4.7 Article

Application of Waveform Analytics for Improved Situational Awareness of Electric Distribution Feeders

Journal

IEEE TRANSACTIONS ON SMART GRID
Volume 6, Issue 4, Pages 2041-2049

Publisher

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC
DOI: 10.1109/TSG.2015.2406757

Keywords

Condition-based maintenance; fault anticipation; incipient fault detection; situational awareness; waveform analytics

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Over the past several years, distribution utilities have invested heavily in installations of smart-meter advanced metering initiative (AMI) systems. Among the anticipated benefits of these systems, utilities with smart-meter deployments are generally able to quickly assess which portions of their systems are operating normally and which customers are experiencing an outage. Projects at multiple utilities have focused on integrating AMI information, along with traditional supervisory control and data acquisition data sources, into utility distribution management systems to improve situational awareness on distribution feeders. Despite the clear benefits each of these systems offer, their ability to provide utilities with broad awareness of events affecting the health and status of the distribution system is limited, and often reactive in nature. This paper presents never-before-published cases observed in real-world field trials, detailing how integration of waveform analytics into utility operational practice leads to improved situational awareness.

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