event
Ph.D. Dissertation Defense - Kavya Ashok
Primary tabs
Title: Distribution Transformer Monitoring on the Grid Edge using Smart Sensor Data
Committee:
Dr. Deepak Divan, ECE, Chair , Advisor
Dr. Nagi Gebraeel, ISyE
Dr. Santiago Grijalva, ECE
Dr. Lukas Graber, ECE
Dr. Matthew Reno, Sandia Energy
Abstract: 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.
Status
- Workflow Status:Published
- Created By:Daniela Staiculescu
- Created:11/30/2020
- Modified By:Daniela Staiculescu
- Modified:11/30/2020
Categories
Keywords
Target Audience