DEVELOPMENT OF PREDICTIVE FAULT DETECTION AND CAUSE ESTIMATION WITH SENSOR-EQUIPPED SECTIONALIZERS IN ADVANCED DISTRIBUTION AUTOMATION SYSTEM

In recent years, with the progress of smart grid technologies, it is possible to detect system abnormalities (predictive signs of fault) and to estimate the causes before an outage occurs by using waveforms in the power distribution system. Therefore, various efforts using diagnosis techniques have been made to efficiently improve the reliability of the grid. With these efforts, various effects such as improvement on asset management of aged equipment, minimizing outage impact, and avoiding fire risks due to ground faults, are highly expected. In the verification at test field, we confirmed the effectiveness of our approach which detects the predictive signs of fault and estimates the cause by analyzing the captured waveform at the sensor-equipped sectionalizers. The method and verification results are described in this paper.