• KIEE International Transactions on Power Engineering
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• v.3A no.4
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• pp.191-197
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• 2003

Accurate detection and classification of faults on transmission lines is vitally important. In this respect, many different types of faults occur, such as inter alia low impedance faults (LIF) and high impedance faults (HIF). The latter in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if undetected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. Because of the randomness and asymmetric characteristics of HIFs, their modeling is difficult and numerous papers relating to various HIF models have been published. In this paper, the model of HIFs in transmission lines is accomplished using the characteristics of a ZnO arrester, which is then implemented within the overall transmission system model based on the electromagnetic transients program (EMTP). This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs 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 algorithm is tested on a typical 154 kV Korean transmission line system under various fault conditions. Test results demonstrate that the ANFIS can detect and classify faults including LIFs and HIFs accurately within half a cycle.

• Proceedings of the KIEE Conference
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• 2002.11b
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• pp.319-322
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• 2002

Distance relay is operated in calculating line impedance. It can be worked accurately in overhead line. However, power cables or combined transmission lines need compensation for calculated impedance because cable systems have sheaths, grounding wires and sheath voltage limiters(SVLs) Neuro-fuzzy can be viewed either as a fuzay system, a neural network or fuzzy neural network and it can estimate the location of the fault accurately. In this paper, fault section and fault location can be classified and estimated in neuro- fuzzy inference system and neural network.

• Proceedings of the KIEE Conference
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• 2003.07a
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• pp.534-536
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• 2003

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

• 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.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.377-379
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• 2001

When a wide area blackout occurres, reenergizing transmission lines should be done at first. The KEPCO(Korea Electric Power Corporation) divides whole power system grid into seven subsystem, and each subsystem has one of two blackstart power plants which are usually hydro or combined-combustion type, one priority power plant which should be first supplied with electric energy, and transmission lines between them. Voltage rising, line charging, and operation stability problem should be considered when these lines are reenergized. In this paper, building-up process for primary transmission system that should be energized at first is analyzed.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.59 no.11
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• pp.1949-1955
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• 2010

This paper describes the characteristic and effectiveness of combined GIL transmission line through lightning surge analysis. In addition the XLPE cable is analyzed in the same condition to compare with GIL. Lighting surge analysis is carried out by EMTP/ATP-Draw to obtain overvoltage of GIL and XLPE cable at service-point and load-out area of underground line. Propagation velocity is calculated in combined transmission lines with GIL and XLPE cable. The overvoltage is also analyzed on GIL and XLPE cable with or without arrester operation. The Analysis results show that overvoltage of GIL is occurred higher than XLPE cable at the same condition. Therefore it is evaluated that the application of GIL at the field should be considered cautiously when more detailed transient analysis, another electrical testes and economic evaluations are implemented.

• The Journal of Korean Institute of Electromagnetic Engineering and Science
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• v.19 no.10
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• pp.1122-1128
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• 2008

A novel tunable bandstop filter was proposed. It is composed of a right-handed transmission line, which has lowpass characteristics, and a left-handed transmission line which has highpass characteristics. Dispersion relations for the unit cells of RHTL and LHTL were derived by the method of ABCD parameter analysis. Varactor diodes and chip inductors were used to make the unit cells of RHTL and LHTL. A tunable bandstop filter was designed and fabricated by the parallel connection of RHTL and LHTL. The measured results of the proposed tunable bandstop filter are agreed well with the simulated results.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.371_372
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• 2009

This paper describes surge characteristics on 345kV combined transmission system mixed overhead line and GIL(Gas Insulated Transmission Line). Then, it is compared with the results of the system mixed overhead line and XLPE power cables. Finally the lightning overvoltages are also discussed according to surge arrester installation in two kinds of combined transmission systems when the lighting strikes on the phase conductor.

• Proceedings of the KIEE Conference
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• 2001.07a
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• pp.252-254
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• 2001

Accurate detection and classification of faults on transmission lines is vitally important. High impedance faults(HIF) in particular pose difficulties for the commonly employed conventional overcurrent and distance relays, and if not detected, can cause damage to expensive equipment, threaten life and cause fire hazards. Although HIFs are far less common than LIFs, it is imperative that any protection device should be able to satisfactorily deal with both HIFs and LIFs. This paper proposes an algorithm for fault detection and classification for both LIFs and HIFs using Adaptive Network-based Fuzzy Inference System(ANFIS). The performance of the proposed algorithm is tested on a typical 154[kV] Korean transmission line system under various fault conditions. Test results show that the ANFIS can detect and classify faults including (LIFs and HIFs) accurately within half a cycle.

• 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.