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채종병,변성현,김철환 成均館大學校 科學技術硏究所 1997 論文集 Vol.48 No.1
High Impedance Faults (HIF) present a source of threat to utilities customers and personnel. Arcing faults result in waste of energy and can damage property. Protection against these faults comes mainly from a moral point of view, i.e. improving safety to persons. High Impedance Faults are difficult to detect, when the impedance at the point of fault is high enough to limit the fault current to the unprotected region of conventional overcurrent devices. Numerous detection methods have been suggested for such fault detection. However, each detection method cannot detect all electrical conditions resulting from down conductor fault. Until now, the arc models used for modeling high impedance fault were proposed. But, these are not suitable for implementing in EMTP. This paper proposes a technique for modeling the high impedance fault in transmission line using the ZnO arrester which can be implemented within EMTP. The performance of the proposed model is tested under a variety of fault conditions on a typical 345[kV] korean transmission line system.
Chae, Jong-Byeong,Lim, Byung-Ho,Ahn, Sang-Pil,Kim, Chul-Hwan 成均館大學校 科學技術硏究所 1998 論文集 Vol.49 No.1
This paper presents a distance relay algorithm which uses wavelet transforms and shows that they may be useful for the power system relaying. Using wavelet transform, fundamental frequency component is extracted and used as input of distance relaying algorithm. Also. for simplicity of simulation processing, a simulation language, called MODELS, is used. It has been added to the EMTP (ElectroMagnetic Transient Program), which per nits to interface control system with power system. One purpose of this study is to build a wavelet transform based digital distance reliving algorithm within EMTP MODELS. Compared to DFT (Discrete Fourier Transform) algorithm, performance of the algorithm presented in this paper is evaluated.
신경회로망을 이용한 LIF 및 HIF 검출에 관한 연구
최해술,박성원,채종병,김철환 성균관대학교 1997 학술회의지원논문목록집 Vol.1997 No.-
A high impedance fault(HIF) in a power system could be due to a downed and is a dangerous situation becausc the current may be too small to be detected by conventional means. In this paper HIF(High impedance fault) and LIF)Low impedance fault) detection methods were reviewed. No single detection method can detect all electrical conditions resulting from downed conductor faults because high impedance fault have arc phenomena asymmetry and randomness. Neural network are well-suited for solving difficult signal processing and pattern recognition problem. This paper present the application of artificial neural network (ANN) to detect the HIF anf LIF. Test results show thar the neural network was able to identify the high impedance fault by real-time operation. Furthermore, neural network was able to discriminate the HIF from the LIF.