DISTRIBUTION TRANSFORMER ASSET MONITORING ON THE GRID EDGE USING SMART SENSOR DATA

Other · Mon Jan 25 04:00:00 EST 2021

OSTI ID:1923994

Ashok, Kavya ^[1]

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1. Georgia Institute of Technology, Atlanta, GA (United States); Georgia Institute of Technology

As new loads such as rooftop photovoltaics, electric vehicles and other distributed energy resources become commonplace on the distribution grid, the stress on already aging assets begins to escalate. This increased loading and changing dynamics can exacerbate failure rates. While traditional monitoring efforts focus on transmission and generation assets, utilities are now beginning to pay close attention to distribution assets in order to increase reliability indices and reduce cost from unexpected outages. This research develops low-cost and scalable methods to monitoring the health of a critical distribution grid asset: the service transformer. Existing methods in literature are either invasive and thus difficult to implement or require the device to be tested offline in an expensive lab setting. Data from the ubiquitous smart meter as well as a novel Bluetooth based transformer monitor are leveraged to automatically notify the utility of deteriorating or damaged transformers. Voltage, temperature, and vibration are some of the signals measured and analyzed by the proposed algorithms to predict transformer failures. Furthermore, these algorithms are designed to keep the implementation and processing costs low by taking advantage of edge computing where possible.

• Research Organization: Georgia Institute of Technology
• Sponsoring Organization: USDOE Office of Electricity Delivery and Energy Reliability, Via the National Energy Technology Laboratory
• DOE Contract Number: OE0000877
• OSTI ID: 1923994
• Country of Publication: United States
• Language: English

Related Subjects

24 POWER TRANSMISSION AND DISTRIBUTION