IEEE PES & PELS Chapter Meeting: Data-Driven Analysis of Events in Distribution Synchrophasors

Share

Synchrophasor measurements offer an unprecedented level of visibility in power distribution infrastructure. These are time-synchronized single-phase or three-phase voltage and current phasor measurements on medium and low voltage distribution circuits. However, data availability alone is not enough to enhance operational intelligence. In this talk, we make the case that the analysis of “events” is a key to translate the data from distribution synchrophasors into useful high-level information. An event in this study is defined rather broadly to include any major change in any component across the distribution feeder. The real data that is used in this study is obtained from a pilot distribution feeder in Riverside, CA. The goal is to enhance situational awareness in distribution grid by keeping track of the operation (or misoperation) of various grid equipment, assets, distribution energy resources, loads, etc. A combination of data-driven machine learning tools and hybrid model-based methodologies are discussed to automatically (and often remotely) detect, classify, and identify the causes of events and their characteristics in power distribution systems. Use cases are diverse and may include asset monitoring, non-intrusive load modeling, analysis of system dynamics, cybersecurity, etc.



  Date and Time

  Location

  Contact

  Registration



  • 8680 Balboa Ave
  • San Diego, California
  • United States 92101
  • Building: Century Park East
  • Room Number: Auditorium
  • Click here for Map

Staticmap?size=250x200&sensor=false&zoom=14&markers=32.822735%2c 117
  • Co-sponsored by PELS
  • Starts 28 October 2019 03:00 PM
  • Ends 13 November 2019 02:10 PM
  • All times are US/Pacific
  • No Admission Charge
  • Register


  Speakers

Dr. Hamed Mohsenian-Rad
Dr. Hamed Mohsenian-Rad

Topic:

Data-Driven Analysis of Events in Distribution Synchrophasors

Synchrophasor measurements offer an unprecedented level of visibility in power distribution infrastructure. These are time-synchronized single-phase or three-phase voltage and current phasor measurements on medium and low voltage distribution circuits. However, data availability alone is not enough to enhance operational intelligence. In this talk, we make the case that the analysis of “events” is a key to translate the data from distribution synchrophasors into useful high-level information. An event in this study is defined rather broadly to include any major change in any component across the distribution feeder. The real data that is used in this study is obtained from a pilot distribution feeder in Riverside, CA. The goal is to enhance situational awareness in distribution grid by keeping track of the operation (or misoperation) of various grid equipment, assets, distribution energy resources, loads, etc. A combination of data-driven machine learning tools and hybrid model-based methodologies are discussed to automatically (and often remotely) detect, classify, and identify the causes of events and their characteristics in power distribution systems. Use cases are diverse and may include asset monitoring, non-intrusive load modeling, analysis of system dynamics, cybersecurity, etc.

Biography:

Dr. Hamed Mohsenian-Rad is an Associate Professor of Electrical and Computer Engineering and a Bourns Family Faculty Fellow at the University of California, Riverside. His research interests include developing hybrid data-driven and model-based techniques for monitoring, control, and optimization of power systems and smart grids. He has received the National Science Foundation (NSF) CAREER Award, a Best Paper Award from the IEEE Power and Energy Society (PES) General Meeting, and a Best Paper Award from the IEEE International Conference on Smart Grid Communications. Two of his papers are currently ranked as the two most cited journal articles in the field of smart grids. Dr. Mohsenian-Rad is the founding Director of the UC-National Lab Center for Power Distribution Cyber Security, a new cyber-security research initiative across four University of California campuses and two DoE National Labs. He also serves as the Associate Director of the Winston Chung Global Energy Center, an endowed research center in the area of energy and sustainability at UC Riverside. He has served as the PI for over $10 million smart grid research projects. He received his Ph.D. in Electrical and Computer Engineering from the University of British Columbia, Vancouver, Canada in 2008. He currently serves as an Editor of the IEEE Transactions on Smart Grid, an Editor of the IEEE Power Engineering Letters, Vice-Chair of the IEEE Smart Grid Communications Technical Committee, and co-Chair of the IEEE Power and Energy Society Working Group on Big Data Access and Research Integration. Dr. Mohsenian-Rad received the UC Riverside Bourns College of Engineering Distinguished Teaching Award in 2017.

Address:San Diego, United States





Agenda

6:00 - 6:30 pm: Food and Networking

6:30 - 8 pm: Presentation and Q/A