Monitoring Parameters of Positive Sequence and Three-Phase Power Network Models

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In this talk we will first present a method to detect permanent errors in utility data bases related to positive sequence transmission line models used by the network applications for operation as well as planning. We will then extend this method to non-symmetrical mixed-phase distribution networks. The talk will also cover an on-line method to track changes in the parameters of three-phase transmission line models which are monitored by synchronized measurements at line terminals. The first method involves a novel approach that modifies the existing state estimators in order to enable detection and differentiation between errors in analog measurements and line model parameters. The main advantage of the method is that it does not require any user intervention or a priori selection of a suspect parameter set, instead the method identifies all existing erroneous parameters in a large-scale power system data base even in the presence of measurement errors. Modal decomposition and compensation methods will be used to extend the method to three-phase systems. The second method combines static state estimation and dynamic parameter estimation to develop an algorithm which can track detailed three-phase un-transposed transmission line model parameters as they vary due to environment conditions or abrupt disturbances. The talk will provide results obtained by applying the developed techniques to synthetic as well as actual power systems.



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  • Date: 19 Nov 2021
  • Time: 03:05 PM to 03:55 PM
  • All times are (GMT-07:00) MST
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  • Salt Lake City, Utah
  • United States 84112

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  • Co-sponsored by University of Utah


  Speakers

Northeastern University

Topic:

Monitoring Parameters of Positive Sequence and Three-Phase Power Network Models

In this talk we will first present a method to detect permanent errors in utility data bases related to positive sequence transmission line models used by the network applications for operation as well as planning. We will then extend this method to non-symmetrical mixed-phase distribution networks. The talk will also cover an on-line method to track changes in the parameters of three-phase transmission line models which are monitored by synchronized measurements at line terminals. The first method involves a novel approach that modifies the existing state estimators in order to enable detection and differentiation between errors in analog measurements and line model parameters. The main advantage of the method is that it does not require any user intervention or a priori selection of a suspect parameter set, instead the method identifies all existing erroneous parameters in a large-scale power system data base even in the presence of measurement errors. Modal decomposition and compensation methods will be used to extend the method to three-phase systems. The second method combines static state estimation and dynamic parameter estimation to develop an algorithm which can track detailed three-phase un-transposed transmission line model parameters as they vary due to environment conditions or abrupt disturbances. The talk will provide results obtained by applying the developed techniques to synthetic as well as actual power systems.

Biography:

Ali Abur received his B.S. degree at Orta Dogu Teknik Universitesi, Ankara, Turkey and M.S. and Ph.D. degrees from The Ohio State University. After graduation he joined the Department of Electrical Engineering at Texas A&M University where he worked as a Professor until 2005. He then moved to the Department of Electrical and Computer Engineering at Northeastern University in Boston where he served as the department chair until 2013. He is currently a professor in the same department. He co-authored the book “Power System State Estimation” and published several technical papers and reports on the same topic. He served as an Editor for IEEE Transactions on Power Systems between 1999 and 2011. He is a Fellow of the IEEE.