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Fault Location in Overhead Transmission Lines Based on Magnetic Signatures and on the Extended Kalman Filter
- Source :
- IEEE Access, Vol 9, Pp 15259-15270 (2021)
- Publication Year :
- 2021
- Publisher :
- IEEE, 2021.
-
Abstract
- This paper proposes a non-contact method for fault location in transmission lines, which is based on magnetic fields produced by current signals measured using magnetoresistive sensors installed only at transmission line terminals, under the phase conductors of the first transmission tower at both terminals or at the substations portals. The proposed method uses the Extended Kalman filter to process these measurements and is based on a travelling wave approach in order to perform the fault localization. This paper also describes the implementation and testing of the method, firstly introducing its overview, followed by an analysis of the magnetic fields produced by the current signals, as well as considerations on their measurement; secondly, detailing the Extended Kalman filter and the travelling wave approach; and, finally, presenting the results of the method with regards to simulations built using EMTP/ATP to evaluate its robustness under different conditions varying the fault resistance, fault inception angle, phases involved and fault location. The results indicate that the proposed method is robust and accurate.
- Subjects :
- General Computer Science
Magnetoresistance
Computer science
020209 energy
020208 electrical & electronic engineering
General Engineering
02 engineering and technology
Fault (power engineering)
Magnetic field
electromagnetic propagation
Extended Kalman filter
Electrical fault detection
power systems
Electric power transmission
Robustness (computer science)
magnetic field measurement
0202 electrical engineering, electronic engineering, information engineering
Electronic engineering
Overhead (computing)
General Materials Science
fault location
lcsh:Electrical engineering. Electronics. Nuclear engineering
Kalman filters
lcsh:TK1-9971
Transmission tower
Subjects
Details
- Language :
- English
- ISSN :
- 21693536
- Volume :
- 9
- Database :
- OpenAIRE
- Journal :
- IEEE Access
- Accession number :
- edsair.doi.dedup.....0409773969a3ddf44f58258a46514ae6