Reising, Donald R.
Loveless, Thomas D.; Karrar, Abdelrahman A.; Hay, Robert W.
College of Engineering and Computer Science
University of Tennessee at Chattanooga
Place of Publication
Power utilities employ "smart'' field devices capable of digitally recording electrical waveforms. The relationship between events and their recorded waveforms can be exploited for characterization of the power grid’s state over any period of time and facilitating the impact electrical disturbances have on equipment, subsystems, and systems. Over a period of one month, these devices record approximately 2,000 electrical disturbance waveforms. Currently, analysis of these waveforms is conducted using by-hand approaches; thus, severely limiting the analysis to roughly 2%. The analysis is done hours to days after the events occurred, which negates informed, timely corrective actions. This document presents an automated hierarchical approach capable of identifying specific events using the electrical disturbance waveforms stored using COMmon format for TRAnsient Data Exchange (COMTRADE) files. The developed approach processes a single file in 1.8 seconds and has demonstrated successful identification of 140 events with a success rate of 91%.
I would first like to thank the chair of my committee, Dr. Donald Reising, for his guidance throughout the course of this work. I wish to also thank my committee members, Dr. Abdelrahman Karrar, Dr. Thomas D. Loveless, and Mr. Bob Hay, for taking the time to assist with the completion of this thesis and for serving on my committee. Special thanks is given to Mr. Jim Glass, Mr. Bob Hay, and Mr. Raymond Johnson of Electric Power Board (EPB) of Chattanooga for allowing access to their databases, systems, providing professional guidance, and for being proactive and supportive throughout this endeavor. This project was funded by the Electric Power Research Institute (EPRI) Distribution Modernization Demonstration (DMD) Data Mining Initiative and the University of Chattanooga Foundation Incorporated. Lastly I would like to thank my wife, Bethany, for encouraging me and acting as my support system throughout the last two years.
M. S.; A thesis submitted to the faculty of the University of Tennessee at Chattanooga in partial fulfillment of the requirements of the degree of Master of Science.
Electric circuit analysis; Electric power systems; Electric power distribution
viii, 73 leaves
Wilson, Aaron, "A hierarchical approach to automated identification of anomalous electrical waveforms" (2019). Masters Theses and Doctoral Dissertations.
Available for download on Saturday, February 01, 2020