Binghamton Data Science TAE / IEEE PES Seminar: Integrated Dynamic State Estimation in Power Systems

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Abstract:

To make well-informed decisions, power system operators need accurate timely estimates of the operational conditions of the power grid. Up to the present time, conventional static state estimators have been widely deployed in utility control centers to improve the estimation accuracy and expand the monitoring areas. However, these estimators are no longer sufficient for monitoring the modern power grid, which is experiencing increasing uncertainty and variation driven by the high penetration of intermittent renewable energy sources (mainly solar and wind). In fact, conventional static state estimation methods for power grids often fail to provide any useful information during transmission-line tripping and cascading grid failures when the power system rapidly changes, and state estimation results are crucially needed.

In this presentation, the conventional state estimation is reviewed. Also, a dynamic state estimation (DSE) approach is proposed that can not only estimate current operational conditions but also predict their future trends and quantify their uncertainty. To minimize the financial cost of measurement devices while achieving observability of important system states, observability and detectability studies are carried out to guide measurement placement and model selection. It is shown that many dynamic states in the power systems are marginally observable (virtually unobservable). If an observer model can be chosen to make the eigenvalues of the corresponding states stable, the DSE can still converge to the true value of the states.



  Date and Time

  Location

  Hosts

  Registration



  • Date: 02 Dec 2022
  • Time: 12:00 PM to 01:00 PM
  • All times are (UTC-05:00) Eastern Time (US & Canada)
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Join Zoom Meeting
https://binghamton.zoom.us/j/97007113079

Meeting ID: 970 0711 3079

  • 4400 Vestal Pkwy East
  • Binghamton University
  • BINGHAMTON, New York
  • United States 13902
  • Building: Academic A
  • Room Number: 340
  • Click here for Map

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  • Co-sponsored by Binghamton Data Science TAE
  • Starts 28 November 2022 09:00 PM
  • Ends 01 December 2022 10:30 PM
  • All times are (UTC-05:00) Eastern Time (US & Canada)
  • No Admission Charge


  Speakers

Ning Zhou Ning Zhou

Biography:

About the speaker: Ning Zhou is currently with the Electrical and Computer Engineering Department at Binghamton University. In 2005, he received his Ph.D. in Electrical Engineering with a minor in statistics from the University of Wyoming. From 2005 to 2013, Dr. Zhou worked as a power system engineer at the Pacific Northwest National Laboratory. His research interests include power system dynamics and statistical signal processing. He is the PI of the NSF CAREER award titled “Integrated Dynamic State Estimation for Monitoring Power Systems under High Uncertainty and Variation” in the year of 2019. 





Agenda

Lunch available.

Parking info for external guests: Please park at the visitor parking lot and get a ticket when you enter the parking lot. Bring your ticket to Dr. Ning Zhou. We will give you a prepaid parking pass for exiting the parking lot. Here is the direction from the visitor parking lot to Acdiamic Building A: Parking map



  Media

parking map 1.23 MiB