John Pierre (UMN Alum, MS 1989, PhD 1991)
University of Wyoming
This presentation discusses signal processing and advanced system identification methods applied to monitoring the stability of a power grid. An interconnected power grid is arguably one of the most complicated systems to model. Of particular interest are a power system’s electromechanical modes which play a critical role in a system’s stability. A massive 1996 power outage in the western US was associated with an electromechanical mode going unstable. Utilities have installed extensive networks of PMU’s (Phasor Measurement Units) which collect GPS synchronized data from throughout the grid. Over the years, our research has developed and applied many signal processing and identification techniques for both ambient conditions and situations where a probing signal is applied to the grid. These various methods are overviewed in the presentation. Not only are the mode frequencies and damping ratios of interest, but so are the mode shapes which give system operators information about what generators are participating in the oscillation. One of the challenges is validating the estimated mode parameters. One approach we use is Bootstrap statistical techniques. Also, the design of input probing signals is also discussed. Numerous experimental results are presented, including results from extensive system wide tests of the US western power grid which were carried out by the Western Electricity Coordinating Council (WECC). These tests included thumping the grid by inserting a 1400 MW resistor for one half of a second, probing the system more gently with a 125 MW signal injected at the Pacific High Voltage DC Intertie, and probing even more gently with a 20 MW pseudo random signal. This research has been conducted at the University of Wyoming in collaboration with PNNL (Pacific Northwest National Laboratories), BPA (Bonneville Power Administration) and DOE (Department of Energy). A more recent project is under way in collaboration with a number of eastern US utilities.
John Pierre is a professor in the Department of Electrical and Computer Engineering at the University of Wyoming. He earned his B.S. degree in EE with a minor in Economics from Montana State University. After working as a design engineer for Tektronix, he continued his education at the University of Minnesota where he received his M.S. and Ph.D. degrees in EE in 1989 and 1991 with a minor in Statistics. He joined the faculty at UW in 1992 and served as Interim Department Head from 2003 to 2004. He has been a UW NASA Space Grant Faculty Fellow, a Department of Energy AWU Faculty Fellow, and recently spent part of his sabbatical working at Pacific Northwest National Laboratories (PNNL) and Montana Tech.
Dr. Pierre’s research interests include applied statistical signal processing and digital signal processing education. He has received research funding from the National Science Foundation, the Department of Energy, NASA, Bonneville Power Administration, Tektronix, the Power Systems Research Consortium, and the Rockwell Foundation. Early in his career his primary research was on sensor array and communication system calibration where he received a patent on a vector calibration system. He also worked with Intermountain Laboratories on infrasonic sensor arrays for avalanche detection. In recent years, he has developed a significant research program investigating signal processing and system identification techniques to help monitor the stability of a power grid.
He has published over 100 professional journal and conference papers. Over half of those have been co-authored by graduate students. His graduate students have gone on to take jobs in industry, government laboratories, and universities. Dr. Pierre is a Senior Member of IEEE. He serves on a technical committee for the IEEE Signal Processing Society and was the Co-General Chair of the 2006 IEEE Digital Signal Processing Workshop. In 2005, he received UW’s College of Engineering Sam Hakes Research and Graduate Teaching Award which recognizes the college’s leading research faculty. He also received the Mortar Board Top Prof Award in 2000 and 2002. In 2009, he received a Technical Committee Prize Paper Award from the IEEE Power and Energy Society.