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.
| Original language | English (US) |
|---|---|
| Title of host publication | Critical Information Infrastructures Security - 13th International Conference, CRITIS 2018, Revised Selected Papers |
| Editors | Eric Luiijf, Inga Žutautaitė, Bernhard M. Hämmerli |
| Publisher | Springer Verlag |
| Pages | 29-41 |
| Number of pages | 13 |
| ISBN (Print) | 9783030058487 |
| DOIs | |
| State | Published - Jan 1 2019 |
| Event | 13th International Conference on Critical Information Infrastructures Security, CRITIS 2018 - Kaunas, Lithuania Duration: Sep 24 2018 → Sep 26 2018 |
Publication series
| Name | Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) |
|---|---|
| Volume | 11260 LNCS |
| ISSN (Print) | 0302-9743 |
| ISSN (Electronic) | 1611-3349 |
Other
| Other | 13th International Conference on Critical Information Infrastructures Security, CRITIS 2018 |
|---|---|
| Country | Lithuania |
| City | Kaunas |
| Period | 9/24/18 → 9/26/18 |
Fingerprint
Keywords
- Identifying codes
- PMU placement
- Transformer health
ASJC Scopus subject areas
- Theoretical Computer Science
- Computer Science(all)
Cite this
Health monitoring of critical power system equipments using identifying codes. / Basu, Kaustav; Padhee, Malhar; Roy, Sohini; Pal, Anamitra; Sen, Arunabha; Rhodes, Matthew; Keel, Brian.
Critical Information Infrastructures Security - 13th International Conference, CRITIS 2018, Revised Selected Papers. ed. / Eric Luiijf; Inga Žutautaitė; Bernhard M. Hämmerli. Springer Verlag, 2019. p. 29-41 (Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics); Vol. 11260 LNCS).Research output: Chapter in Book/Report/Conference proceeding › Conference contribution
}
TY - GEN
T1 - Health monitoring of critical power system equipments using identifying codes
AU - Basu, Kaustav
AU - Padhee, Malhar
AU - Roy, Sohini
AU - Pal, Anamitra
AU - Sen, Arunabha
AU - Rhodes, Matthew
AU - Keel, Brian
PY - 2019/1/1
Y1 - 2019/1/1
N2 - 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.
AB - 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.
KW - Identifying codes
KW - PMU placement
KW - Transformer health
UR - http://www.scopus.com/inward/record.url?scp=85059945071&partnerID=8YFLogxK
UR - http://www.scopus.com/inward/citedby.url?scp=85059945071&partnerID=8YFLogxK
U2 - 10.1007/978-3-030-05849-4_3
DO - 10.1007/978-3-030-05849-4_3
M3 - Conference contribution
AN - SCOPUS:85059945071
SN - 9783030058487
T3 - Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)
SP - 29
EP - 41
BT - Critical Information Infrastructures Security - 13th International Conference, CRITIS 2018, Revised Selected Papers
A2 - Luiijf, Eric
A2 - Žutautaitė, Inga
A2 - Hämmerli, Bernhard M.
PB - Springer Verlag
ER -