parts to perform different works. First, neuro-fuzzy system for fault type classification is performed with approximation coefficient of currents obtained by wavelet transform. The second neuro-fuzzy system discriminates the fault section between overhead and underground with detail coefficients of voltage and current. The last neuro-fuzzy system calculates the fault location with impedance in this paper, neuro-furry system shows the excellent results for classification of fault types and discrimination of fault section.

• Journal of the Korean Institute of Illuminating and Electrical Installation Engineers
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• v.26 no.2
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• pp.51-60
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• 2012

An improved method for detecting fault distance in overhead transmission lines is described in this paper. Based on single-ended measurement, propagation theory of traveling waves together with the wavelet transform technique is used. In estimating fault location, a simple, but fundamental method using the time difference between the two consecutive peaks of transient signals is considered; however, a new method to enhance measurement sensitivity and its accuracy is sought. The algorithm is developed based on the lattice diagram for traveling waves. Representing both the ground mode and alpha mode of traveling waves, in a lattice diagram, several relationships to enhance recognition rate or estimation accuracy for fault location can be found. For various cases with fault types, fault locations, and fault inception angles, fault resistances are examined using the proposed algorithm on a typical transmission line configuration. As a result, it is shown that the proposed system can be used effectively to detect fault distance.

• Proceedings of the KIEE Conference
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• 2005.07a
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• pp.178-180
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• 2005

Recently, electrical demands increase rapidly in metropolitan areas according to the extension of urban areas. Therefore underground transmission lines are getting expanded. This paper presents the rapid and accurate algorithm for fault discrimination and fault location in underground transmission lines. This paper uses fuzzy logic method using voltage and zero sequence for fault discrimination. And this paper uses travelling wave and wavelet transform for fault location. To prove the performance of the algorithm, it test algorithm with signal obtained from ATPDraw simulation.