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Health Monitoring of Critical Power System Equipments Using Identifying Codes

  • Kaustav BasuEmail author
  • Malhar Padhee
  • Sohini Roy
  • Anamitra Pal
  • Arunabha Sen
  • Matthew Rhodes
  • Brian Keel
Conference paper
Part of the Lecture Notes in Computer Science book series (LNCS, volume 11260)

Abstract

High voltage power transformers are one of the most critical equipments in the electric power grid. A sudden failure of a power transformer can significantly disrupt bulk power delivery. Before a transformer reaches its critical failure state, there are indicators which, if monitored periodically, can alert an operator that the transformer is heading towards a failure. One of the indicators is the signal to noise ratio (SNR) of the voltage and current signals in substations located in the vicinity of the transformer. During normal operations, the width of the SNR band is small. However, when the transformer heads towards a failure, the widths of the bands increase, reaching their maximum just before the failure actually occurs. This change in width of the SNR can be observed by sensors, such as phasor measurement units (PMUs) located nearby. Identifying Code is a mathematical tool that enables one to uniquely identify one or more objects of interest, by generating a unique signature corresponding to those objects, which can then be detected by a sensor. In this paper, we first describe how Identifying Code can be utilized for detecting failure of power transformers. Then, we apply this technique to determine the fewest number of sensors needed to uniquely identify failing transformers in different test systems.

Keywords

Transformer health Identifying codes PMU placement 

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Copyright information

© Springer Nature Switzerland AG 2019

Authors and Affiliations

  • Kaustav Basu
    • 1
    Email author
  • Malhar Padhee
    • 2
  • Sohini Roy
    • 1
  • Anamitra Pal
    • 2
  • Arunabha Sen
    • 1
  • Matthew Rhodes
    • 3
  • Brian Keel
    • 3
  1. 1.NetXT Lab, SCIDSEArizona State UniversityTempeUSA
  2. 2.Pal Lab, SECEEArizona State UniversityTempeUSA
  3. 3.Salt River ProjectTempeUSA

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