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이산 웨이블릿 변환과 신경회로망을 이용한 FRTU의 고장판단 능력 개선에 관한 연구
洪大昇(Dae-Seung Hong),高鈗錫(Yoon-Seok Ko),姜泰求(Tae-Ku Kang),朴學烈(Hak-Yeol Park),任化永(Hwa-Young Yim) 대한전기학회 2007 전기학회논문지 Vol.56 No.7
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 2000㎳. 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 new-a! 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 22.9㎸ power distribution system.