• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.33 no.1
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• pp.65-69
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• 2020

The aim of this study is to improve the fault decision ability of FRTU (Feeder remote terminal unit) in DAS (Distribution automation system). FRTU uses the FI (Fault indicator) algorithm based on fault current pickup and operation of the protection device. Even if the inrush current flows or the protection device is sensitive to the transient current, FRTU may indicate incorrect fault information. To address these problems, we propose an improved fault recognition algorithm that can be applied to FRTU. We will detect a specific wave that is indicative of a fault, and use this information to identify a fault wave. The specific wave-detection algorithm is based on the duration and periodicity of the voltage, current, and harmonic variations. In addition, we propose fault recognition algorithms using voltage factor variation analysis and DWT (Discrete wavelet transform). All the wave data used in this study were actual data stored in FRTU.

• The Journal of the Korea institute of electronic communication sciences
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• v.17 no.6
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• pp.1113-1120
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• 2022

In this paper, a communication methodology for the digital FRTU(: Feeder Remote Terminal Unit) required by the smart grid distribution system was studied. The digital FRTU consists of a fault handling unit and a communication unit. The fault handling unit transmits fault information to the communication unit in case of a failure, and the communication unit is designed to autonomously determine the fault section through two-way communication between surrounding digital FRTUs. For performance verification, a performance verification system consisting of 3 line sections based on 3 digital FRTUs was constructed to enable fault simulation for various failure scenarios. Various fault cases including one phase ground fault, line-to-line short-circuit fault, and three-phase short-circuit fault were experimentally simulated on the established performance verification system, and the validity of the developed methodology was confirmed by proving the accurate fault section inference results for each fault simulation case.

• Journal of Electrical Engineering and Technology
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• v.3 no.2
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• pp.192-198
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• 2008

This paper proposes a FRTU-based intelligent fault distance determination strategy in which each FRTU is able to avoid multiple estimations and reduce the level of estimation error by utilizing heuristic rules driven by voltage and current information collected by 1:1 communication with other FRTUs from the same zone in a ubiquitous-based distribution system. In the proposed method, each FRTU, at first, determines a fault zone and a fault path on the faulted zone based on the proposed heuristic rules which use its current data and the voltage data of its neighboring FRTUs as input data. Next, it determines the fault distance from its position based on the fault current estimated from the current data of the neighboring FRTUs. Finally, in order to prove the effectiveness of the proposed method, the diverse fault cases are simulated in several positions of the typical distribution system using the EMTP.

• The Transactions of The Korean Institute of Electrical Engineers
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• v.56 no.7
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• pp.1183-1190
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• 2007

This paper proposes the improved fault decision algorithm using DWT(Discrete Wavelet Transform) and ANNs for the FRTU(Feeder Remote Terminal Unit) on the feeder in the power distribution system. Generally, the FRTU has the fault decision scheme detecting the phase fault, the ground fault. Especially FRTU has the function for 2000ms. This function doesn't operate FI(Fault Indicator) for the Inrush current generated in switching time. But it has a defect making it impossible for the FI to be operated from the real fault current in inrush restraint time. In such a case, we can not find the fault zone from FI information. Accordingly, the improved fault recognition algorithm is needed to solve this problem. The DWT analysis gives the frequency and time-scale information. The neural network system as a fault recognition was trained to distinguish the inrush current from the fault status by a gradient descent method. In this paper, fault recognition algorithm is improved by using voltage monitoring system, DWT and neural network. All of the data were measured in actual 22.9kV power distribution system.

• Journal of the Korean Institute of Intelligent Systems
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• v.17 no.3
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• pp.374-379
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• 2007

This paper focuses on the improvement of fault detection algorithm in FRTU(feeder remote terminal unit) on the feeder of distribution power system. FRTU is applied to fault detection schemes for phase fault and ground fault. Especially, cold load pickup and inrush restraint functions distinguish the fault current from the normal load current. FRTU shows FI(Fault Indicator) when the fault current is over pickup value or inrush current. STFT(Short Time Fourier Transform) analysis provides the frequency and time Information. FCM(Fuzzy C-Mean clustering) algorithm extracts characteristics of harmonics. The neural network system as a fault detector was trained to distinguish the inruih current from the fault status by a gradient descent method. In this paper, fault detection is improved by using FCM and neural network. The result data were measured in actual 22.9kV distribution power system.

