DocumentCode
44618
Title
Application of Waveform Analytics for Improved Situational Awareness of Electric Distribution Feeders
Author
Wischkaemper, Jeffrey A. ; Benner, Carl L. ; Russell, B. Don ; Manivannan, Karthick
Author_Institution
Dept. of Electr. & Comput. Eng., Texas A&M Univ., College Station, TX, USA
Volume
6
Issue
4
fYear
2015
fDate
Jul-15
Firstpage
2041
Lastpage
2049
Abstract
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.
Keywords
SCADA systems; fault diagnosis; maintenance engineering; power distribution control; power distribution faults; smart meters; waveform analysis; AMI information integration; condition-based maintenance; distribution system status; distribution utilities; electric distribution feeders; fault anticipation; incipient fault detection; situational awareness improvement; smart-meter advanced metering initiative systems; smart-meter deployments; supervisory control-and-data acquisition data sources; utility distribution management systems; waveform analytics; Capacitors; Maintenance engineering; Monitoring; Substations; Switches; Transient analysis; Condition-based maintenance; fault anticipation; incipient fault detection; situational awareness; waveform analytics;
fLanguage
English
Journal_Title
Smart Grid, IEEE Transactions on
Publisher
ieee
ISSN
1949-3053
Type
jour
DOI
10.1109/TSG.2015.2406757
Filename
7095588
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