• 대한전기학회:학술대회논문집
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• 대한전기학회 1990년도 하계학술대회 논문집
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• pp.106-112
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• 1990

본 논문은 디지탈 거리 계전 방식의 구현을 위해 최적 FIR 필터를 사용하는 알고리즘을 제시한다. 이 알고리즘은 고장 발생시 과도 현상에 의한 임피이던스 궤적의 영향 면에서 볼 때, 기존의 디지탈 거리계전 알고리즘이나 Kalman 필터를 이용한 거리계전 알고리즘 보다 훨씬 유리하여 고장 발생 시 빠르고 정확한 고장 판단과 고장점의 산출을 제공한다. 이러한 알고리즘은 EMTP를 통해 생성된 고장 데이타의 실시간 적용을 통해 입증되었고, 이의 실시간 구현은 모토롤라 DSP (Digital Signal Processor) 56001을 연산 전용의 프로세서로 사용한 디지탈 보호계전 시스템을 통하여 성공적으로 수행되었다.

• 대한전기학회논문지
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• 제41권3호
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• pp.219-226
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• 1992

In this study, Kalman filtering theory is applied to the estimation of symmetrical components from fault voltage and current signal when it comes to faults with the power system. An algorithm for estimating fault location accurately and quickly by calculating the symmetrical components from the extracted fundamental voltage phasor and current phasor is presented. Also, to confirm the validity of digital distance relaying techniques using Kalman filtering, the experimental results obtained by using the digital simulation of power system is shown.

• 대한전기학회논문지
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• 제43권4호
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• pp.553-563
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• 1994

This paper presents a filtering method using neural networks to extract fundamental frequency components of the transient wave signals in power systems. Based on the ability of multilayer feedforward neural networks to approximate any continuous function, a neural networks mapping filter is proposed for the protective distance relaying systems to extract the effective components efficiently. A characteristic feature of this mapping filter is composed of the multilayer perceptron neural networks which are trained by using random signals and those are mapped to the DFT filtering computational structure by GDR(Generalized Delta Rule). The advantage of this approach is demonstrated by the random waves and the fault transient wave signals of EMTP(electromagnetic transients program) in power systems fault conditions. The proposed method is compared with the conventional method and the simulation results show the efficiency of the neural networks.