• Proceedings of the KIEE Conference
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• 2008.07a
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• pp.245-246
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• 2008

변전소 모선에서 측정되는 전압, 전류를 기반으로 하는 CB기반 고장거리 추정기법은 배전선의 다중 분기선 때문에 다중개의 고장위치를 추론하는 것은 물론 분기 부하모델의 불확실성으로 인해 거리 계산에 오차를 포함하게 된다. 따라서 본 연구에서는 유비쿼터스 기반의 배전계통 하에서 구간 측정 전압, 전류 및 IED간 정보교환을 통해 얻어지는 전압, 전류 정보를 이용하여 고장경로를 추정하는 IED 기반 고장경로 추정기법을 제안한다.

• Journal of the Korean Institute of Intelligent Systems
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• v.8 no.2
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• pp.9-20
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• 1998

In this paper, a new distance relaying scheme is proposed. Artificial neural networks are applied to the distance relaying system composed of pattern recognition based. The proposed distance relaying scheme has two blocks of pattern recognition stages to estimate the fundamental frequency and to classify the fault types. In the first block, a filtering method using neural networks called a neural networks mapping filter(NMF) is presented to efficiently extract the features. And in the sec'ond block, the estimator called neural networks fault pattern estimator(NFPE) is also presented to classify the fault types by the extracted effective features obtained from NMF. Each block of these applied schemes is trained by back-propagation algorithm of multilayer perceptron and show the fast and accurate pattern recognition by ability of multilayer neural networks. The test result of this approach are obtained the good performance from the fault transient wave signals of EMTP(e1ectromagnetic transients program) in the various fault conditions of power systems.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.30_31
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• 2009

송전선로에서 고장이 발생할 경우 가능한 빠르게 고장을 검출하고 고장점을 파악하여 수리하는 것은 전력 공급의 신뢰도 및 전력품질 향상에 매우 중요하다. 고장점 추정을 위한 방법은 크게 전압과 전류의 기본파를 이용한 임피던스 계산 방법과 과도신호에 기반한 진행파 해석 방법으로 분류할 수 있다. 과도신호에 기반한 진행파 해석 방법은 매우 빠른 응답을 갖는다는 장점을 갖고 있으나 진행파의 특징을 추출하여 고장거리를 계산하는데에는 어려움이 따른다. 따라서 본 논문에서는 송전선로에서 고장이 발생할 경우 나타나는 진행파의 특징을 분석하고 진행파로부터 고장점 정보를 추출하기 위한 방법을 제시하였다.

• Journal of the Korea Computer Industry Society
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• v.6 no.5
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• pp.689-696
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• 2005

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the Kappa(2) reliability model, which can capture the nomotonic decreasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on sum of the squared errors and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing two parameter of the Kappa distribution, was employed. This analysis of failure data compared with the Kappa model and the existing model using arithmetic and Laplace trend tests, bias tests is presented.

• Journal of the Korea Society of Computer and Information
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• v.11 no.1 s.39
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• pp.45-53
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the $x^2$ reliability model, which can capture the increasing nature of the failure occurrence rate per fault. Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using real data set, SYS2(Allen P.Nikora and Michael R.Lyu), for the sake of proposing shape parameter of the $x^2$ distribution using the degree of freedom, was employed. This analysis of failure data compared with the $x^2$ model and the existing model using arithmetic and Laplace trend tests, Kolmogorov test is presented.

• The Transactions of the Korean Institute of Electrical Engineers A
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• v.55 no.4
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• pp.144-150
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• 2006

IEC 61850 is the worldwide protocol for the substation automation system. IEC 61850 transports the information which consists of different formats such as GOOSE(Generic Object Oriented Substation Event), MMS(Manufacturing Message Specification), SV(Sampled Values) and so on. For real time data transmission, GOOSE can be used. The remote-bus current data which were collected in a local-bus current differential IED can be transmitted to a distance IED at the same location by using GOOSE messages. The distance IED can eliminate the reactance effect by using the transmitted remote-bus current data. This method can improve the performance of the fault location.

• Journal of the Korea Society of Computer and Information
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• v.11 no.5 s.43
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• pp.9-18
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• 2006

Finite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, Goel-Okumoto and Yamada-Ohba-Osaki model was reviewed, proposes the exponentiated exponential distribution reliability model, which maked out efficiency substituted for gamma and Weibull model(2 parameter shape illustrated by Gupta and Kundu(2001) Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE, AIC statistics and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using NTDS data set for the sake of proposing shape parameter of the exponentiated exponential distribution was employed. This analysis of failure data compared with the exponentiated exponential distribution model and the existing model (using arithmetic and Laplace trend tests, bias tests) is presented.

• The Journal of the Korea institute of electronic communication sciences
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• v.3 no.4
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• pp.276-281
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• 2008

Because the distribution systems experience frequently the fault by several causes, the identification task of fault location plays very important role in the view point of power supply reliability. The distribution systems are designed as radial structure with three-phase and single-phase branch line to supply the electric power to the widely dispersed loads, and it have a several load taps within each line segment. it makes the accurate fault distance determination difficult. Accordingly in this papers, the existing fault point determination methods are surveyed and analyzed, and then a fault distance determination method for distribution feeder is adopted which can be executed effectively in DAS center. Finally, the adopted method is verified using EMTP simulation.

• Convergence Security Journal
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• v.7 no.3
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• pp.51-60
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• 2007

Infinite failure NHPP models presented in the literature exhibit either constant, monotonic increasing or monotonic decreasing failure occurrence rates per fault. In this paper, exponential distribution and Rayleigh distribution model was reviewed, proposes the mixture reliability model, which made out efficiency substituted for situation for failure time Algorithm to estimate the parameters used to maximum likelihood estimator and bisection method, model selection based on SSE and Kolmogorov distance, for the sake of efficient model, was employed. Analysis of failure using S27 data set for the sake of proposing shape parameter of the mixture distribution was employed. This analysis of failure data compared with the mixture distribution model and the existing model(using arithmetic and Laplace trend tests, bias tests) is presented.

• Proceedings of the KIEE Conference
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• 1996.07b
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• pp.808-810
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• 1996

In this paper, neural network, which has learning capability, is used for fault type classification and fault section estimation for high speed relaying. The potential of the neural network approach is demonstrated by simulation using ATP. The instantaneous values of voltages and currents are used the inputs of neural networks. This approach determines the fault section directly. In this paper, back-propagation network(BPN) is used for fault type classification and fault section estimation and can use for high speed relaying because it determines fault section within a few msec.