• Proceedings of the KIEE Conference
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• 2007.04c
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• pp.46-48
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• 2007

This paper presents research about improvement of fault detection algorithm in FRTU on the feeder of distribution system. FRTU(Feeder Remote Terminal Unit) is applied to fault detection schemes for phase fault, ground fault, and cold load pickup and Inrush restraint functions distinguish the fault current and the normal load current. FRTU is occurred FI(Fault Indicator) when current is over pick-up value also inrush current is occurred FRTU indicate FI. Discrete wavelet transform(DWT) analysis gives the frequency and time-scale information. The neural network system as a fault detector was trained to discriminate inrush current from the fault status by a gradient descent method. In this paper, fault detection is improved using voltage monitoring system with DWT and neural network. These data were measured in actual 22.9kV distribution system.

• Proceedings of the KIEE Conference
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• 2006.11a
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• pp.369-371
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• 2006

본 논문은 계통 모의시험프로그램을 이용하여 배전계농에서 나타나는 지락 및 단락고장에 대하여 모의시험을 수행하였다. 고장모의시험에서 배전자동화용 개폐기의 고장인지(Fault Indicator)의 동작에 영향을 미치는 고장전류의 변화를 살펴보았다. 그리고, 이러한 고장전류를 감지하여 FI를 배전자동화 시스템 주장치로 보내어주는 FRTU의 정상동작 시험을 위하여 실시간 계통 시뮬레이터를 이용하여 FRTU의 시험방법을 제안하였다.

• Proceedings of the KIEE Conference
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• 2007.07a
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• pp.497-498
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• 2007

When we implement the substation automation, the largest problem is that IEDs may come from different vendors, which will result in the reduction of the reliability of communication between IEDs. To solve the problem IEC61850 is investigated, which uniforms the communication interface. However, in order to communicate with an IEC61850 implanted IED, FRTU (Feeder Remote Terminal Unit) need to be compatible with IEC6185 consequentially. A new IEC61850 based FRTU development scheme is proposed. The performance shows his compatibility with other IEC61850 IED, which has already been tested in ARET (Agent-based Reliability Enhancement Technology) system.

• Proceedings of the KIEE Conference
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• 2009.07a
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• pp.1_3
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• 2009

국내 내륙 전체 배전계통은 "22.9kV-Y 중성선 다중접지방식"으로 일원화하여 운영 중에 있으나 도서 섬지역은 자체 내연력 발전 설비를 갖추고 380V-Y로 발전하여 $6.6kV-{\Delta}$로 승압 후 전력을 공급하고 있다. 현재 한전은 설비용량 200kW이상 38개 도서에서 비접지 계통으로 운영 중에 있다. KEPCO와 KDN은 비접지계통($6.6kV-{\Delta}$)으로 운영중인 도서 중 전북지사 부안지점 관내 위도에 시범운영을 통해서 실선로에서 비접지 1선 지락 고장 검출여부 검증을 시행하였다. 시범운영에는 배전자동화 시스템 주장치 1식, mFRTU 12대를 개폐기와 같이 설치하였는데, mFRTU에는 독창적이고 상용화 가능한 "비접지 지락고장검출 알고리즘" 개발하여 탑재하였으며 1선 지락고장을 발생시켜 mFRTU가 고장선로와 고장지점을 정확하게 검출하는지 여부를 검증하였다. 이번에 비접지계통 실선로에서 지락고장을 완벽하게 검출한 가장 큰 의의는 국내 및 해외 최초로 비접지 지락고장검출을 성공하였다는 것입니다. 본 논문에서는 비접지로 운영중인 도서지역에 배전자동화시스템 기반으로 지락고장검출하는 기능을 상용화하여 운영중인 시스템에 대한 내용이다. 이번에 구축한 배전자동화시스템은 비접지계통에 알맞도록 개발된 자동화용 개폐기와mFRTU에 지락고장검출 알고리즘을 기능 구현하였다. 선로에 1선지락 고장발생시 mFRTU가 고장선로, 고장구간 및 고장상 등을 판단하고 상위 주장치에 전송한다. 주장치는 고장정보를 HMI 단선도에 고장지점을 표시하여 종합적으로 감시제어 할 수 있는 시스템이다.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.32 no.2
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• pp.151-156
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• 2019

The aim of this investigation is to detect specific waveforms in a distribution line prior to the occurrence of a fault. Conditions were introduced such that a feeder remote terminal unit (FRTU) of the distribution automation system selects and stores fault waveforms from the different waveforms detected in the distribution line. In addition, an algorithm was developed to detect specific waveforms from the fault waveforms stored using the FRTU. This algorithm exploits the duration and periodicity of harmonic changes in voltage and current. The efficacy of the algorithm was confirmed based on the measurements of fault waveforms in an actual distribution line. The results indicated that faults in a distribution line can be predicted via experimental measurements.