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 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.